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For this week’s Notorious, my friends at Standard Metrics previewed some of their benchmarking data on global startup revenue growth. I’d be curious to get your take on why revenue growth rates have been declining. The simple explanation might be that during the crazy years of 2021-2022, startups had more access to capital which meant more marketing spend and sales team growth which artificially inflated growth rates during that period. Big thanks to John Melas-Kyriazi, David Miller and Maile McCann and be on the lookout next week for the full benchmarking report!

Startup Revenue Growth Benchmarking

Standard Metrics is committed to answering an age-old question in VC and PE: how can I measure my or my portfolio company’s performance against other startups in the private markets?

When we first founded Standard Metrics in 2020, our product suite focused on creating tools to help build what we described as a “lingua franca” or common language between VCs and their portfolio companies. We invested in better data collection, time-saving analysis tools, and easy reporting tech like exportable tear sheets to streamline communication between investors and their portcos.

By 2024, we realized that our platform had become a treasure trove of private market data, with millions of performance data points built from the financial statements of hundreds of firms’ thousands of startups (across different industries, sizes, and regions). We decided to launch our first data product late that year — Global Benchmarking — to help our customers with a common problem: establishing a like-to-like comparison while assessing the performance of their portfolio. Today, over 9,000 startups have chosen to opt in to the product, helping us establish a robust data set of over four years of historical performance across metrics like revenue, runway, growth, and gross margin.

To highlight this data, we started sharing a series of free, ungated benchmarking reports, showcasing the stories that we found most interesting in our data each quarter. We’re publishing our full report next week, but are excited to give Notorious readers a sneak peak into how startups fared in Q1 2025 before it’s out.

How Global Benchmarking highlights a consistently tough Q1 in the private markets

Standard Metrics’ Global Benchmarking data highlighted a significant drop in quarterly revenue growth across companies of all sizes in Q1 this year — with median quarterly revenue growth dropping between 3 and 5 percentage points quarter-over-quarter. Interestingly, this isn’t just a point-in-time trend: since 2021, we’ve seen companies consistently increase in quarterly revenue growth in Q4, then decline in quarterly revenue growth in Q1.

This is even true for top performing companies: upper quartile revenue growth dropped by 8 to 10 percentage points quarter-over-quarter in Q1 2025.

We were curious if this trend was being influenced by industry biases. Consumer startups, for example, have an almost unavoidable December holiday boost and January post-holiday slump. While consumer startups were most affected by this trend, we saw the same results in other industries like fintech, SaaS, and even AI.

We were also curious if this performance decrease was affected by macroeconomic headwinds. However, given the cyclical nature of this trend, Standard Metrics didn’t necessarily see tariffs wildly affecting startups in Q1 2025, though future effects remain to be seen. (While President Trump began to research tariffs in February, more active implementation began in April, after the quarter closed.)

Instead, some combination of holiday sales, lower household discretionary income, and startups pushing big deals to close before the holidays may have all been more likely explanations for this consistent Q1 drop.

Why (we think) this matters and what’s next

A value that we think that Standard Metrics’ Global Benchmarking data can bring to both firms and startups is an ability to contextualize, both in comparison to other startups and in comparison to other startups over long periods of time. When a company’s performance is looked at in isolation, it’s easy to over- or under- appreciate wins as well as miss important signs of trouble.

A new company examining a revenue growth drop in isolation, for example, might initially panic at the performance. But with our Q1 2025 data, they’d have the context of a market-wide downturn in the metric to better understand performance.

We hope the other stories we examine in our upcoming report — how fintech vs. SaaS are handling an AI sea change and how companies are stacking up in IPO-readiness — also bring readers more global context into the private markets.Get in touch if you’d like us to send it to you next week when it launches!

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• Amperos Health, a multi-modal AI billing platform built specifically for healthcare providers to reduce denials and streamline claims collections, has raised $4.8M. The round was led by Nebular, Uncork Capital and Neo.

• Archil, a default storage platform for cloud applications built for data teams, has raised $6.7M. The round was led by Felicis, with participation from Lombardstreet Ventures, Peak XV Partners, Wayfinder Ventures, General Catalyst, Twenty Two Ventures and Y Combinator.

• Console, a startup specializing in automating IT help desk tasks using AI, has raised $6.2M. The round was led by Thrive Capital, with participation from Zeal Talent Ventures.

• Deepdots, an end-to-end AI platform that unifies and analyzes customer feedback at scale, has raised $6.2M. The round was led by Dawn Capital, with participation from Maki.vc.

• Delpha, a startup developing an autonomous AI agent focused on commercial data quality, has raised $2M. The round was led by 50 Partners.

• Hirundo, a startup offering technology designed to surgically remove unwanted data and behaviors from already-trained AI models, has raised $8M. The round was led by Maverick Ventures Israel, with participation from SuperSeed, Tachles VC, Alpha Intelligence Capital, AI.Fund and Plug and

• Latent Technology, a game technology company focused on AI-driven physical animation, has raised $8M. The round was led by Spark Capital and AlbionVC, with participation from Root Ventures and Alumni Ventures.

• Solidroad, an AI-powered QA and training platform for modern customer experience teams, has raised $6.5M. The round was led by First Round Capital, with participation from Y Combinator.

• Tenzai, a startup operating in stealth at the intersection of cybersecurity and artificial intelligence, has raised $32M. The round was funded by Battery Ventures and Greylock.

• Thunder Code, a generative AI-powered software testing platform that uses agents to mimic human testers, has raised $9M. The round was led by Silicon Badia, Titan Capital and Janngo.

• Veris.AI, an end-to-end platform for teaching AI agents to perform enterprise tasks, has raised $8.5M. The round was led by Decibel Partners and Acrew Capital, with participation from The House Fund.

Series A:

• Aive, an AI platform that automates video post-production for businesses, has raised $13.5M. The round was led by The Invus Group, with participation from BNP Paribas Développement.

• Handoff, an AI assistant designed specifically for residential construction contractors, has raised $5.7M at an $87.65M valuation. The round was led by Masco Ventures, with participation from Nemetschek Group, Afore Capital, Initialized Capital Management, Greycroft and Y Combinator.

• Impart Security, an AI-powered security platform designed to operate autonomously in production environments, has raised $12M at a $62M valuation. The round was led by Madrona Venture Group, with participation from 8-Bit Capital and CRV.

• Infisical, an open-source encrypted tool that helps developers manage secrets and environment variables across teams, devices, and infrastructure, has raised $16M. The round was led by Elad Gil, with participation from Gradient Ventures, Y Combinator and Dynamic Funds.

• MIND, a data security platform that automates data loss prevention (DLP) and insider risk management (IRM) programs, has raised $30M. The round was led by Crosspoint Capital Partners and Paladin Capital Group, with participation from Okta Ventures and YL Ventures.

• Netic, an AI-based platform that helps home services firms automatically reach out to clients in need of maintenance or upgrades, has raised $13M at a $111M valuation. The round was led by Founders Fund, with participation from Greylock, Hanabi Capital Management, Day One Ventures and SV Angel.

• Sema4.ai, an enterprise AI agent platform that runs natively on Snowflake, has raised $25M at a $505M valuation. The round was funded by Benchmark, Snowflake Ventures, Cox Enterprises, Rocketship.vc, Mayfield Fund and MVP Ventures.

• Thread AI, an AI-powered platform that enables enterprises to build, connect, and manage workflows and agents, has raised $20M. The round was led by Greycroft, with participation from Index Ventures, Scale Venture Partners, Meritech Capital Partners, Homebrew and Plug and Play Tech Center.

• Toma, an AI automation platform for building personalized AI agents that automate customer communications and operational tasks for automotive dealerships, has raised $17M. The round was led by Andreessen Horowitz, with participation from Holman Growth Ventures, Flex Capital and Y Combinator.

• Trustifi, an AI-powered cybersecurity platform specializing in email security, has raised $25M. The round was led by Camber Partners.

• Wordsmith, an AI-powered platform designed for in-house legal teams to automate contract and policy reviews, has raised $25M. The round was led by Index Ventures and Kinnevik.

Series B:

• Simetrik, a B2B SaaS platform that provides finance teams with AI-driven automation tools for reconciliation, compliance, and transactional control, has raised $30M. The round was led by Growth Equity at Goldman Sachs Alternatives.

• Speedata, the developer of an ASIC processor designed to accelerate complex analytics workloads, has raised $44M. The round was funded by Viola Ventures, Walden Catalyst, 83North, Koch Disruptive Technologies, Pitango Venture Capital and ArtofIn.

Series C:

• Anysphere, a startup that offers a code editor called Cursor, which uses AI to automate programming tasks, has raised $900M at a $9B valuation. The round was led by Thrive Capital, with participation from Andreessen Horowitz, Accel and DST Global.

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Why Agents Break PLG (And How to Rebuild It)

Product-led growth (PLG) is built on a simple premise: let users use your product, get hooked on its value, and drive adoption organically. But what happens when users stop using and start delegating? The rise of AI agents, systems that perform tasks for users rather than empowering users to do them, is flipping the PLG playbook on its head. Instead of clicking around your interface, users now hand off an intention and watch the agent work. This shift challenges the very tactics PLG teams have honed for years, from onboarding flows to UI optimizations. It’s a sharp wake-up call: users aren’t “users” in the old sense anymore, and growth strategies must adapt.

When Users Delegate, Classic PLG Falls Apart

Traditional PLG assumes a hands-on user journey. A new user signs up, navigates UI, explores features, hits an “aha” moment after gradually discovering value, and moves themselves down the funnel. Onboarding checklists, tooltips, and gradual feature discovery are all designed to guide humans through using the product. But in an agentic UX, the paradigm flips: you’re not executing the task, you are managing the team who execute it. In other words, the user’s role shifts from operator to delegator. They express intent (“what” they want), and the agent handles the “how.”

This flip comes with serious side effects for PLG tactics:

• Onboarding flows break: An AI agent doesn’t need your cute interactive tour. If a user can simply tell the agent their goal and let it handle the steps, those guided walkthroughs and tooltip tutorials go unused. The user isn’t learning the interface; they’re outsourcing the work.

• UI optimization loses impact: We’ve spent years polishing UX, minimizing clicks, highlighting buttons, all assuming a human is clicking. But an agent might be using your product via API or script, or skipping the UI entirely.

• Feature discovery dwindles: In a direct-use world, users wander through menus, trial new features, and stumble on value. In an agent-driven world, nothing is stumbled upon, the agent executes exactly what the user requested, no more, no less. The user might never see half your features, even if the agent uses them in the background.

• “Aha” moments and usage-based activation weaken: PLG teams love to track the moment a user first realizes the product’s value (the aha moment) and the usage milestones that correlate with retention (e.g. “user uploaded 10 files”). With agents, value can be delivered in a single, delegated leap. The user’s “aha” might simply be the task got done. They didn’t click 10 times or slowly build up usage; the agent just did the thing.

In short, AI agents break the linear, user-driven progression that PLG optimizes for. Instead of a journey from novice to power-user, we get users who issue a command and expect instant outcomes. The old growth levers – optimize funnel steps, drive feature adoption, nail the UX – feel wobbly when the user isn’t actually in the driver’s seat.

Agents vs Toolkits: Examples in the Wild

This isn’t theoretical, it’s happening now. Let’s look at a few examples of agentic products and how differently they operate compared to traditional tool-like products:

• Perplexity’s Copilot: If Google is a search engine, Perplexity is an answer engine. Its AI “copilot” acts like a genius intern that does research for you: it performs the searches, reads through the links, summarizes what matters, and provides answers with references. Instead of the user manually querying and clicking, the agent handles the workflow. For PLG, onboarding and UI don’t matter much, the user’s loyalty hinges on result quality, not interface mastery.

• Windsurf: Windsurf is an AI-native IDE designed for a world where AI writes 90% of the code. Developers describe features and review AI-generated changes, rather than manually building everything. The product is structured around delegation, not exploration. Traditional activation metrics like “first 5 edits” or “time to Hello World” don’t apply when the agent handles the heavy lifting.

• Granola: Granola is an AI notepad that joins meetings, transcribes conversations, and handles follow-ups like drafting recap emails and creating summaries. Users barely touch the product. All the engagement happens under the hood, but value is still delivered. Notes written, emails sent, summaries created, all by the agent. PLG metrics like feature usage or editing time are irrelevant here.

Each of these products shows the same shift: agents treat products as tool, while users just expect results. The agent doesn’t need to explore your features or appreciate your UI. And the user doesn’t care how the result got done – only that it did.

Rebuilding PLG for an Agent-Native World

If AI agents change how users experience value, then PLG needs to evolve. Here’s how to rebuild it:

1. Optimize for intent capture, not feature engagement

Your “aha moment” is no longer clicking feature X, it’s expressing an intent and getting what you want. Focus onboarding around helping users articulate their goal clearly. Build interfaces (or APIs) that make it dead simple to say: this is what I need. Your new activation event is a successful delegation.

2. Make outcomes measurable and shareable

Since users won’t click around anymore, make results the product. Track outcomes: reports generated, emails drafted, actions completed. Then make them shareable. Let users send, export, or broadcast those results easily. That’s your new growth loop.

3. Rethink onboarding as “delegation setup”

It’s not about teaching users where the buttons are. It’s about giving the agent access, context, and preferences to do the job right. Did they connect their calendar? Upload data? Define success criteria? That’s the new onboarding checklist.

4. Design for trust, transparency, and reversibility

Users need to feel safe letting agents act on their behalf. Let them preview outputs, approve actions, see what happened, and undo mistakes. The more control you give users over the agent, the more they’ll let go — and that’s where retention lives.

The Bottom Line

AI agents break classic PLG. They short-circuit UI journeys, skip onboarding, and render usage-based metrics meaningless. But they also open the door to a new kind of growth, one rooted in intent, outcomes, and delegation. If you can capture what the user wants, deliver it autonomously, and prove it’s working, you win.

PLG isn’t dead. But your user might not be the user anymore. The agent is. And it’s time we started building for that.

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango and Workmate.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• Agree, an AI-powered agreements platform that automatically detects and labels all input fields and signature blocks in contracts, has raised $7.2M at a $30M valuation. The round was led by Pelion Venture Partners, with participation from Better Tomorrow Ventures, Everywhere Ventures, 8-Bit Capital, FirsthandVC, Hustle Fund, Singh Capital Partners, Trust Fund and Blank Ventures.

• Fastino, an AI model architecture company building task-specific language models, has raised $17.5M. The round was led by Khosla Ventures, with participation from Dropbox Ventures, Valor Equity Partners and Insight Partners.

• Korl, an AI-first platform that generates customer-ready presentations and messaging for roadmap, QBR, and renewal conversations, has raised $5M. The round was led by MaC Venture Capital and Underscore VC, with participation from Perceptive Ventures.

• Rork, an AI platform for building mobile applications using only natural language prompts, has raised $2.8M. The round was led by Cheyenne Partners and Innovius Capital, with participation from Salesforce Ventures, Snowflake Ventures and Norwest Venture Partners.

• SSOReady, an open-source authentication infrastructure for B2B software companies, has raised $3.3M. The round was funded by Y Combinator.

• TensorStax, an agentic platform designed to build and maintain data pipelines, has raised $5M. The round was led by Glasswing Ventures, with participation from Bee Partners, S3 Ventures, Mana Ventures and Gaingels.

• WisdomAI, an AI-powered business insights platform that uses intelligent agents to deliver deep understanding of company data, has raised $23M. The round was led by Coatue Management, with participation from Madrona Venture Group, GTM Capital and Menlo Ventures.

• Luzia, an AI-powered personal assistant that helps users manage daily tasks by answering questions and providing personalized support, has raised $13.5M. The round was led by Prosus Ventures, with participation from Khosla Ventures and Monashees.

Series A:

• Glide Finance, an AI-powered growth platform for credit unions and community banks, has raised $15M. The round was led by Acrew Capital, with participation from Pathlight Capital and Pear.

• Sett, an agentic AI platform that enables mobile gaming studios to create data-driven marketing and in-game content at scale, has raised $15M. The round was led by Bessemer Venture Partners, with participation from vgames and Saga Ventures.

• Trek Health, an AI-powered platform that helps healthcare organizations benchmark and negotiate their payer contracts using real market data, has raised $11M at a $28M valuation. The round was led by Madrona Venture Group, with participation from Founder Collective, Correlation Ventures, LifeX Ventures, SNR and Accrete Health Partners.

• Unblocked, an AI-powered coding assistant that answers contextual questions about lines of code, has raised $20M. The round was funded by Radical Ventures and B Capital.

Series B:

• 7Learnings, an AI-powered optimization platform for B2C companies, has raised $10M. The round was led by Accel and New Enterprise Associates, with participation from Tru Arrow Partners, Valor Equity Partners, Overmatch and StepStone Group.

• Carta Healthcare, a startup using AI, machine learning, and clinical expertise to automate the collection and analysis of clinical data, has raised $18.25M. The round was led by UPMC Enterprises, with participation from CU Healthcare Innovation Fund, Rex Health Ventures, MemorialCare Innovation Fund, Tampa General Hospital, Memorial Hermann Health System, Mass General Brigham Ventures, Storm Ventures, Paramark Ventures and Frist Cressey Ventures.

• Recraft, an AI-powered image generation platform designed for professional designers with a focus on brand consistency, has raised $30M at a $148M valuation. The round was led by Accel, with participation from Khosla Ventures, RTP Global and Madrona Venture Group.

• Relevance AI, an AI agent operating system that enables companies of all sizes to build and deploy AI agent workforces, has raised $24M. The round was led by Bessemer Venture Partners, with participation from Insight Partners, King River Capital and Peak XV Partners.

Series C:

• Classiq, a quantum development platform for designing, optimizing, analyzing, and executing quantum algorithms, has raised $110M. The round was led by Entrée Capital, with participation from Wing VC, IN Venture, Samsung NEXT Ventures, Phoenix Financial, Norwest Holdings, NightDragon, Clal Industries, Qbeat Ventures, Team8, NEVA SGR, HSBC Holdings and Hamilton Lane.

• Parloa, an AI Agent Management Platform that enables enterprises to build, test, and deploy AI agents, has raised $120M at a $1B valuation. The round was led by Altimeter Capital Management, General Catalyst and Durable Capital Partners, with participation from Senovo, EQT Ventures, Mosaic Ventures and Riverpoint Capital.

• Sanity, a content operating system designed to help organizations manage content across digital surfaces, has raised $85M. The round was led by GP Bullhound, with participation from Heavybit, Threshold Ventures, ICONIQ Growth, Shopify Blue Cloud Ventures and Monochrome Ventures.

• Statsig, a product development platform that helps software engineering teams test, analyze, and roll out new features, has raised $100M at a $1.1B valuation. The round was led by ICONIQ Growth, with participation from Sequoia Capital and Madrona Venture Group.

Series D:

• AI21 Labs, a startup developing enterprise AI systems and foundation models, has raised $300M. The round was led by Nvidia and Alphabet.

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Does Cursor Have a Defensible Moat?

In the world of AI code assistants, one startup has drawn both hype and some recent skepticism: Cursor, a collaborative, AI-native coding environment that’s quickly gaining traction with developers. Cursor is essentially a fork of VS Code supercharged with AI. It lets programmers chat with their codebase, generate and refactor code via natural language, and even have an “agent” complete multi-step coding tasks autonomously. Backed by big-name investors and used by engineers at companies like OpenAI and Shopify, Cursor is on a meteoric rise​. The company is reportedly in talks to raise a Series C at a $10B valuation. That's a staggering leap from its $2.5B valuation just a few months ago. With $300M+ in annual recurring revenue (ARR) and a user base of over 360,000+ developers, Cursor is making waves in the developer tools space. But amid this excitement, a pressing question has emerged: Does Cursor have a defensible moat, or just a head start in the AI coding race? Let’s debate both sides.

The Bull Case: Product Love, Integration, and First-Mover Edge

Proponents argue that Cursor’s product experience and UX are a generation ahead of the competition. Unlike retrofitting an AI plugin into an old IDE, Cursor was built AI-first. It’s a standalone editor deeply integrated with large language models (LLMs) at its core. That means features like next-action predictions, one-click code rewrites, and chatting directly with your entire repository are not bolted on, they’re woven into how you code. Developers rave that this feels like pair programming with an genius partner on call 24/7. According to A16Z (an investor), thousands of users have already signed up and “give glowing reviews of the product,” with many becoming paid users who “rarely switch back to other IDEs”. That kind of user delight and retention hints at a UX moat: once you get used to an AI co-coder that actually understands your project, going back to a dumb text editor feels painfully limiting.

Early community and feedback loops further reinforce Cursor’s advantage. As an agile startup, the Cursor team iterates at breakneck speed, pushing out new features and improvements based on user input from their forum and Discord. They’ve cultivated a passionate user base that effectively co-develops the product by surfacing pain points and wish lists. This tight feedback cycle lets Cursor stay UI/UX-forward in a way big incumbents struggle to match. The result is a fast-evolving toolkit finely tuned to developer needs, a moving target for would-be copycats. Moreover, Cursor smartly leveraged go-to-market strategy and traction among power users: by onboarding engineers at influential tech companies and engaging early adopters, they created tech buzz and FOMO. That led to rapid early traction, sources say Cursor became one of the more popular AI coding tools and even hit $4M in monthly revenue within its first year​. In the winner-takes-most world of developer tools, such a head start in users and mindshare can compound into a durable lead.

Under the hood, Cursor is also amassing a potential data and infrastructure moat. Every code generation, edit, and fix that developers perform with Cursor provides feedback (implicit or explicit) that can improve its AI models. Over time, this usage data creates a flywheel: Cursor can fine-tune its systems to better fit real-world coding patterns, catching bugs or suggesting solutions in a way generic models can’t. The company’s recent acquisition of Supermaven bolsters this data advantage as well. Supermaven brought in an in-house generative code model called Babble that can understand massive codebases with super-low latency​. By integrating Babble and co-designing the AI with the editor UI, Cursor controls more of the tech stack end-to-end. In other words, they’re not just calling OpenAI’s API; they’re gradually developing proprietary model enhancements tailored to their users’ workflows. Combine that with the practical infrastructure work (optimizing context window sizes, indexing entire repos, ensuring privacy modes for enterprise​), and you get a product that’s technically hard to replicate. First-mover advantage in this space isn’t just about being first to launch, it’s about having spent thousands of hours solving gnarly integration issues (AI prompt management, multi-file editing UX, etc.) that any newcomer will also have to figure out. Team and execution matter for moats too: Cursor’s team seems obsessed with AI coding and laser-focused on experience, which has led them to “simply get it right” where others have stumbled​. All these factors form a narrative that Cursor is digging a wide trench around its lead in AI-assisted development environments.

The Bear Case: Commoditized Brains and Imitators at the Gate

Yet for all those strengths, skeptics counter that Cursor’s moat might be more mirage than fortress. The harsh reality of the AI world in 2025 is that the brains behind Cursor, the large language models doing the heavy lifting, are rapidly commoditizing ad evidenced how good Claude Code is becoming. Today’s underlying model that powers Cursor’s code genius (whether it’s GPT-4, Claude, another API, or Babble) could be matched by an open-source equivalent tomorrow. In fact, we’re already seeing open models catch up to proprietary ones at breakneck speed. Meta’s open release of Code Llama and its successors has demonstrated GPT-4-level coding prowess in the wild​, and a host of community-driven models (e.g. StarCoder, Mistral) are improving monthly. One recent analysis put it bluntly: “LLMs are… commoditized components” of the stack now, and the only real differentiator is the data or ecosystem built around them​. This means that any technological edge Cursor has due to its AI could prove fleeting. A determined competitor can take the same open-source LLM that Cursor uses or fine-tunes, fork the same open-source VS Code base, and end up with a very similar product. In other words, if the secret sauce is just “VS Code + good LLM,” it’s not much of a secret. As one Hacker News commenter quipped, “Clone VS Code, add a few custom blobs and extensions, API to existing LLMs. For that, $20 a month?” The barriers to entry in AI coding assistants aren’t huge when everyone has access to state-of-the-art models and a popular editor framework.

Competition in this arena is not theoretical, it’s already here, and coming from all sides. Large incumbents are baking AI into their own tools: Microsoft’s VS Code isn’t standing still (recent releases hint at more AI-native features to fend off Cursor​), and GitHub Copilot (with ChatGPT in the backend) is deeply integrated into developers’ existing workflows. GitHub has an army of 1.8 million paying Copilot users and is rolling out its own Chat and voice features in the IDE. Windsurf has been growing very fast and has high user love, but is rumored to be acquired by OpenAI for $3B which will further extend its distribution. Amazon has CodeWhisperer. Upstart Replit, with its Ghostwriter AI, offers an AI-powered IDE in the browser. And for the highly motivated hackers, there are open-source projects to create “AIDEs” (AI development environments) that mimic Cursor’s functionality using free models. The truth is, none of Cursor’s individual features are completely unique, whether it’s code chat, autocompletion, or bulk edits, you can find an alternative implementation somewhere. Over time, what one tool can do, others tend to learn. That puts pressure on Cursor to continuously innovate just to stay ahead of the pack. If the moat rests on feature velocity, what happens when the giants start moving just as fast? OpenAI with Windsurf could move just as fast as Cursor and can ship AI features to the millions of VS Code users overnight via an update. Cursor will have to run hard to keep its early lead.

There’s also the question of sustainable advantage in the long run. While Cursor has a growing community, the network effects in developer tools are limited, this isn’t a social media platform where more users make the product inherently better for each other (aside from maybe more community plugin sharing). Developers can and will churn if a better solution comes along, especially if it’s the difference between a free built-in tool and a $20/month add-on. And though Cursor is amassing usage data, one could argue that giants like OpenAI/Windsurf and GitHub/Microsoft have an even bigger data moat (they sit on decades of coding data from GitHub repos and Copilot interactions). Open-source communities, meanwhile, benefit from each other’s improvements transparently, when someone fine-tunes an open model to improve its coding ability, everyone can use that model the next day. In this light, any data flywheel Cursor hopes to spin might be outrun by the sheer scale of data available to the open-source and Big Tech efforts. Finally, relying on others’ platforms cuts both ways: Cursor’s innovation is effectively subsidized by VS Code (open source) and by whichever AI model it uses. If Microsoft decided to change VS Code’s licensing or if OpenAI changed API terms, Cursor would have to respond. The recent snafu where Cursor’s own AI support bot hallucinated a false policy and stirred user backlash​ shows how precarious building on cutting-edge AI can be, mistakes can erode user trust, and trust is a big part of any moat.

What Cursor Could Do Next to Fortify Its Moat

If Cursor wants to convert early momentum into long-term defensibility, it can’t just keep shipping features—it needs to architect strategic moats. Here are a few areas where it could play offense:

• Own the Social Layer of Coding
  Cursor could build the social graph for developers within its IDE, think GitHub meets Figma meets Discord. Features like real-time collaboration, shared debugging sessions, and public code walkthroughs could turn Cursor into the place where devs not only write code, but build reputation, relationships, and learning loops. The more developers use it to work together, the harder it is to leave.

• Go Deep on Proprietary Data Flywheels
  Cursor can lean into fine-tuning its AI on actual user behavior: common bug patterns, code review preferences, preferred architecture choices. If that data stays in-house and improves model performance in ways open competitors can’t match, that becomes a self-reinforcing moat.

• Verticalize for Teams and Enterprises
  Move from individual developer workflows to team-based ones. Cursor could become the AI-native replacement for static internal wikis, onboarding docs, and code reviews. Integrations with CI/CD, observability tools, and ticketing systems would further lock in adoption at the org level.

• Turn Cursor Into a Platform
  Opening up Cursor to third-party plugins, agents, or even model extensions would create an ecosystem around it. If devs build on top of Cursor instead of just inside it, platform dynamics kick in, and platforms are much harder to displace than products.

• Own the Deployment Loop
  If Cursor expands from code generation to code deployment (preview environments, edge shipping, AI-assisted testing), it could become the default place where code goes from prompt to production. That end-to-end loop would be tough to unseat.

So, Moat or Not?

Ultimately, whether Cursor has a defensible moat comes down to which narrative wins out. On one side, you have the argument that Cursor’s exceptional developer experience, tight-knit community, and head start in integrating AI deeply into coding workflows will give it a lasting edge. Its focused team and fast execution could keep it ahead of slower-moving rivals, and over time it might accumulate proprietary advantages (data, fine-tuned models, enterprise integrations) that form a real moat. On the other side, you have the reality that the core technology, LLMS that write code, is becoming a commodity, and a slew of competitors (from open-source enthusiasts to trillion-dollar companies) are racing through the same opportunity. I would say Cursor has amassed some moats from its first mover advanatge and its on them to keep building the best product. If they do that, users will stick with them and continue to flock to the product, but competition is fierce and racing to catch up.

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango and Workmate.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• Adaptive Computer, a no-code web app platform built for non-programmers to create apps using text prompts, has raised $7M at a $28M valuation. The round was led by Pebblebed, with participation from Weekend Fund, Conviction Partners and Anti Fund.

• Amplifier, a security platform that uses AI to automate user engagement and close security gaps in real time, has raised $5.6M. The round was led by WestWave Capital and Cota Capital.

• Cluely, an AI app that delivers live answers to users, has raised $5.3M. The round was led by Abstract Ventures and Susa Ventures.

• Kenzo Security, an agentic AI platform designed to help security teams manage the many facets of modern security operations, has raised $4.5M. The round was led by The General Partnership.

• P-1 AI, an AI-powered engineering agent that helps users design physical systems more efficiently, has raised $23M. The round was led by Radical Ventures, with participation from Predictive Venture Partners, Schematic Ventures, VitalStage Ventures and Village Global.

• Ravenna, an AI-powered help desk tool built for teams that work in Slack, has raised $15M at a $62M valuation. The round was led by Khosla Ventures, Founders' Co-op and Madrona Venture Labs.

• Tella, a screen recording platform designed to help users create professional videos for marketing and education, has raised $2.1M. The round was led by Gradient Ventures, with participation from The Singularity Group, Mento VC, Lobster Capital and AltaIR Capital.

• Terra Security, an agentic-AI platform built for continuous web application penetration testing, has raised $7.5M at a $31M valuation. The round was led by SYN Ventures and FXP Ventures, with participation from Underscore VC.

Early Stage:

• Capably, an intelligent automation platform that helps businesses adopt AI for smarter work delegation, has raised $4.07M. The round was led by Boost Capital Partners, with participation from Telefónica, Koro Capital, Ascension, Sure Valley Ventures, Concept Ventures, Haatch, Wayra and Arāya Ventures.

• Manus AI, a multipurpose AI agent designed to control multiple models and autonomously complete complex tasks, has raised $75M at a $500M valuation. The round was led by Benchmark.

• Reco, a startup using generative AI and AI agents to help organizations strengthen the security of their SaaS applications, has raised $25M. The round was led by Khosla Ventures, Founders' Co-op and Madrona Venture Labs.

Series A:

• Ascertain, an AI-powered case management platform that automates administrative tasks for healthcare teams, has raised $10M. The round was led by Deerfield Management, with participation from Northwell Health.

• Exowatt, a renewable energy company providing modular energy solutions tailored for energy-intensive applications like data centers, has raised $70M. The round was led by Felicis, with participation from Andreessen Horowitz, 8090 Industries, MVP Ventures, MCJ, Thrive Capital, Goat Ventures, Atomic Labs, Starwood Capital Group and StepStone Group.

• Listen Labs, an AI-based interviewer designed to get insights from customers, has raised $27M. The round was led by Sequoia Capital.

• Reducto, a startup helping companies turn their most complex documents into LLM-ready inputs, has raised $24.5M. The round was led by Benchmark, with participation from First Round Capital, BoxGroup and Y Combinator.

Series B:

• Cynomi, a startup that is creating an AI-based ‘virtual CISO’ for SMB cybersecurity, has raised $37M. The round was led by Entrée Capital and Insight Partners, with participation from Flint Capital, Canaan Partners and S16VC.

• Endor Labs, a startup that builds tools to scan AI-generated code for vulnerabilities, has raised $93M at a $635M valuation. The round was led by DFJ Growth, with participation from Citi Ventures, Salesforce Ventures, Coatue Management, S32, Dell Technologies Capital and Lightspeed Venture Partners.

• Manychat, a conversational AI and automation platform for social and messaging apps, has raised $140M at a $630M valuation. The round was led by Summit Partners.

• Push Security, a cybersecurity company specializing in identity attacks in the browser, has raised $30M. The round was led by Redpoint Ventures, with participation from GV, B3 Capital, Datadog and Decibel Partners.

• Sentra, a startup offering cloud-native data security for the AI era, has raised $50M at a $205.1M valuation. The round was led by Key1 Capital, with participation from Munich Re Ventures, Bessemer Venture Partners, Zeev Ventures and Standard Investments.

Series D:

• Chainguard, a company specializing in open-source software, security, and cloud-native development, has raised $365M at a $3.5B valuation. The round was led by IVP and Kleiner Perkins, with participation from Salesforce Ventures, Fortius Ventures, Datadog, K5 Global, 515 Ventures, K5 Ventures, Amplify Partners, Sequoia Capital, Mantis VC, LiveOak Ventures, Banana Capital, Redpoint Ventures, Spark Capital, Lightspeed Venture Partners and Alpha Partners.

• Supabase, an open-source backend platform that assists developers in building and managing applications, has raised $200M at a $2B valuation. The round was led by Accel, with participation from Coatue Management, Felicis, Craft Ventures and Y Combinator.

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Cursor’s $10B Rocketship: How an AI Coding Tool Scaled at Warp Speed

Every now and then, a startup bursts onto the scene with such explosive growth that it feels like the whole tech world just got whiplash. Right now, that startup is Cursor – an AI-powered code editor that’s shot from obscurity to a $10B valuation in just a couple of years. It’s not just hype: Cursor’s revenue growth has been off the charts. We’re talking essentially zero to $100M+ ARR in about a year, with developers flocking to this “AI IDE” in droves. How did a tiny MIT-founded team pull this off, and what makes their execution so special? Let’s dive into Cursor’s rapid rise – the sharp revenue trajectory, the tactics fueling its scale, and why its playbook has VCs and founders buzzing with excitement.

Blistering Growth & a Stratospheric Valuation

Cursor’s growth metrics read like startup fantasy. By spring 2024, the company was doing around $4M in ARR, which then exploded 12× to about $48M ARR by October 2024. And it didn’t stop there. Sources say Cursor barreled past $100M in ARR within its first 12 months on the market – reportedly making it the fastest SaaS product ever to hit that milestone (yes, even faster than ChatGPT’s meteoric climb). As of early 2025, Cursor’s ARR has already climbed to ~$200M, achieved with only a handful of team members.

Such blazing growth translated into equally impressive valuations. In mid-2024, Cursor raised a $60M Series A at a ~$400M valuation, then just four months later landed $100M at a $2.6B post-money. Now, barely another quarter later, the company is reportedly closing a new round at nearly $10B – a valuation jump that implies ~66× its current ARR. Investors are effectively pricing Cursor like a once-in-a-generation rocketship, and so far the numbers back it up. When VC firms are falling over themselves to get a piece (more on that frenzy later), you know you’ve hit a nerve.

Product-Led Growth Fueling a Developer Frenzy

So what’s behind Cursor’s breakneck scale? In a nutshell: a few savvy tactics and a product that basically sells itself:

Bottom-up adoption fueled by a frictionless freemium model: Cursor’s go-to-market strategy is a masterclass in PLG, driven by bottom-up adoption and a frictionless freemium model. Instead of a top-down sales approach, Cursor went straight to developers, offering a tool engineers genuinely love, which turned the product itself into the marketing engine. Word spread quickly, and by August 2024, Cursor had over 40,000 customers, including “cool kid customers” like OpenAI, Midjourney, Shopify, and Instacart. By early 2025, that number had skyrocketed to over 360,000 paying users, thanks to the ease of adoption: developers can start with a free trial and quickly see the value, with affordable plans priced at $20/month for pro and $40 for business. This low-friction, self-serve model means trial users seamlessly convert to paying customers, fueling rapid, sustainable growth.

A superior AI-native product experience: Cursor isn’t just an IDE with an AI bolted on; it’s an AI-first code editor built to make coding feel almost like chatting. This “vibe coding” approach – where writing code becomes a mellow back-and-forth with the AI – truly set Cursor apart. The product integrates seamlessly with developers’ existing workflow, so devs get a familiar environment supercharged with AI. It offers live autocomplete that can handle multiple files and big codebases, answer questions about your code, and refactor in seconds. In short, it delivers real “10x” developer productivity gains – enough to make even GitHub’s Copilot look over its shoulder.

Community-driven product iteration: Cursor didn’t just build in isolation – they built with their users. From day one, the team leaned into community feedback, rapidly iterating based on real-world developer needs. They actively engaged with users on platforms like Discord, GitHub, and even Twitter, fostering a loyal base that felt invested in the product’s success. This transparent, feedback-driven approach didn’t just help build a better product; it turned early adopters into vocal advocates, amplifying Cursor’s reach and reputation organically.

Riding the “Vibe” to a Category-Defining Company

Perhaps the most remarkable part of Cursor’s story is how it changed the developer experience zeitgeist. The product has made coding feel cool again – even fun. Users started talking about “vibe coding” with Cursor, describing how banging out code became more like chatting with a fellow engineer who never sleeps and knows basically everything. By eliminating a lot of the tedium, Cursor lets developers stay in a creative flow. That feel-good factor has been a huge asset; it’s not just a productivity tool, it’s a bit of a status symbol and community meme in engineering circles.

All this culminated in Cursor moving from a new kid on the block to the white-hot center of the tech zeitgeist. That’s a bold claim, but the buzz checks out – especially when you see a $9B valuation for a ~3-year-old startup and the fact that major dev tool incumbents are scrambling to catch up. Cursor’s execution so far has been nearly flawless: nailing product-market fit out of the gate, harnessing prodigious growth with a PLG strategy, and keeping the feature flywheel spinning fast enough to maintain a lead. It has turned the humble code editor into the latest arena of the AI revolution – and seized the crown in the process.

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango and Workmate.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• Arlo Health, an AI-powered health insurance underwriter for small businesses, has raised $4M. The round was led by Upfront Ventures, with participation from 8VC and General Catalyst.

• Charm Security, an AI-powered customer security platform that protects organizations and their customers from scams, social engineering, and human-centric fraud, has raised $8M. The round was led by Team8.

• Paid, a business engine that helps AI agent companies accelerate growth and profitability, has raised $10.73M. The round was funded by EQT Ventures and Sequoia Capital.

• ScribeHealth.AI, an AI-powered medical scribe platform designed to automate SOAP notes and medical coding, has raised $1.2M. The round was led by Better Financial, with participation from Soma Capital, Global Founders Capital and Y Combinator.

• Sohar Health, an AI-driven eligibility determination and verification of benefits provider, has raised $3.8M. The round was led by Kindred Capital, with participation from General Catalyst, Character, Y Combinator, Rebel Fund and Concept Ventures.

• Taxo, a data extraction and reasoning engine dedicated to healthcare administration, has raised $5M. The round was led by Character, with participation from General Catalyst and Y Combinator.

• Voiceops, an AI platform intended to help call centers achieve sales efficiency, has raised $5M. The round was led by Bonfire Ventures and Twelve Below, with participation from Precursor Ventures, Not Boring, Village Global, Kearny Jackson, Mana Ventures and Four Acres Capital.

• Yutori, a startup building personal AI assistants that automate everyday digital tasks, has raised $15M. The round was led by Radical Ventures, with participation from Felicis.

• Ethos, an automated expert network that matches users with relevant experts using AI, has raised $3.25M. The round was led by General Catalyst, with participation from McKinsey & Company, Jane Street, Bain & Company, Conviction Partners, 8VC, Common Magic, Interface Capital, Sequoia Capital, Andreessen Horowitz, Atomico, Elliott Investment Management, The Goldman Sachs Group and SoftBank Group.

Early Stage:

• Nexthop.ai, an AI infrastructure company providing networking solutions for cloud companies, has raised $110M. The round was led by Lightspeed Venture Partners, with participation from Battery Ventures, Emergent Ventures, WestBridge Capital and Kleiner Perkins.

Series A:

• Arcade, a generative AI marketplace for designing physical products, has raised $25M at a $202M valuation. The round was led by Canaan Partners, with participation from Inspired Capital, Torch Capital, Factorial Funds, Forerunner Ventures, Offline Ventures, Adverb Ventures and Sound Ventures.

• Automaise, a no-code AI platform built to create, deploy, and manage AI agents for customer experience automation, has raised $5.36M. The round was led by Oxy Capital, with participation from Bright Pixel Capital, HCapital and Armilar Venture Partners.

• Brisk Teaching, an AI teaching and learning agent for K-12 schools, has raised $15M. The round was led by Bessemer Venture Partners, with participation from South Park Commons, Owl Ventures and Springbank Collective.

• DeepIP, an AI assistant for drafting patents, has raised $15M. The round was led by Resonance VC, with participation from Headline, Serena and Balderton Capital.

• Distributed Spectrum, a defense tech company developing AI-powered sensors to help the U.S. military locate enemy troops and drones by their radio emissions, has raised $25M. The round was led by Shield Capital, Conviction Partners and Nat Friedman, with participation from Xfund and Felicis.

• Layer Health, a healthcare AI company leveraging LLMs to enhance chart reviews, has raised $21M at a $100M valuation. The round was led by Define Ventures, with participation from GV, MultiCare Health System, East Post Road Ventures, MultiCare Capital Partners and Flare Capital Partners.

• Silna Health, a healthcare revenue cycle management platform that uses AI to manage prior authorization, benefit checks and eligibility verification, has raised $27M. The round was led by Accel and Bain Capital Ventures.

• Straiker, a startup offering real-time protection for AI applications and agents with an AI-native security solution, has raised $21M. The round was funded by Lightspeed Venture Partners, Bain Capital Ventures and Rain Capital.

Series B:

• n8n, an AI-powered workflow automation platform, has raised $60M at $270M valuation. The round was led by Highland Europe, with participation from Sequoia Capital, Felicis, Harpoon VC and HV Capital.

• Tomorro, a legal contract management platform that leverages AI to streamline contract processes for businesses, has raised $26.9M. The round was led by XAnge, Acton Capital and Adelie, with participation from HenQ, Resonance VC, Founders Future, Motier Ventures and Financière Saint James.

Series C:

• Navina, an AI copilot that provides clinical intelligence to clinicians and care teams, has raised $55M. The round was led by Goldman Sachs Asset Management, with participation from Grove Ventures, Vertex Ventures Israel and ALIVE Israel Healthtech Fund.

Later Stage:

• Mercury, a fintech company that provides a banking stack for startups, has raised $300M at a $3.5B valuation. The round was led by Sequoia Capital, with participation from Marathon, Coatue Management, Andreessen Horowitz, CRV and Spark Capital.

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Themes from the Fastest Growing AI Startups

AI-native startups are rewriting the traditional playbook for software growth, scaling faster and leaner than anything we've seen in SaaS history. Whether targeting developers, creators, infrastructure, or enterprise workflows, the most successful companies share a few defining traits: they’re deeply integrated into user workflows, move at blistering speeds, and rely on product-led growth to drive viral adoption. This wave isn’t just about adding AI features, it’s about reimagining software from the ground up for an AI-first world.

PLG Developer-Focused Apps

We’re seeing developer-first AI startups scale at breakneck speed by deeply integrating into existing workflows and letting product value drive adoption in the product development process. Cursor, Codeium, Bolt and Lovable are all hitting tens of millions in ARR with teams under 50 by solving acute pain points (e.g. writing, editing, or generating code/apps) and offering great UX with minimal friction and expanding the audience of application development. Cursor went from zero to $100M ARR in just 12 months with under 20 people and no marketing, likely the fastest SaaS growth curve on record. Unlike incumbents who bolted on AI features, Cursor was purpose-built for an AI-first coding experience, helping developers describe what they want in plain English and generating production-ready code with minimal effort. This AI-native orientation allowed it to move quickly and offer a cleaner UX than legacy IDEs, creating viral pull across the dev ecosystem.

The common theme is developers discovering, loving, and sharing these tools organically. Community (GitHub stars, Twitter demos, Discords), rapid iteration, and dead-simple onboarding drove viral growth without traditional sales. Codeium crossed $40M ARR with 700K+ devs. Bolt hit $20M ARR in just 8 weeks by letting users build full-stack apps with a single prompt, expanding reach to non-technical creators. Even Cognition Labs’ Devin, positioned as the first AI software engineer, leveraged buzz, benchmarks, and exclusivity to drive thousands of inbound pilots pre-GA. These startups aren’t just replacing tools, they’re redefining workflows. Cursor in particular benefited from counter-positioning against slower-moving IDEs and rapid execution speed, a temporary but powerful edge. We’re especially excited by the velocity at which usage turns into revenue, often without CAC, and the potential to expand from individual devs to org-wide adoption with near-zero friction.

PLG Prosumer Creative Tools

Creative AI apps like Midjourney, Captions, Photoroom, and ElevenLabs have unlocked a viral loop: users create content with them, then share it across social platforms, turning every output into distribution. Midjourney scaled to $300M in revenue in 2024 (up from $50M in 2022), entirely bootstrapped and without a sales team, by building a thriving Discord-native community and delivering stunning outputs that fueled organic growth. ElevenLabs surged from $25M to $90M ARR in under a year, driven by its Creative Studio, which lets creators generate multilingual, lifelike voiceovers that power content creation across platforms. Photoroom, now at $50M ARR with 200M+ users and 4M monthly downloads, has become essential for millions of SMBs and creators producing high-quality product visuals and social media content.

We see these companies as proof that prosumer AI can scale like SaaS, with stronger virality and lower CAC. Their growth is powered by community, shareability, and fast product iteration. They convert casual creators into power users with clear value, simple pricing, and constant delight. Their models scale well: Midjourney and Photoroom are profitable, Runway is layering in B2B and API channels, and Pika is turning its Discord-native community into a consumer video platform. The creative AI stack is one of the clearest opportunities for mass-market PLG in the AI era, and these companies are defining the playbook.

AI Model Development and Deployment Infra

Together.ai, Modal, Fal.ai, Fireworks, and Mercor are scaling rapidly by building core infrastructure for training, deploying, and operating AI models. Together.ai reached $100M+ in annualized revenue within two years by offering lower-cost, open-weight model training and inference—making it the go-to partner for startups looking for more control and lower infra costs. Modal is building a serverless GPU platform with over 10,000 developers, focusing on developer experience and lightning-fast deploys—positioning itself as a Vercel for AI workloads. Fal.ai went from $1M to $40M run rate in one year by specializing in multimedia inference, serving customers like Quora and Adobe. Fireworks.ai brands itself as the fastest inference engine and has grown to double-digit millions in run rate revenue, with customers including DoorDash, Notion, and Uber. These companies have grown fast by staying programmable, cost-efficient, and tuned for modern AI-native workloads.

Mercor, while adjacent, plays a critical role in powering human-in-the-loop model training. It built a global labor marketplace for prompt evaluators, data labelers, and QA workers—now serving OpenAI, Anthropic, and more. The company surpassed $100M in ARR by automating sourcing, vetting, and task routing, becoming the ops layer for high-quality data pipelines. What unifies this group is their focus on removing the core bottlenecks in the modern LLM stack—whether compute, inference latency, customization, or training data ops. This isn’t about competing with AWS, it’s about owning the high-leverage primitives the next generation of AI builders depend on.

First-Mover AI Applications

First-mover applications like Harvey, Sierra, and Decagon have rapidly gained traction by targeting high-value enterprise workflows with innovative AI solutions in areas where copilots or agents have clear initial ROI and value. Harvey has established itself as a leader in legal AI, securing firm-wide deployments at Allen & Overy and PwC, achieving over $50M in Annual Recurring Revenue (ARR) across more than 200 law firms, and raising $300M at a $3B valuation (with some of that contracted but not live yet). Sierra, led by Bret Taylor, focuses on automating customer support using LLMs and has initiated numerous Fortune 500 pilots by offering seamless integrations and a compelling "replace Zendesk" value proposition. Decagon specializes in AI-powered customer support agents and has experienced significant growth, raising a total of $100M in funding, including a $65M Series B led by Bain Capital Ventures, to enhance enterprise customer support through automation and efficiency. ​

A common thread among these companies is their swift establishment of enterprise trust. They recognize that in regulated and reputation-sensitive industries, delivering not only advanced AI models but also ensuring security, transparency, and enterprise-grade workflows is crucial. Their go-to-market strategies emphasize credibility and relationship-building: Harvey leverages backing from OpenAI and references from prestigious law firms; Sierra utilizes founder-led go-to-market approaches and rapid integrations; and Decagon invests in domain expertise and compliance-ready solutions in an area where agents are showing clear ROI. By earning trust and securing early enterprise adoption, these companies are poised to become the next-generation systems of record in sectors where switching costs are high, and incumbents are slow to adapt.

Conclusion

Each of these segments—developer tools, creative prosumer apps, infra platforms, and first-mover enterprise agents—offers a glimpse into the playbook of tomorrow’s iconic companies. They move fast because the market rewards speed. They scale efficiently because the product sells itself. And they win not just by solving problems, but by reshaping the way work gets done. As AI-native startups continue to mature, the most enduring ones will be those that combine world-class product execution with structural advantages like low CAC, viral adoption, and clear paths to enterprise expansion. This is just the beginning.

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango and Workmate.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• Arcade, an AI agent infrastructure startup, has raised $12M. The round was led by Laude Ventures, with participation from Flybridge Capital Partners, Hanabi Capital Management and Neotribe Ventures.

• Augment, a startup building an AI assistant for the logistics industry, has raised $25M. The round was led by 8VC, with participation from Applico Capital.

• Rerun, a company building a multimodal data stack for Physical AI, has raised $17M. The round was led by Point Nine Capital, with participation from Costanoa Ventures, Seedcamp and Sunflower Capital.

• Town.com, a tax advisory platform designed to empower small businesses with AI-enhanced expert guidance, has raised $18M. The round was led by First Round Capital, with participation from Conviction Partners, Alt Capital, Depth Capital Ventures, Mischief, WndrCo and Position Ventures.

• Vallor, an AI-powered contract management platform intended to automate tasks and optimize contracts, has raised $4.2M at a $16.2M valuation. The round was funded by Bloomberg Beta, Right Side Capital Management and Forum Ventures.

Series A:

• Gradial, a startup developing AI marketing operations agents, has raised $13M at an $85M valuation. The round was led by Madrona Venture Group, with participation from DLA Piper, General Advance, Outsiders Fund and Pruven Capital.

• Multiply Mortgage, a financial technology company making homeownership accessible through employer benefits, has raised $23.5M. The round was led by Kleiner Perkins, with participation from Mischief, A*, BoxGroup and Workshop Fund.

• Numeral, a startup that handles sales tax compliance for both ecommerce and SaaS companies, has raised $18.13M at a $97M valuation. The round was led by Benchmark Capital Holdings, with participation from FundersClub, Uncork Capital and Y Combinator.

• Prezent, an enterprise business storytelling platform for business communication, has raised $20M. The round was led by Greycroft, with participation from Zoom Ventures, Manulife, Alumni Ventures, BluePointe Ventures, Emergent Ventures, WestWave Capital and True Global Ventures.

• Utila, an institutional digital assets operations platform that helps organizations securely manage and build on digital assets, has raised $18M. The round was led by Nyca Partners, with participation from Wing VC, NFX, Haymaker Ventures, Gaingels and Cerca Partners.

Series B:

• Graphite, an AI-powered code review platform, has raised $52M at a $292M valuation. The round was led by Accel, with participation from Shopify Ventures, Anthropic, Figma Ventures, Andreessen Horowitz, The General Partnership and Menlo Ventures.

• Cognition, an AI-powered coding assistant, has raised $120M at a $4B valuation. The round was led by 8VC, with participation from Founders Fund, Khosla Ventures and Conviction Partners.

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I came across the below post in one of my favorite newsletters: Growth Unhinged by my friend Kyle Poyar that explores the hidden playbooks behind the fastest-growing startups. Below (and originally here) is one of the best blog posts I’ve read this year and Kyle and Yaakov have kidly given permission to share it with the Notorious community.

There is so much love for new AI products for note taking (Granola), photo editing (PhotoRoom, Aftershoot) and even app building (Replit, Bolt). What’s been fascinating is seeing new 🔥 UX patterns emerge. These products are reaching millions of users and tens of millions in ARR in a matter of weeks. Repeat contributor Yaakov Carno — founder of Valubyl and author of the Product Led Growers newsletter — unpacks the subtle UX choices that are leading to breakout growth.

AI products are shattering growth records, with some hitting $100M ARR faster than any software in history.

Just look at Bolt—within two months, the product reportedly skyrocketed to $20M ARR with over 2 million users. Its secret? Not just powerful AI, but a ridiculously smooth, intuitive UX that makes complex development workflows feel effortless.

Bolt isn’t an isolated instance; I’ve noticed similar hockey-stick growth at companies like Cursor, Replit, Lovable and PhotoRoom.

Meanwhile, many AI products end up as a flash in the pan. They attract AI ‘tourists’—users who sign up, get confused, and churn almost instantly. Why? Because they can’t figure out how to use it, don’t trust its decisions, or feel like they’re wrestling with AI rather than collaborating with it.

The difference between AI-native products that explode in growth and those that fade away often comes down to one thing: user experience.

Unlike traditional software, AI-driven products are dynamic and unpredictable. They generate unique outputs, adapt to user input, and, when poorly designed, can feel frustrating, mysterious, or outright unreliable.

The best AI-native products don’t just deliver powerful automation. They guide users through a seamless, intuitive, and trustworthy experience—one where AI feels like an assistant rather than a guessing game.

I’ll break down five key UX challenges in AI-native products and how the best companies are solving them.

Challenge 1: AI feels like a black box

🧠 "AI feels like magic, but that makes it hard to trust."

Users hesitate to rely on AI when they don’t understand how it works. If an AI system produces results without explanation, people second-guess the accuracy. This is especially problematic in industries where transparency matters—think finance, healthcare, or developer automation.

How companies are solving this

• Bolt breaks down the AI process step-by-step in real time, so users see exactly how their code is being generated or automated.

• Cursor doesn’t just “fix” your code—it explains why it made each suggestion, reinforcing trust.

• PhotoRoom adds explanations behind AI edits, helping users understand the “why” behind its decisions.

Pro-tips

✅ Show step-by-step visibility into AI processes.

✅ Let users ask, “Why did AI do that?”

✅ Use visual explanations to build trust.

Challenge 2: AI is only as good as the input — but most users don’t know what to say

📝 "Users don’t need better AI—they need better ways to talk to it."

AI is only as effective as the prompts it receives. The problem? Most users aren’t prompt engineers—they struggle to phrase requests in a way that gets useful results. Bad input = bad output = frustration.

How companies are solving this

• Bolt & Replit make it easy for users to refine prompts with one-click enhancements, helping users improve their input before execution and get better results.

• PhotoRoom introduces three AI editing paths:

  • Assisted mode: Guides users step-by-step through structured editing.

  • Image mode: Suggests similar images to spark inspiration.

  • Manual mode: Gives advanced users full control over edits.

Pro-tips

✅ Offer pre-built templates to guide users.

✅ Provide multiple interaction modes (guided, manual, hybrid).

✅ Let AI suggest better inputs before executing an action.

Challenge 3: AI can feel passive and one-dimensional

💡 "A great AI assistant should work with you, not just for you."

Many AI tools feel transactional—you give an input, it spits out an answer. No sense of collaboration or iteration. The best AI experiences feel interactive.

How companies are solving this

• Replit uses a dual-mode AI assistant: agent mode (automates full builds) and assistant mode (helps with smaller refinements).

• Cursor combines AI chat with execution, allowing users to switch between exploratory conversation and direct AI-powered coding assistance.

• Fathom’s Ask Fathom feature turns AI meeting summaries into an interactive experience, letting users engage with transcript results instead of just receiving static output.

Pro-tips

✅ Design AI tools to be interactive, not just output-driven.

✅ Provide different modes for different types of collaboration.

✅ Let users refine and iterate on AI results easily.

Challenge 4: Users need to see what will happen before they can commit

🤔 "People don’t trust what they can’t test."

Users hesitate to use AI features if they can’t predict the outcome. The fear of irreversible actions makes them cautious, slowing adoption.

How companies are solving this

• Bolt uses predefined AI prompts that allow users to test it before committing — even before signing up.

• Replit adds confirmation & rollback checkpoints so users can preview AI-generated code before executing it, reducing risk and fear.

• Fathom provides interactive onboarding, where users can test AI insights in a sandbox environment (a two minute test call) before having the recording bot join them in real meetings.

Pro-tips

✅ Allow users to test AI features before full commitment.

✅ Provide preview or undo options before executing AI changes.

✅ Offer exploratory onboarding experiences to build trust.

Thanks for reading Kyle Poyar’s Growth Unhinged. Please support my work: subscribe, like & share this post!

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Challenge 5: AI can feel disruptive

⚙️ "AI should weave into the workflow, not interrupt it."

Poorly implemented AI feels like an extra step rather than an enhancement. AI should reduce friction, not create it.

How companies are solving this

• Cursor lets users accept/reject AI suggestions instantly for a seamless workflow.

• Granola seamlessly blends your rough notes with a comprehensive, contextual summary, allowing you to capture loose thoughts effortlessly - without ever losing focus on the call.

• Grammarly adapts to each scenario, offering context-aware edits and replies - eliminating the need for repetitive “Write me a reply that…” prompts.

• Bolt allows users to seamlessly switch between AI-generated code and a live preview.

Pro-tips

✅ Provide simple accept/reject mechanisms for AI suggestions.

✅ Design seamless transitions between AI interactions.

✅ Prioritize the user’s context to avoid workflow disruptions.

Designing AI that works for people

AI isn’t the differentiator anymore—great UX is. If you want your AI product to succeed, make sure it’s clear, trustworthy, and seamless—or watch users disappear.

The patterns we’ve explored—transparency, guided input, interactivity, predictability, and seamless integration—are key to creating AI experiences that drive real adoption and retention.

*******************************************************************************************

The Notorious community can use this link to get 15% off their order of HBS Professor and Flybridge VC Founer Jeff Bussgang’s new book on building AI startups (discount applied at checkout): Get The Experimentation Machine

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Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango, Tome and Workmate.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

15 Biggest Stock Gainers (1 month):

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• Aomni, an AI agent platform that helps sales teams conduct deep research on potential customers, has raised $4M. The round was led by Decibel Partners, with participation from Sancus Ventures and Ride Home Fund.

• CO/AI, a community platform designed to help discover and share how to use AI, has raised $1.8M. The round was led by The Critical Co, Movi Partners and Sequoia Capital, with participation from Gaingels.

• CTGT, an enterprise AI risk management and performance platform that actively monitors and audits client’s custom models, has raised $7.2M. The round was led by Gradient Ventures, with participation from General Catalyst, Liquid 2 Ventures, Y Combinator and Deepwater Asset Management.

• Henry AI, an AI-driven deal assistant designed for commercial real estate professionals, has raised $4.3M. The round was led by 1Sharpe Ventures and Susa Ventures, with participation from Pioneer Fund, RXR ARDEN Digital Ventures, Singularity Capital, Unwritten Capital, Coalition Operators, Orange Collective and StoryHouse Ventures.

• Lingo.dev, an AI-powered localization engine that provides the infrastructure to help developers go global, has raised $4.2M. The round was led by Initialized Capital Management, with participation from Y Combinator.

• OpenInfer, a startup building inference solutions that enable developers to run AI models efficiently on any hardware, has raised $8M. The round was funded by Brave Capital, Cota Capital, Essence Venture Capital, Operator Stack and StemAI.

• Pulse, a startup specializing in unstructured data preparation for machine learning models, has raised $3.9M. The round was led by Nat Friedman, with participation from Olive Tree Capital, Sequoia Capital, Liquid 2 Ventures, Soma Capital and Y Combinator.

• Safe Intelligence, a startup that offers deep validation of machine learning models, has raised $5.17M. The round was led by Amadeus Capital Partners, with participation from VSquared Ventures and OTB Ventures.

• Sawmills, a telemetry data management platform that allows companies to automate the management of data that flows from software applications and services to their observability tools, has raised $10M. The round was led by Team8, with participation from Mayfield Fund and Alumni Ventures.

• Singulr AI, an enterprise AI governance and security platform that helps streamline and secure enterprise AI use at scale, has raised $10M at a $35M valuation. The round was led by Dell Technologies Capital.

• Thread, an AI service desk designed for managed service providers, has raised $7.25M. The round was led by Integr8d Capital.

• Valid., an AI-enabled ad agency designed to unlock consumer and product insights, has raised $5.5M. The round was led by Canaan Partners, with participation from J Ventures and Neo.

• WilsonAI, an AI-powered assistant for in-house legal operations, has raised $1.7M. The round was led by Nomad Ventures, with participation from Entrepreneur First, Autopilot Ventures and Transpose Platform Management.

Series A:

• ClustroAI, an edge AI technology that enables local device AI processing without relying on cloud computing, has raised $12M. The round was led by Forum Ventures, with participation from Nvidia, Metaverse Group and metablast.

• Guidde, an AI-powered video documentation company focused on creating software training videos, has raised $26.6M. The round was led by Qualcomm Ventures and Norwest Venture Partners, with participation from Entrée Capital, Honey Stone VC, Tiferes Ventures and Inkberry Ventures.

• OpenEvidence, a generative AI chatbot exclusively for doctors, has raised $75M at a $1B valuation. The round was led by Sequoia Capital.

• Patlytics, an AI-enabled patent analytics platform designed to help corporations, IP professionals and law firms streamline their patent workflows, has raised $14M. The round was led by Next47, with participation from Gradient Ventures, 8VC, Alumni Ventures, Liquid 2 Ventures and Myriad Venture Partners.

• SmartSuite, a next-generation work management platform that enables teams to manage any business process or project, has raised $38M. The round was led by Canapi Ventures, with participation from Sorenson Capital and High Alpha.

Series B:

• Mercor, an AI-powered hiring platform designed to streamline the hiring process for both candidates and companies, has raised $100M at a $2B valuation. The round was led by Felicis, with participation from General Catalyst, Benchmark Capital Holdings, Menlo Ventures, Emergence and DST Global.

• Sanas, a real-time accent translation startup that helps non-native speakers speak more clearly, has raised $65M at a $500M valuation. The round was led by Quadrille Capital and Teleperformance, with participation from Insight Partners, Quiet Capital and DN Capital.

• Together AI, a public cloud optimized to run AI models for developers, has raised $305M at a $3.3B valuation. The round was led by Prosperity7 Ventures and General Catalyst, with participation from Nvidia, Salesforce, DAMAC Group, SE Ventures, Coatue Management, March Capital, Emergence, Greycroft, Cadenza Capital, Lux Capital, Long Journey Ventures, Definition, Kleiner Perkins, Brave Capital, SK Telecom and SaaS Ventures.

Series C:

• Arize, a unified AI observability and LLM evaluation platform that helps teams develop and maintain more successful AI, has raised $70M. The round was led by Adams Street Partners, with participation from M12, Datadog, PagerDuty, Battery Ventures, Archerman Capital, TCV, Foundation Capital, Swift Ventures, Industry Ventures, SineWave Ventures and OMERS Ventures.

• Baseten, an AI startup that’s focused on high-performance inference for large language models and other AI applications, has raised $75M. The round was led by IVP and Spark Capital, with participation from South Park Commons, Greylock, Conviction Partners and 01 Advisors.

• Hightouch, a data and AI platform for marketing and personalization, has raised $80M at a $1.2B valuation. The round was led by Sapphire Ventures, with participation from Bain Capital Ventures, ICONIQ Growth, New Ventures Capital, Amplify Ventures, NewView Capital and Y Combinator.

• Luminance, an AI assistant for attorneys that automates contract preparation and negotiation, has raised $75M at a $385M valuation. The round was led by Point72 Ventures, with participation from National Grid Partners, Forestay Capital, RPS Ventures, Slaughter and May, March Capital and Schroders Capital.

Series D:

• Abridge, a generative AI platform for clinical conversations, has raised $250M at a $2.75B valuation. The round was led by IVP and Elad Gil, with participation from CVS Health Ventures, NVentures, California Healthcare Foundation, CapitalG, Atria Ventures, SV Angel, K. Ventures, Redpoint Ventures, Lightspeed Venture Partners, Bessemer Venture Partners and Spark Capital.

• Lambda, a cloud computing platform designed for large-scale AI training and inference, has raised $480M at a $2.5B valuation. The round was led by Andra Capital and SGW, with participation from Nvidia, Pegatron, Super Micro Computer, Wistron, Wiwynn, Crescent Cove Advisors, Fortified Ventures, Helios Ventures, AJI Capital, Pureun Investment, US Innovative Technology Fund, G Squared, Bossa Invest, Principal Venture Partners, Launchbay Capital, Fincadia Advisors, In-Q-Tel, 1517 Fund, ARK Investment Management and KHK & Partners.

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2025: Year of the Agentic Workforce

The way we work is about to change forever. 2025 marks the beginning of the AI agent era—a shift where digital colleagues take on tasks, make decisions, and collaborate with humans to drive business productivity at an unprecedented scale.

For decades, businesses have relied on Software-as-a-Service (SaaS) tools to operate. Employees navigated countless apps, manually entering data, updating records, and coordinating workflows. That model is now collapsing. The next generation of work won’t be about using software; it will be about managing intelligent agents that do the work for us.

From SaaS to AI Agents: A Tectonic Shift

Microsoft CEO Satya Nadella put it best: “SaaS is CRUD databases with business logic. As AI takes over that logic, SaaS will collapse.” In 2025, we’ll see the first real wave of this transformation. AI agents won’t just be assistants; they’ll be autonomous digital colleagues capable of executing complex workflows, learning from data, and optimizing operations across industries.

Businesses won’t be paying for software licenses; they’ll be hiring AI agents to get work done. Need customer support? Deploy an AI agent to handle inbound requests 24/7. Need financial analysis? Assign an agent to analyze transactions and flag anomalies. The future of software isn’t a static dashboard—it’s a network of intelligent agents operating seamlessly across systems.

The Startup Gold Rush: Building the Agent Economy

The shift from SaaS to AI agents presents one of the biggest startup opportunities of the decade. Just as the SaaS boom created billion-dollar companies, the rise of AI agents will fuel a new wave of disruptors.

• Agent Development Platforms: Startups building low-code/no-code tools for creating AI agents will be in high demand. Businesses will want customizable agents that can integrate into their unique workflows without requiring AI expertise.

• Vertical-Specific Agents: Industry-focused AI agents that solve niche problems—like AI-driven legal research, automated medical billing, or AI compliance officers—will carve out highly lucrative markets.

• Agent Marketplaces & Infrastructure: Just like the rise of the app store, there will be marketplaces for AI agents where businesses can buy, deploy, and manage different agents from a single hub. Security, compliance, and governance solutions tailored for AI agents will also become essential.

• Outcome-Based AI Services: Instead of traditional SaaS subscriptions, new pricing models will emerge where businesses pay per task completed or per successful outcome, aligning cost with value.

Considerations for Founders Building AI Agents

For founders looking to capitalize on this trend, here are some key considerations:

• Data Access & Integration: Agents need reliable access to enterprise data to be effective. Partnerships with existing SaaS vendors or integrations with legacy systems will be crucial.

• Trust & Explainability: Businesses will only adopt agents they fully trust. Founders should prioritize building transparent, explainable AI models with clear decision-making logic.

• Autonomy vs. Control: Balancing agent independence with human oversight is critical. Many companies will want human-in-the-loop workflows before they fully hand off processes to AI.

• Security & Compliance: Handling sensitive business data comes with strict compliance requirements. AI agents must meet GDPR, SOC2, and other regulatory standards to be enterprise-ready.

• Differentiation: With major players like OpenAI, Anthropic, Meta and Google investing heavily in AI, startups need to find unique angles—whether through proprietary datasets, domain expertise, or deeper workflow integrations.

The Agentic Workforce Is Already Here

We’re already seeing glimpses of the agent-driven future. Startups like Sierra and Decagon are building autonomous agents for complex workflows. Salesforce (rebranding as Agentforce) and HubSpot are integrating AI deeply into their platforms to keep up with the agent revolution. Workday is creating an “Agent System of Record” to manage AI workers just like human employees.

This is just the beginning. The companies that embrace AI agents now will dominate the next decade of business. 2025 is the tipping point—the year where AI agents move from experimental to essential.

Are You Ready?

The future of work isn’t about more software. It’s about more intelligence, more automation, and more outcomes with less manual effort. The companies that figure out how to harness AI agents effectively will win big. The rest? They’ll be stuck in the SaaS past.

Welcome to the age of the Agentic Workforce. 2025 is just the beginning.

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango, Tome and Workmate.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

15 Biggest Stock Gainers (1 month):

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• Aracor AI, an automated contract review tool designed for attorneys to analyze documents to deliver professional insights, has raised $4.5M. The round was led by Fuel Venture Capital.

• Bluebook, a startup building AI agents for accounting firms, has raised $3M. The round was led by EQT Ventures, with participation from Y Combinator.

• Genia, an AI-powered generative design software intended to produce optimized structural engineering drawings, has raised $3M. The round was led by Pi Labs, with participation from Amplify, Boost VC, Dorm Room Fund, Suffolk Technologies and The Y Startup Index Fund.

• Hatz AI, a white-labeled AI platform designed to build applications and agents, vector storage, and custom large language models, has raised $2.5M at a $34.5M valuation. The round was led by Vestigo Ventures.

• Indigo, an AI-powered home buying and selling platform for real estate agents, has raised $8M. The round was led by NFX, Era Ventures and GTM Fund, with participation from 1Sharpe Ventures.

• Iris, an AI platform designed to streamline the RFP process, has raised $4.07M. The round was funded by Florida Funders and Naples Technology Ventures.

• Minerva, an AI platform designed to model consumer behavior and provide companies with insights into their customers, has raised $8.1M at a $30M valuation. The round was led by The General Partnership, with participation from Soma Capital, KBW Ventures and Sequoia Capital.

• Pinkfish AI, a startup helping enterprise customers build AI agents and other AI-driven workflows through natural language prompts, has raised $7.6M. The round was led by Norwest Venture Partners, with participation from Storm Ventures.

Series A:

• ConverzAI, an AI-powered virtual recruiting platform designed to autonomously hire candidates, has raised $16M at an $81M valuation. The round was led by Menlo Ventures, with participation from Afore Capital, Recall Capital, Left Lane Capital and Foundation Capital.

• Eudia, an augmented intelligence platform designed for corporate legal teams, has raised $105M. The round was led by General Catalyst, with participation from Sierra Ventures, Everywhere Ventures, Floodgate, Hakluyt Capital, Defy Partners Management, B3 Capital and Backbone Capital.

• Latent Labs, a startup developing foundation AI models to support the development of new medicines, has raised $50M. The round was led by Radical Ventures and Sofinnova Partners, with participation from 8VC, Kindred Capital, Pillar VC, SBXi, Flying Fish Partners and AWS Startups.

• Plain, a B2B support platform for modern companies, has raised $15M. The round was led by Battery Ventures, with participation from Index Ventures and Connect Ventures.

• Tofu, an omnichannel marketing platform that helps B2B marketing teams scale their campaigns, has raised $12M at a $66M valuation. The round was led by SignalFire, with participation from HubSpot Ventures, Tau Ventures, Correlation Ventures, Alumni Ventures, SH Fund, Riverside Ventures, Eudemian Ventures and Han Bridge Capital.

• Unwrap, a customer intelligence platform that uses AI natural language processing to analyze large amounts of customer data, has raised $12M. The round was led by Scale Venture Partners, with participation from Atlassian Ventures, Cercano, ScOp VC and the Allen Institute for Artificial Intelligence.

Series B:

• Comulate, a startup developing automated billing and revenue operations technology for insurance companies, has raised $20M at a $240M valuation. The round was led by Workday and BOND Capital, with participation from Spark Capital and Neo.

• fal, a generative media platform designed for developers, offering AI model inference and training capabilities, has raised $49M. The round was led by Notable Capital, with participation from Andreessen Horowitz, Kindred Ventures, First Round Capital and Bessemer Venture Partners.

• Moderne, an automated code refactoring and analysis company, has raised $30M. The round was led by Acrew Capital, with participation from Intel Capital, Allstate, AMEX Ventures, TIAA Ventures, True Ventures, Mango Capital and Morgan Stanley.

• SpotDraft, an AI-driven contract management platform designed to draft and execute legal contracts, has raised $54M. The round was led by Trident Growth and Vertex Growth, with participation from Premji Invest, Arkam Ventures, Xeed Ventures and Prosus.

Series D:

• Harvey, an AI startup focused on the legal industry, has raised $300M at a $3B valuation. The round was led by Sequoia Capital, with participation from OpenAI Startup Fund, GV, REV Venture Partners, Coatue Management, Conviction Partners and Kleiner Perkins.

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Notorious Startup of the Week: Apollo

This week, we have one of the most amazing GTM pivot stories in startups for you. Tim Zheng is Apollo's Co-founder and CEO. An engineer by trade, he founded the company in 2015 and today is leading the product's evolution to an end-to-end AI-powered sales platform. We are very grateful as Tim wrote this post exclusively for Notorious.

Apollo’s path to $100M ARR almost didn’t happen.

After a relatively smooth journey from $0 to $5M, Apollo’s growth hit a wall. By 2020, we were out of cash. Our sales-led motion wasn’t just slow—it was killing us. Our unit economics were upside down, spending $1 to acquire only $0.80 in revenue. We had six months of runway left. Morale was tanking, and our best talent was leaving. We had two options: pivot or die.

So we pivoted—hard.

We switched from a high-touch, sales-led motion to a freemium, product-led growth (PLG) model, with a self-serve product priced for SMBs. It worked. In 24 months, we tripled in size, surpassed $100M ARR, raised three more rounds, and today, Apollo’s valuation sits at $1.6B.

How We Did It: The Four Pillars of Apollo’s PLG Strategy

1. Find Your Uncontested Market

If they zig, we zag.

Before 2020, we were fighting for mid-market and enterprise deals, competing with sales tech giants. Meanwhile, we saw massive, unmet demand from SMBs and startups—they wanted an easy-to-use, all-in-one GTM platform but lacked the budget and ops teams to manage complex enterprise tools.

So we stopped chasing the mid-market and pivoted to serve SMBs with:

● $99/month pricing (vs. $10K+ annual contracts)

● Freemium, self-serve onboarding (so users could activate without talking to sales)

● A platform built for immediate value (usable from day 1 with minimal setup)

Lesson: Don't compete head-on with incumbents. Find an underserved segment and build exactly what they need.

2. Growth = NPS x Virality

In PLG, your product is the growth engine. Our key insight? Net Promoter Score (NPS) is not just a retention metric—it’s a growth metric.

Instead of forcing referrals through gimmicks (like “invite friends for credits”), we focused 100% on making the product better. As our NPS skyrocketed, word-of-mouth took off. Today:

● More than 90% of new users come from organic channels.

● Most inbound traffic is from branded search (proof of demand).

● Our viral factor compounds as happy customers fuel signups.

Lesson: The best virality play isn’t a referral program—it’s a product that people can’t stop talking about.

3. Turn Internal Data into an SEO Growth Engine

We had zero budget for paid ads or traditional content marketing, so we asked: What are our users already searching for?

Sales reps and founders were constantly looking for contact and company information—and they were already searching for it inside Apollo. We flipped this inside-out by indexing our data on Google in a growth hack we called “Discovery SEO.”

● We created millions of landing pages featuring useful contact and company data.

● These pages ranked on Google for highly relevant search queries.

● Hundreds of thousands of users found us organically—without ads.

This one growth hack generated orders of magnitude more traffic than paid ads—at zero cost.

Lesson: Your product likely has hidden SEO potential. Ask: What high-intent searches does our product already solve? Then, turn that into organic acquisition.

4. Experiment Relentlessly to Move Key Metrics

We didn’t just guess our way to growth—we applied the scientific method to increase retention by 6x—without adding features.

We focused on understanding user behavior rather than adding more features. Instead of guessing, we ran rigorous correlation analyses on what actions led to long-term retention. The key was identifying what behaviors distinguished high-retention users from those who churned, and then designing product experiences to drive those behaviors.

1. Mapped the funnel: Identified where users were dropping off.

2. Correlated behaviors with retention: Users who completed 3+ key actions (e.g., sending an email) had higher long-term retention.

3. Designed interventions: We nudged users toward those key actions via in-app guidance and onboarding tweaks.

4. Iterated weekly: We ran constant A/B tests to refine the experience.

Lesson: PLG isn’t about “big bets”—it’s about small, data-driven improvements that compound over time.

Takeaways (& How Apollo Continues to Scale)

Two years ago, we were on the brink of collapse. Today, we’re cash-flow positive and growing faster than ever. But the pivoting never really stops. The market evolves, competition shifts, and expectations rise. Staying ahead means constantly reevaluating and adjusting course.

Apollo isn’t just scaling—it’s redefining how companies grow. With AI-driven sales automation, deeper data enrichment, and an expanding ecosystem of integrations, we’re eliminating friction in the GTM process and shaping the next phase of PLG.

The game isn’t just about getting bigger; it’s about getting better. Find your market. Optimize ruthlessly. Build a product people can’t shut up about. That’s how you win.

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango, Tome and Workmate.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

15 Biggest Stock Gainers (1 month):

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• Arva AI, an AI-powered business verification platform designed to streamline and expedite verification for banks and fintech companies, has raised $3M. The round was led by Gradient Ventures, with participation from Olive Tree Capital, Amino Capital, 468 Capital and Y Combinator.

• Atomicwork, an agentic service management solution that empowers IT teams to automate employee support and IT service management, has raised $40.07M. The round was led by Blume Ventures and Z47, with participation from Alphatron Capital, Foster Ventures, Neon Fund, Matrix and Storm Ventures.

• BeHeard, an AI-based platform designed to enhance customer feedback through AI agents, has raised $5M. The round was funded by Anthropic, Ridge Ventures, Sterling Road, True Ventures and Menlo Ventures.

• Boardy, an AI-driven professional networking startup, has raised $8M. The round was led by Creandum, with participation from 8VC, Precursor Ventures, Afore Capital, FJ Labs, NextView Ventures, Soma Capital and Hacker Fellowship Zero.

• Borderless AI, a startup building AI agents for HR departments, has raised $32M. The round was led by SIG and Aglaé Ventures, with participation from PeopleTech Partners and Trac.

• Collate, an AI-based life sciences platform intended to automate the documentation processes that slow down drug and medical device development, has raised $30M at a $100M valuation. The round was led by Redpoint Ventures, with participation from First Round Capital, Conviction Partners and Y Combinator.

• Confido Health, a startup building AI-powered digital workers for the healthcare industry, has raised $3M. The round was led by Together Fund, with participation from MedMountain Ventures, Rebellion Ventures and DeVC.

• Coplay, an AI copilot for game developers, has raised $1.2M. The round was led by Failup Ventures, with participation from Tower Research Ventures, Founders, Inc and Sequoia Capital.

• Fazeshift, an AI-powered accounts receivable software designed to eliminate manual tasks, has raised $4M. The round was led by Gradient Ventures, with participation from Pioneer Fund, Wayfinder Ventures, Phoenix Investment Club and Y Combinator.

• Grove AI, an AI clinical research agent designed to accelerate participant recruitment and engagement at scale, has raised $4.9M. The round was led by A* Capital, with participation from Afore Capital, LifeX Ventures, Pear and Upfront Ventures.

• Jentic, an AI integration software intended to connect agents with application programming interfaces securely, has raised $4.19M. The round was led by Elkstone, with participation from Sure Valley Ventures, TechOperators and Shuttle.

  Keye, an AI-native due diligence platform offering data analysis tailored for PE investors, has raised $3.5M at a $35M valuation. The round was funded by Syntax Ventures, DG Daiwa Ventures and Y Combinator.

• Lanai, an enterprise operating system designed to assist organizations in adopting AI, has raised $10M. The round was led by Juxtapose, with participation from Lux Capital, F7 Ventures and BAG Ventures.

• Orchid Security, a security platform that leverages LLMs to unify and secure complex identity environments across enterprises, has raised $36M. The round was led by Intel Capital and Team8, with participation from Capital One.

• Riley AI, an AI-powered product insights assistant, has raised $3M. The round was led by Vertex Ventures US, with participation from NextView Ventures and Hyphen Capital.

• Salt AI, an AI workflow orchestration firm for enterprises, has raised $3M. The round was led by Morpheus Ventures, with participation from Irregular Expressions, Calm Ventures and Struck Capital.

• Tenex.AI, an AI-enabled cybersecurity platform providing managed detection and response services for Google Cloud environments, has raised an undisclosed amount of funding from Andreessen Horowitz and Shield Capital.

Early Stage:

• 1Up, an AI-powered knowledge automation platform for sales teams, has raised $5.25M. The round was funded by Upfront Ventures and Lightbank.

• Bioptimus, a startup that is developing a foundational AI model for biology, has raised $41M. The round was led by Cathay Innovation, with participation from Hitachi Ventures, Sunrise Capital, Andera Partners, Pomifer Capital, Boom Capital Ventures, Sofinnova Partners and Bpifrance.

• Dub, an open-source link management infrastructure platform designed for modern marketing teams, has raised $2M. The round was funded by OSS Capital.

• nexos.ai, an infrastructure company providing a centralized platform for enterprises to integrate and manage multiple AI models, has raised $8M. The round was led by Index Ventures, with participation from Creandum and Dig Ventures.

• Nilus, an AI-driven treasury management platform, has raised $10M. The round was led by Vesey Ventures and Felicis, with participation from Better Tomorrow Ventures, Bessemer Venture Partners and Cerca Partners.

Series A:

• Backflip, an AI-driven design platform that turns text descriptions and photos into 3D-printable models, has raised $30M. The round was led by Andreessen Horowitz and New Enterprise Associates.

• Basis, a startup developing AI agents for accounting tasks, has raised $34M. The round was led by Khosla Ventures, with participation from Better Tomorrow Ventures, BoxGroup, Avid Ventures and NFDG.

• Bland AI, an AI based phone-calling platform designed for enterprise communication, has raised $59.43M. The round was led by Scale Venture Partners, with participation from ElevenLabs, Cameron Ventures, Horizon Venture Capital and Y Combinator.

• Decart, a startup that helps businesses train AI models at scale, has raised $32M at a $500M valuation. The round was led by Benchmark, with participation from Sequoia Capital and Zeev Ventures.

• Eve, an AI-powered platform designed to assist plaintiff law firms throughout every phase of a legal case, has raised $47M. The round was led by Andreessen Horowitz, with participation from Menlo Ventures and Lightspeed Venture Partners.

• Gumloop, a no-code platform designed for automating workflows with AI, has raised $17M. The round was led by Nexus Venture Partners, with participation from First Round Capital and Y Combinator.

• Raspberry AI, a generative AI platform for fashion designers, has raised $24M. The round was led by Andreessen Horowitz, with participation from MVP Ventures, Correlation Ventures and Greycroft.

Series B:

• Air, a provider of creative workflow automation solutions for brands and marketers, has raised $35M. The round was led by Avenir Growth Capital, with participation from Salesforce Ventures, Good Friends and Xfund.

• Anysphere, an applied research lab working on automating coding, has raised $100M at a $2.6B valuation. The round was led by Thrive Capital, with participation from Andreessen Horowitz.

• Clay, a provider of AI technology designed to automate sales and marketing processes, has raised $40M at a $1.25B valuation. The round was led by Meritech Capital Partners.

• Hippocratic AI, a startup building AI solutions that can handle non-diagnostic patient-facing tasks, has raised $141M at a $1.64B valuation. The round was led by Kleiner Perkins, with participation from Universal Health Services, WellSpan Health, Nvidia, Premji Invest, SV Angel, General Catalyst and Andreessen Horowitz.

• StackBlitz, an instant fullstack web integrated development environment for the JavaScript ecosystem, has raised $105.5M. The round was led by Emergence and Ghosal Ventures, with participation from Madrona Venture Group, Conviction Partners and Mantis VC.

Series C:

• ElevenLabs, a cloud-based AI platform that enables customers to generate synthetic speech for use in applications such as dubbing, has raised $250M. The round was led by ICONIQ Growth, with participation from Andreessen Horowitz.

• Render, a cloud application platform that developers can use to deploy applications, services and websites on cloud infrastructure, has raised $80M. The round was led by Georgian, with participation from General Catalyst, South Park Commons, Addition, Bessemer Venture Partners, 01 Advisors and Avra.

Series D:

• Instabase, a company that creates software for extracting and processing unstructured data from myriad document types, has raised $100M. The round was led by Qatar Investment Authority, with participation from Greylock, Andreessen Horowitz, Index Ventures and Nea.

• Synthesia, an AI startup that lets businesses produce lifelike video avatars, has raised $180M. The round was led by New Enterprise Associates, with participation from GV, Atlassian Ventures, MMC Ventures, FirstMark Capital, WiL and PSP Partners.

Series J:

• Databricks, an AI and data analytics firm, has raised $10B at a $62B valuation. The round was led by Insight Partners, GIC Private, WCM Investment Management, Thrive Capital, Andreessen Horowitz and DST Global, with participation from Sands Capital, Stripes, Lightspeed Venture Partners, ICONIQ Growth, MGX, Kleiner Perkins, Ontario Teachers' Pension Plan, Wellington Management, Macquarie Group and Olive Hill Group.

Later Stage:

• Anthropic, a developer of a series of enterprise-focused large language models, has raised $1B. The round was funded by Alphabet.

• Perplexity, the creator of an AI search engine, has raised $500M at a $9B valuation. The round was led by IVP, with participation from Nvidia, Builders + Backers, New Enterprise Associates, B Capital and T. Rowe Price Group.

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Notorious Startup of the Week: Highlight

In the rapidly evolving world of AI and large language models (LLMs), one major challenge stands out: how do we move beyond simple question-and-answer interfaces into a realm where agents can truly work for us, long-term and in the background, across all the tools and environments we rely on every day?

Enter Highlight. Built from the ground up to empower agents, Highlight leverages underlying browser technology—specifically Chromium via Electron—to bridge the gap between the intelligence of LLMs and the practical, complex tasks that span web apps, operating systems, and beyond. Think of it as the “iPhone for LLMs”—an easy-to-use platform that consolidates all the best interfaces and agents into a single, seamless ecosystem. For this edition of Notorious, Highlight CEO and Founder Pim de Witte shares his approach and strategy to building Highlight with us:

Designed for Agents from Day One

From its inception, Highlight has been designed to run agents. Unlike traditional browser-based interfaces that are limited by security models and URL-based permissions, Highlight provides a native runtime environment. This environment empowers agents to interact directly with the operating system in ways a standard browser can’t. Here’s how:

• Seamless Agent Integration: You can publish web interfaces as Highlight agents in under a minute. Because Highlight shares the same foundation as Chrome, any web-based experience can become a native Highlight agent.

• Integrated Authentication & Runtime API: Agents can hook into Highlight’s own authentication system and use a special Runtime API to access OS-level features securely. This is a permissions-based approach that maintains safety while granting more powerful capabilities.

• App Store for Agents: Highlight has its own app store with full deep-linking support. It can transform popular websites—like Goodreads or LinkedIn—into Highlight-compatible apps in minutes. As a result, nearly any web experience can quickly become part of your agent’s toolkit.

These elements come together to give agents everything they need to accept tasks, convert them into prompts, find the right tools, and execute them as long-running background processes.

How Long-Running Tasks Work

With Highlight, the dream scenario becomes a reality: you delegate a complex, time-consuming task, and your agent runs with it—quietly, in the background, until it’s done. Here’s what that looks like:

1. Prompt Assembly: Highlight identifies or constructs the right prompts for the agent. For many consumer tasks, a robust prompt repository will supply the perfect instructions.

2. Enterprise-Ready Guardrails: In more controlled environments, deterministic guardrails can ensure tasks run safely within corporate policies and compliance requirements.

3. Task Detection: Highlight eventually will be able to recognize when you want to initiate a long-running task—something that would traditionally require you to babysit a browser tab or script (coming soon).

Over time, as model-based systems like RunnerH improve at performing computer-level tasks, these agents will become more adept at handling intricate, behind-the-scenes operations. Highlight consolidates this complexity, choosing the best intelligence and context for you automatically, just as an iPhone chooses the best networks and configurations without user intervention.

The User Experience: Invisible, Yet Powerful

The ideal user experience is effortless. With Highlight:

• Background Execution: Assign a task and let the agent work silently. No invasive pop-ups or interruptions. Check in from anywhere—phone, computer, or tablet—and see how your tasks are progressing.

• Sandboxed Browser Agents: Because these agents run within Highlight’s controlled environment, they’re more secure and intuitive. They understand web interfaces by default, which covers a huge range of use cases immediately. Over time, Highlight’s runtime will evolve to let agents control entire desktops and local applications with proper permissions.

• Scalability: Spawn agents will eventually work on tasks simultaneously (coming soon). Each agent knows when to finish and when to request more input, enabling a level of productivity unheard of in today’s point-and-click workflows.

Winning on the Task Interface

The first step to mainstream adoption is to significantly improve how users interact with and benefit from LLMs. Highlight focuses on two key accelerations:

1. 10x Faster Inputs: By automatically gathering context and writing prompts for you, Highlight reduces the friction of talking to an LLM. Screen-based prompting—where the system anticipates what you need next—lets you move from idea to execution almost instantly.

2. 10x Faster Outputs: Highlight delivers results where you need them most. Whether writing directly into a Notion doc, updating tasks in Linear, or scheduling events in your Calendar, Highlight’s output integration ensures the agent’s work lands exactly where it’s useful.

As power users begin to automate their own input and output workflows—essentially building personal prompt repositories—Highlight’s underlying runtime can leverage these same prompts to control browser instances with natural language. This creates a cycle of continuous improvement, personalization, and capability expansion.

Memory, Prompts, and Enterprise Scalability

Once Highlight nails the core task interface, the platform turns its attention to deeper capabilities:

• Memory: Agents should know you—your preferences, habits, and past tasks. Highlight’s memory layer sits above all agents, ensuring continuity and personalized results.

• Prompt Repository: By accumulating a library of high-quality prompts, Highlight matches context-rich tasks with the right solutions, accelerating productivity even further.

• Long-Running Tasks & Enterprise-Ready Workflows: Eventually, organizations want these capabilities in secure, audited environments. Highlight’s architecture supports that transition seamlessly.

Building a Moat Through Integration and Context

Highlight’s advantage compounds as it integrates into every aspect of the user’s digital life:

• Capture Interface: Highlight becomes the single pane of glass for delegating tasks. Instead of juggling multiple apps, users rely on Highlight’s interface. One platform, one workflow.

• Cross-Platform Reach: With native support across devices, it doesn’t matter if you’re on Windows at work or an iPhone on the go—Highlight ties everything together.

• Growing Ecosystem: Agents and apps published in Highlight’s store will proliferate, making it harder for big tech players to replicate the ecosystem quickly. Coupled with Highlight’s unique memory and prompt optimization, this creates a powerful defensible advantage.

The Path to Magic

Winning in the consumer world means delivering an experience that feels like magic—where the agent already knows what you want and acts on it without exhaustive setup. Achieving this requires continuous refinement, focus, and user-centric design. Highlight’s long-running tasks and dynamic prompt ecosystem won’t appear as “infrastructure” to users; they’ll simply know it as the capability to do more, faster, with less hassle.

The trajectory is clear:

1. Perfect the task interface.

2. Accelerate input and output.

3. Leverage prompts, memory, and runtime integration.

4. Personalize at scale.

5. Let users carry these capabilities across every device and platform.

By following these steps, Highlight aims to usher in an era where LLM-powered agents are not just tools you consult occasionally—but trusted, ever-present assistants that quietly shape and streamline your digital life, no matter what device you’re on or what task you need done.

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango, Tome and Workmate.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

15 Biggest Stock Gainers (1 month):

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• Across AI, a startup developing Agentic AI for enterprise workflows, has raised $5.75M. The round was led by Village Global and Cota Capital.

• AIMon, a full-cycle LLM App accuracy platform, has raised $2.3M. The round was led by Tidal Ventures and Bessemer Venture Partners.

• Argmax, a startup dedicated to empowering developers and enterprises in deploying commercial-scale inference workloads on user devices, has raised $8M. The round was led by Salesforce Ventures, with participation from General Catalyst.

• Briefcase, an AI-powered bookkeeping assistant designed to automate manual bookkeeping tasks, has raised $3M. The round was led by Earlybird Venture Capital, with participation from Entrepreneur First and Tiny Supercomputer Investment Company.

• Cake, a managed open-source AI infrastructure platform, has raised $10M. The round was led by Gradient Ventures, with participation from Firestreak Ventures, Primary Venture Partners, Alumni Ventures, Friends & Family Capital and Correlation Ventures.

• Cartesia, a multimodal intelligence tool designed to enable real-time, on-device AI capabilities on every device, has raised $22M. The round was led by Index Ventures, with participation from Lightspeed India Partners, FactoryHQ, SV Angel, General Catalyst and A* Capital.

• Elvex, an AI-based tool intended to reduce complexity and mitigate risk in enterprise workflows, has raised $6.4M. The round was led by m]x[v Capital and FundersClub, with participation from Remarkable Ventures, Industry Ventures and Accelerator Ventures.

• eSelf AI, a platform for businesses to create face-to-face conversational AI agents, has raised $4.5M. The round was led by Explorer Investments, with participation from Ridge Ventures.

• NeuBird, a company using generative AI to automate IT site reliability operations, has raised $44.5M at a $100M valuation. The round was led by M12, with participation from Prosperity7 Ventures, Mayfield Fund, AIspace Ventures and StepStone Group.

• Pathway, a startup building live AI systems that think and learn in real-time as humans do, has raised $10M. The round was led by TQ Ventures, with participation from Inovo VC, Market One Capital, Id4 Ventures and Kadmos Capital.

• Pin, an AI-powered recruitment platform designed to streamline the hiring process from sourcing to interview scheduling, has raised $3M. The round was led by Expa.

• Pixeltable, an open-source AI data infrastructure company, has raised $5.5M at a $25M valuation. The round was led by The General Partnership, with participation from Liquid 2 Ventures, South Park Commons, Exceptional Capital and Serena Ventures.

• Sightglass, an AI-powered investor relations platform for the private markets, has raised $3M. The round was led by Base10 Partners.

• WaveForms AI, a startup creating AI assistants that pick up on emotional cues from verbal interactions, has raised $40M at a $200M valuation. The round was funded by Andreessen Horowitz.

• Zero, a startup developing an AI-powered “zero-click” CRM, has raised $2.7M. The round was led by 20VC, with participation from 20Growth, 20Product, Discovery Ventures, Illusian and Greens.

Early Stage:

• xAI, Elon Musk’s artificial intelligence venture, has raised $6B. The round was funded by Valor Equity Partners, Sequoia Capital, Andreessen Horowitz, AJI Capital and Qatar Investment Authority.

Series A:

• Aampe, a provider of mobile app engagement and personalization infrastructure for short-form notifications and messaging, has raised $18M. The round was led by Theory Ventures, with participation from Z47.

• Brellium, a clinician-validated AI audit system designed to help automate medical chart review, has raised $11.14M. The round was funded by First Round Capital.

• BRM, an AI-powered vendor management and procurement platform, has raised $15M. The round was led by Caffeinated Capital, with participation from Definition and Original Capital.

• Chargezoom, a platform for AI-powered billing and integrated payments, has raised $11.5M. The round was led by Kickstart Fund, with participation from Adly, Frazier Group, Early Light Ventures, Motley Fool Ventures, SaaS Venture Capital, Stout Street Capital and Okapi Venture Capital.

• Enterpret, an AI-integrated customer feedback intelligence platform for product development and CX teams, has raised $20.8M. The round was led by Canaan Partners, with participation from Wing VC, Kleiner Perkins, Peak XV Partners and Recall Capital.

• Happyrobot, a startup that specializes in AI-enabled voice solutions for the logistics sector, has raised $15.6M. The round was led by Andreessen Horowitz, with participation from Ryder Ventures and Y Combinator.

• Liquid AI, a foundation model company building general-purpose AI systems at every scale, has raised $250M at over a $2B valuation. The round was led by AMD, with participation from Itochu Techno-Solutions, Nuclea, OSS Capital, Duke Capital Partners and PagsGroup.

• RapidCanvas, a startup developing AI agents that automate complex tasks traditionally performed by data scientists and engineers, has raised $16M. The round was led by Peak XV Partners, with participation from Titanium Ventures, Accel and Valley Capital Partners.

• Stainless, a startup creating an SDK generator powered by AI, has raised $25M at a $152M valuation. The round was led by Sequoia Capital and Andreessen Horowitz, with participation from Zapier, MongoDB Ventures, The General Partnership and Felicis.

• Stigg, a monetization platform for engineers, has raised $17.5M. The round was led by Red Dot Capital Partners, with participation from Unusual Ventures, Emerge Ventures, Cerca Partners and Redseed.

• Twelve Labs, a developer of hyperscale AI models that understand various types of information in video, has raised $30M. The round was led by NVentures and New Enterprise Associates, with participation from Intel Capital, Databricks, HubSpot Ventures, SK Telecom, Snowflake, In-Q-Tel, Operator Collective, InnoWhale Ventures, Index Ventures, Radical Ventures, WndrCo, Samsung NEXT Ventures and Korea Investment Partners.

• Vapi, a developer platform for deploying Voice AI agents, has raised $20M. The round was led by Bessemer Venture Partners, with participation from Abstract Ventures, AI Grant, Y Combinator and Saga Ventures.

• Vooma, an AI platform designed for freight brokers and carriers, has raised $16.3M in Seed and Series A funding. The $3.6M Seed Round was led by Index Ventures and the $13M Series A was led by Craft Ventures.

Series B:

• Connectly, a conversational AI platform that automates how businesses communicate with their customers, has raised $20M at a $90M valuation. The round was led by Alibaba Group, with participation from RX Ventures, Globant Ventures, Falabella Ventures, Unusual Ventures and Volpe Capital.

• Luma AI, a video generator platform intended to offer multimodal AI to expand human imagination and capabilities, has raised $90M at a $267.71M valuation. The round was led by Andreessen Horowitz, with participation from Amazon Web Services, Advanced Material Development, South Park Commons, Prototype Capital, Factorial Funds, Bossa Invest, AJI Capital and Silicon Valley Future Capital.

• Sublime Security, an AI-powered email security platform, has raised $60M. The round was led by IVP, with participation from Citigroup Alternative Investments, Decibel Partners, Index Ventures and Slow Ventures.

• Yurts, a company providing generative AI integration at scale for defense, government, and enterprise customers, has raised $40M. The round was led by XYZ Ventures, Glynn Capital and Nava Ventures.

Series C:

• Evinced, a software company focused on accessible web and mobile development, has raised $55M. The round was led by Insight Partners, with participation from M12, Capital One Ventures, Engineering Capital, Vertex Ventures US and BGV Group Management.

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AI and the Dawn of the 10x Founder

Today we have a special guest blog post by HBS Professor and GP / Co-Founder of Flybridge Capital Partners Jeff Bussgang. Jeff is brilliant and is a mentor. He's also the author of a new book: The Experimentation Machine: Finding Product Market Fit in the Age of AI. Enjoy:

In February 2024, OpenAI co-founder and CEO Sam Altman made an audacious prediction during an interview at a JP Morgan conference:

“We’re going to see 10-person companies with billion-dollar valuations pretty soon…In my little group chat with my tech CEO friends there’s this betting pool for the first year there is a one-person billion-dollar company, which would’ve been unimaginable without AI. And now [it] will happen.”

Startups are defined by their constraints: they have limited time, money, talent, resources, and opportunities compared to established businesses. But their main advantage—their ace in the hole—is their ability to move fast. Speed is imperative as startups search for a functioning business model. And now with the power of generative AI, founders will be expected to move even faster. Welcome to the era of the 10x Founder.

The startup world has long mythologized the 10x developer: the computer engineer who is so good that they can do the work of 10 average engineers. 10x developers were once the difference between a startup becoming a unicorn and fizzling out.

10x Founders have their own superpowers: the ability to recognize the next most important task and deploy the right AI workflow to execute it efficiently. They can build and scale their startups faster, with fewer resources and less capital than traditional founders. They integrate AI throughout their organization, from product development to sales and marketing to operations. They run more experiments to out-learn and out-iterate their competitors. They scale their companies without necessarily growing headcount. They use AI in creative ways to improve every function of their business.

The best way to understand a 10x Founder is to introduce you to a few of them. At Flybridge’s recent Founders Week 2024 Conference in NYC, we featured portfolio company founders who are using AI to grow rapidly and efficiently.

AllSpice: Scaling PLG with AI. Hardware engineering startup AllSpice demonstrates how 10x Founders can grow rapidly with minimal resources. When co-founders Valentina Ratner and Kyle Dumont saw that hardware teams were losing billions on mistakes due to poor version control, they built a "GitHub for hardware teams." With a successful bottoms-up sales motion and early signs of product-market fit - top cohorts spending 40 hours per month on the platform with over 100 weekly interactions - the team faced a critical growth challenge: scaling customer acquisition with limited resources and avoiding the PLG Trap.

Instead of building an expensive outbound sales team, Ratner and Dumont leveraged AI to nurture their strong inbound demand. They use tools like Eleven Labs and Heygen to create thousands of customized demonstration videos from a single recording. Their customers are engineers who often prefer these (AI-generated) video demos over live sales calls – and AllSpice can use these tools to move customers further down the funnel. They also use AI to automatically generate and maintain product documentation, ensuring it stays current as their platform evolves. This AI-powered approach has allowed AllSpice to efficiently convert both small teams and enterprises through multiple sales motions while maintaining a lean team focused on product development.

Topline Pro: Unlocking a Fragmented Market. Topline Pro demonstrates how AI unlocks previously impossible business opportunities. Co-founders Nick Ornitz and Shannon Kay initially launched a video chat service for plumbers, but pivoted when they discovered these businesses needed help finding customers. Using GPT-3, they built an all-in-one marketing platform for home service providers.

With its promise to provide pros with “More customers. More jobs. Less bullsh*t”, Topline Pro is remarkable in how they use AI to serve a highly fragmented market efficiently. They use ChatGPT to analyze small business profiles in local markets and identify qualified leads, create personalized sales content based on those profiles that achieves 10% response rates, and provide 24/7 customer support through AI chatbots. The AI chatbot has become so popular with pros that with fewer than 40 employees, Topline Pro has helped generate $180 million in new business for thousands of pros across the country.

TalkTastic: Scaling Founder-led Support. As a self-taught, “pseudo-technical” founder with a background in AI, Matt Mireles created an elegant solution when his voice-first neural interface startup TalkTastic needed a customer support system. Instead of a traditional chat system, he built an AI-powered workflow in just four hours that begins with a personal welcome video and allows customers to leave voice messages or text questions. These messages are transcribed by ChatGPT, analyzed by Claude AI to create personalized responses, and automatically flagged if they indicate bugs. The entire system runs without human intervention, yet customers regularly praise the support experience as "stellar."

Startupland is quickly being divided into old world and new world thinking. Old world thinking says that Mireles has to purchase an expensive, generic chat-based support system because he doesn’t have the time or resources to build something better. New world thinking—10x Founder thinking—says “give me four hours.”

Old world thinking says you need hundreds of salespeople, organized by region, to attack a fragmented industry. New world thinking says, “I can send personalized emails to thousands of people per week without hiring anyone.”

I share these stories because it’s hard to break out of the old world mindset, even when you come into contact with the power of AI. We need to see 10x Founder thinking in action to fully understand the leverage we now have at our fingertips. And here’s the most magical part: these modern tools keep getting better. The more you can instrument your product development, sales and marketing, and customer support processes with AI – even using the imperfect tools today – the faster you’ll be able to adopt the improved tools as they become available.

Here is one more story that exemplifies the 10x Founder shift, this one from a friend’s startup still in stealth mode. This founder recently lost his technical cofounder. In the past, that would have been an existential crisis. Today, though, my friend has opted to use ChatGPT to build his MVP. ChatGPT has become the perfect co-founder.

As he shared with me, “The result is that my burn rate is incredibly low, and velocity—the speed at which I can build and iterate on my product—has shot through the roof.” He has been able to test out his initial hypotheses while searching for a new technical co-founder on the side.

Traits of a 10x Founder

Let’s try to deconstruct the anatomy of a 10x Founder. What makes Nick Ornitz, Shannon Kay, Matt Mireles, and my stealth founder friend different? There are several traits they embody. I encourage every founder to emulate and develop them:

Scaling without Growing

When I was a founder, success meant hiring—more capital meant more headcount. That era is over. Going forward, startups will be less obsessed with hiring and more focused on deploying AI to enhance their organization's ability to scale without growing. As Adobe executive Scott Belsky says, "We are entering an era of scaling without growing... Every function of an organization will be refactored in ways that allow small teams to scale their reach and ambition without growing headcount proportionately."

Topline Pro and TalkTastic demonstrate this mindset. Rather than hiring hundreds of sales reps and support agents, they use AI to automate outreach and customer service with minimal staff. And while my stealth founder friend isn't at scale yet, he chose to build his MVP using ChatGPT rather than hire an expensive technical cofounder.

Building AI-Forward Startups

At Flybridge, we invest in AI-Forward startups - companies that use AI to build faster, better, and more efficiently. Building an AI-native organization takes intention and a commitment to reinvent how startups operate. Look at any core elements of the business model – customer value proposition, go-to-market, technology and operations, profit formula – and you'll find dozens of startups building AI tools to help founding teams become more efficient. One friend who runs a public software company tells me he's tracking 44 companies just in the AI sales development space as he looks to bring automation and AI to his go-to-market motion.

Not all these tools will survive, but soon some combination of big and small companies will provide an extraordinary suite of AI tools to enhance productivity across organizations. Lower R&D, Sales & Marketing, and G&A costs will eventually translate into higher profits.

Preserving Capital and Driving Profits Margins

As a venture capitalist, I can't help but think of the financial implications of generative AI tools. Next time a founder tells me they need millions for a sales team, I'll point them to what AllSpice and Topline Pro accomplished with good tooling. If they can't comprehend how to use such powerful leverage, they may not survive in VC-backed startups. Money will follow founders who take full advantage of AI, and results will be close behind.

Generative AI is making software companies more profitable while requiring less capital. Some argue that competition and lack of moats in an AI age outweigh the efficiency gains. Those headwinds are real, but they're not strong enough to slow down this productivity boom.

The age of the 10x Founder is here. The winners in this new era won't necessarily be the founders with the most capital or the largest teams, but those who best harness AI to run rapid experiments and scale efficiently.

Want to learn more about building startups in the age of AI? My upcoming book The Experimentation Machine provides a complete playbook for becoming a 10x Founder.

I share detailed case studies, specific AI tools and techniques, and a framework for running the experiments that will help you find product-market fit faster than ever. Pre-Order today to read the first three chapters. Use the code NOTORIOUS at checkout for 10% off.

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango, Tome and Workmate.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

15 Biggest Stock Gainers (1 month):

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• /dev/agents, an AI agents operating system developer, has raised $56M. The round was led by Index Ventures and CapitalG.

• Argil, a Paris-based AI video engine for content creators, has raised $4.16M. The round was led by EQT Ventures.

• Circleback., an AI-powered platform intended to create a unified workflow that simplifies meeting management, has raised $2.5M. The round was funded by Transpose Platform Management, Rebel Fund, Pioneer Fund and Y Combinator.

• PlayAI, a voice interface for AI, has raised $21M. The round was led by Kindred Ventures and 500 Global, with participation from Pioneer Fund, Trac, Soma Capital, Race Capital and Y Combinator.

• Tempest, an enterprise-grade developer platform intended to provide a single surface for the entire software stack, has raised $3.2M. The round was led by Abstract Ventures, with participation from BoxGroup, Ascolta Ventures and Background Capital.

Early Stage:

• Talus Network, a developer of a blockchain protocol to build autonomous AI agents for performing tasks, has raised $6M at a $150M valuation. The round was led by Polychain Capital, with participation from Strategxy Ventures, Foresight, Giggster, Alora Pharmaceuticals, Echo Capital Group, Animoca Ventures, GeekCartel, Zero Gravity and Fortune Tech Ventures.

Series A:

• Wherobots, a cloud-native data analytics platform intended to help businesses process data in a geospatial context, has raised $21.5M. The round was led by Felicis, with participation from Wing VC, JetBlue Ventures, Prosperity7 Ventures and Clear Ventures.

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Notorious Startup of the Week: Enterpret

One of the emerging and most important datasets is the voice of the customer. Customers leave feedback and share their concerns and praises everywhere today - in support tickets, on social media, in emails, on phone calls, in the product etc. However, it has been extremely challenging for companies to be able to unify these nuggets of feedback and understand who they are from and what they mean for product, support and marketing decisions. Enter Enterpret. Enterpret is a fast-growing startup (3x+ y/y) backed by top venture firms (Kleiner Perkins) with some of the best customers logos I’ve seen at this stage (Series A/B). Enterpret is customer obsessed and is leveraging AI to deliver a better product experience and make sense of the wealth of online breadcrumbs left from customers. For this edition of Notorious, Enterpret Head of Product Marketing Tiffany Go and CEO Varun Sharma share how they are leveraging AI to win over super high quality customers.

From Noise to Insight: Enterpret’s AI Strategy for Transforming Customer Feedback

Enterpret is the unified customer feedback intelligence platform used by teams like Canva, Notion, Vimeo, and Strava. With Enterpret, these teams turn the Voice of Customer into a guiding force in product development, driving growth and building products that customers genuinely love.

With a focus on transforming raw feedback into actionable insights, Enterpret builds adaptive AI models to turn all customer interactions into a unified Voice of Customer, driving strategic decisions and empowering teams to stay ahead.

Turning subjective feedback into insights

Enterpret turns diverse, subjective customer feedback into objective, actionable insights that truly capture the Voice of Customer (VoC).

This is achieved by ensuring comprehensive feedback collection from a range of sources—support tickets, reviews, sales conversations, surveys, social media, and community forums. Each piece of feedback is processed through AI-driven categorization, structuring it into both broad and granular categories.

This multi-level hierarchy enables teams to gain actionable insights without being overwhelmed by excessive detail, as the AI dynamically determines the depth based on relevance and context.

Providing real-time, product-specific feedback intelligence

Our AI models are uniquely capable of discerning feedback specific to the product by understanding its various features and capabilities. The feedback structure updates automatically in near real-time, maintaining alignment with new product developments, user base changes, and emerging issues.

With seamless integration across feedback channels, Enterpret captures VoC from any customer touchpoint, allowing teams to analyze and filter this feedback by any metadata—such as user cohorts, feedback sources, product features, and more.

Delivering insights that drive decisions

Additionally, Enterpret goes beyond generating standard insights; it provides net new information for product experts, meeting a high bar to ensure that the insights are deeply relevant, nuanced, and capable of informing strategic decisions. This level of precision supports data-driven product strategy, helping teams anticipate trends, identify issues, and prioritize actions based on quantifiable data that links back to the customer's original input.

Enterpret's platform also enables proactive applications such as issue reporting and trend alerts, empowering teams with real-time insights on the evolving needs and sentiments of their customers.

Supporting an agile approach to product and customer engagement

By consistently delivering a refined, multi-layered understanding of the Voice of Customer, Enterpret supports a well-informed, agile response to customer feedback, keeping teams ahead in their product development and customer engagement efforts.

Enterpret’s GTM: Building Trust, Demand, and Advocacy

At Enterpret, we’re not just building a product; we’re building a new category: Unified Customer Feedback Intelligence. This is more than a tool—it’s a foundation for every customer-centric company, a way to elevate the Voice of Customer across the organization. We believe it fuels growth, sparks innovation, and creates customer relationships that last.

Storytelling is the heart of our GTM strategy. We bring Enterpret’s purpose to life by spotlighting real customer wins and showing how they build products that put customer needs front and center. By sharing their stories, we’re creating a community of customer-obsessed brands who don’t just talk about being customer-centric—they live it.

Our GTM strategy is centered on three goals:

1. Build brand trust and awareness.

2. Grow demand and pipeline.

3. Foster customer love and turn it into advocacy.

Building brand trust and awareness

Building trust means delivering real value, and we like to have some fun along the way. Our brand stands out by being both useful and relatable. Here’s how we do it:

• User-generated content: Instead of pushing products, we let customers do the talking. We partner with customers like Notion, Coda, and Figma to build Voice of Customer templates (using their products) to show the power of customer feedback in action. It’s about their wins, not just ours.

• The permissionless pilot: We love brands who prioritize their customers, so we analyze public data from companies we admire—like Airbnb, OpenAI, and Starbucks. It’s our way of showing what Enterpret can do while offering actionable insights.

• Distinct brand voice: Customer feedback is a privilege, not just a data point. We take it seriously, but we keep things fresh and engaging—think insightful videos, playful memes, and content that brings our story to life.

Distributing value to grow demand

Whether it’s marketing or sales reaching out, it’s all about adding value. Every touchpoint counts, and we make sure it’s intentional. Here’s our approach:

• Meeting audiences where they are: We get our content in front of people where they’re already spending time—events, podcasts, sponsored newsletters, and close-knit communities for product and CX pros.

• ABM: Our account-based marketing is laser-focused. We nurture micro-segments with personal Loom videos and tailored content instead of casting wide nets. Each Proof of Concept (POC) is crafted around the customer’s unique data to set the stage for lasting partnerships.

• Constant experimentation: We’re constantly testing new ways to reach the right people—whether through paid ads, direct mail, SEO, or creative social pushes.

Turning customer love into advocacy

We’re all about creating genuine customer love. It’s built on impact, shared wins, and a community where customers feel seen, heard, and connected. Here’s how we turn customer love into advocacy:

• Standout customer experience: Customer experience is our North Star. We exist to solve our customers’ biggest pain points, and our success team ensures insights don’t just land—they partner in building out programs that drive real results.

• Spotlighting our customers: Our customers are the true standard-bearers of customer-centricity. We spotlight their journeys to show the real-world impact of a strong Voice of Customer program and to share the best practices that put customers first, like this Guide to Building a Voice of Customer Program. 

• Building an authentic community: We’re creating a space where customers connect, learn, and grow together. Through curated dinners, conference invites, and speaking engagements, we celebrate their stories and foster connections that go beyond business.

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango, Tome and Workmate.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

15 Biggest Stock Gainers (1 month):

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• Auquan, an AI solutions provider for financial services, has raised $10.48M. The round was led by Peak XV Partners, with participation from Neotribe Ventures.

• Boardy, an AI-driven professional networking startup, has raised $3M. The round was funded by HF0, 8VC, Precursor, Afore, FJ Labs, and NextView.

• Coframe, an AI startup focused on website optimization, has raised $9.3M. The round was led by Khosla Ventures and NFDG.

• Decart, a startup building a real-time generative AI open world model, has raised $21M. The round was led by Sequoia Capital, with participation from Zeev Ventures.

• Embedded Intelligence, a developer platform that allows users to build AI apps for the desktop using simple web technologies, has raised $10M. The round was funded by General Catalyst, Valor, SV Angel and Conviction Embed.

• Evertune, a brand monitoring and analytics platform designed for comparing different AI models' views about the brand, has raised $4M. The round was led by Eniac Ventures, with participation from Nextview.

• GlassFlow, a platform that runs event-driven data pipelines in Python, has raised $4.84M. The round was led by Upfront Ventures, with participation from Robin Capital, Tiny Supercomputer Investment Company and High-Tech Gründerfonds.

• Moondream, an open-source vision language model (VLM) designed to build multimodal apps, has raised $4.5M at a $22.5M valuation. The round was led by Felicis, with participation from M12 and Ascend Venture Capital.

• Pantheon AI, an AI architecture platform intended for designing offices, has raised $25M at a $62.4M valuation. The round was led by Andreessen Horowitz, with participation from Company Ventures, Felicis and 8VC.

• Passionfroot, a marketplace for business-focused content creators looking for brand partnerships, has raised $3.8M. The round was led by Supernode Global, with participation from Creandum, Scout Fund and S16VC.

• Persana AI, an AI agents and data integration platform for sales teams, has raised $2.3M. The round was led by Female Founders Fund, Race Capital and Stage 2 Capital, with participation from Y Combinator.

• Sapien, a startup building "AI coworkers" to work alongside CFOs, has raised $8.7M. The round was led by General Catalyst.

• Skipper, a browser management tool designed to organize digital information, has raised $1.8M. The round was led by Menlo Ventures.

Early Stage:

• Casap, a copilot and collaboration platform designed to automate disputes and reduce fraud costs, has raised $8.5M. The round was led by Lightspeed Venture Partners, with participation from Primary Venture Partners, Curql Collective, Commerce Ventures, Alloy Labs and gener8tor.

• Interface.AI, a provider of agentic AI solutions for community banks and credit unions, has raised $30M. The round was led by Avataar Venture Partners.

• Regal, a company that offers phone and text-based chatbots that can field common customer service requests, has raised $40M. The round was led by Emergence, with participation from Founder Collective and Homebrew.

• Sierra, a conversational AI platform for businesses, has raised $175M at a $4.5B valuation. The round was led by Greenoaks Capital Partners, with participation from Thrive Capital and ICONIQ Capital.

Series A:

• Bifrost, a generative 3D data platform, has raised $8M. The round was led by Carbide Ventures, with participation from Airbus Ventures, Surge Ventures, Wavemaker Partners, MD ONE Ventures and Techstars.

• Brightwave, a startup building AI agents to help with financial research, has raised $15M. The round was led by Decibel Partners, with participation from OMERS Ventures.

• CrewAI, an AI multi-agent platform that enables organizations to build crews of AI agents using any LLM model and cloud platform, has raised $18M across two rounds. The seed round was led by boldstart ventures, and the Series A was led by Insight Partners, with participation from Blitzscaling Ventures, Craft Ventures and Earl Grey Capital.

• Fixify, an AI-powered IT help desk solution provider, has raised $25M. The round was led by Decibel Partners, Paladin Capital Group and Costanoa Ventures, with participation from Scale Venture Partners.

• Genie AI, an AI-based legal assistant, has raised $17.53M. The round was led by GV and Khosla.

• Genmo, an AI company focused on video generation, has raised $28.4M. The round was led by New Enterprise Associates, with participation from WndrCo, The House Fund, Gold House Ventures, Eastlink Capital and Essence Venture Capital.

• Granola, an AI-powered notepad for meetings, has raised $20M. The round was led by Spark Capital, with participation from AI Grant, Lightspeed Venture Partners, Betaworks and Firstminute Capital.

• Neysa, a startup that provides AI and machine learning infrastructure and platform as a service to enterprise customers, has raised $30M. The round was led by Z47, Nexus Venture Partners and NTTVC.

• Procurement Sciences AI, an AI-powered bidding-intelligence platform for government contractors, has raised $11.38M at a $35M valuation. The round was led by Battery Ventures, with participation from K Street Capital, Blu Venture Investors and Tower Research Capital.

• Reality Defender, a cybersecurity company helping enterprises and governments detect deepfakes and AI-generated media, has raised $33M. The round was led by Illuminate Financial, with participation from Booz Allen Ventures, IBM Ventures, the Jefferies Family Office, Accenture, DCVC, The Partnership Fund for New York City and Y Combinator.

• Speckle, an open-source data platform for architecture, engineering, and construction, has raised $12.5M. The round was led by Addition, with participation from Frontline Ventures, Foundamental, Foreword and Matrix.

• Tollbit, a startup that offers AI bots and data scrapers a compliant way to compensate websites directly for content, has raised $24M. The round was led by Lightspeed Venture Partners.

Series B:

• Diffblue, an automated testing software designed to improve error-prone manual coding, with fully autonomous unit test writing, has raised $6.34M. The round was led by Oxford Investment Consultants, Parkwalk Advisors and IP Group, with participation from AlbionVC and Citigroup.

• Nooks, an AI sales assistant platform that automates dialing, prospecting, and coaching for reps, has raised $43M. The round was led by Kleiner Perkins, with participation from Tola Capital.

• Read AI, a startup developing AI tools to summarize meetings and conversations, has raised $50M. The round was led by Smash Capital, with participation from Madrona Venture Group and Goodwater Capital.

• Socket, a startup that provides tools to detect security vulnerabilities in open-source code, has raised $40M. The round was led by Abstract Ventures, with participation from Cooley, GTM Operators Network and Andreessen Horowitz.

• Spot AI, a startup that specializes in AI camera systems, has raised $31M. The round was led by Qualcomm Ventures, GSBackers and Gaingels, with participation from Cheyenne Partners, Calm Ventures, Redpoint Ventures, Bessemer Venture Partners, MVP Ventures, Scale Venture Partners and StepStone Group.

• Tennr, a healthcare AI startup developing a document reasoning model that can read, reason, and respond to paperwork, has raised $37M. The round was led by Lightspeed Ventures, with participation from Foundation Capital and Andreessen Horowitz.

Series C:

• Infinitus Systems, an AI platform specifically built to automate manual healthcare phone calls, has raised $51.5M. The round was led by Andreessen Horowitz, with participation from GV, Memorial Hermann, Coatue Management and Kleiner Perkins.

Series E:

• Melio, an accounts payable and receivable platform for small and medium sized businesses, has raised $150M at a $2B valuation. The round was led by Fiserv, with participation from Capital One Ventures, Shopify Ventures, Coatue Management, General Catalyst, Latitude Ventures, Accel, Bessemer Venture Partners, Frontline Ventures and Thrive Capital.

Later Stage:

• Sana, a Sweden-based company which specializes in applying AI to enterprise knowledge, has raised $55M at a $500M valuation. The round was led by New Enterprise Associates.

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Notorious Startup of the Week: Copy.ai

Go-to-market (“GTM”) is the lifeblood of every company. As companies scale, it becomes increasingly complex and difficult to reach the right customers with on-brand marketing when they are ready to buy. Companies create playbooks to optimize their sales and marketing processes, but these workflows are often manual and tedious. Enter Copy.ai. Copy.ai is building an AI-powered GTM platform that ingests unstructured data and orchestrates coordinated workflows. For this edition of Notorious, Copy.ai CMO Kyle Coleman shares Copy’s formula growing 3.5x in 8 months:

“Over the last eight months, Copy.ai has increased revenue by 260%, with October marking our fourth straight month of 20%+ ARR growth. During that same period, our ACVs have tripled and deal cycle times have been cut in half. This acceleration isn’t a fluke—it’s the result of a calculated master plan. A plan focused on building something bigger than just another piece of software. We’re creating the autonomous Go-to-Market AI platform—an evolving, intelligent system that gets stronger and smarter as more use cases are adopted.

Here’s how we did it: product vision, market positioning, and transformative pricing & packaging.

Initially, Copy.ai was known as a powerful tool to generate fast, high-quality copy, amassing over 17 million users. When GPT 4.0 dropped last year, we moved to the next phase of our master plan. Generative AI isn’t just about copy; it’s capable of automating entire workflows for go-to-market (GTM) teams. We had the product architecture—simple, scalable, deeply integrated. It was time to evolve. We pivoted from a chat app for copywriters to an end-to-end workflow automation platform purpose-built for GTM teams.

We quickly won some impressive enterprise customers—ServiceNow, Siemens—but “workflow automation” alone wasn’t moving the needle at the C-Suite level. We needed to strike a nerve with CMOs and CROs, addressing their most urgent and existential problems. In March, we sharpened our positioning and started evangelizing a new reality: Go-to-Market Bloat. This is the root cause of skyrocketing CACs and declining valuations. Our message was simple: if you don’t solve GTM Bloat, your company’s future is at risk. And the only weapon against it is an autonomous GTM platform powered by AI.

With this bold positioning, we were now speaking the C-Suite’s language, unlocking executive access earlier in the sales cycle. The problem was clear, but the solution needed a starting point. The prospect of a full-blown platform can seem daunting. So we engineered a targeted entry point—a wedge to get in and deliver immediate value.

We identified the highest-value use cases with the strongest market pull and designed seven targeted "wedge" packages—our Land SKUs in a classic Land & Expand strategy. Each package serves a specific executive-level problem, providing immediate ROI. And as companies adopt more SKUs, the real magic happens. Value compounds. The platform begins to operate as a true autonomous GTM flywheel—handling everything from prospecting to personalization, with intelligence that scales across the organization.

Our Solutions team ensured these wedges weren’t just packaged ideas but production-grade, hardened workflows. The pricing model is consumption-based, removing risk and fear of shelfware, while our value journey provides a clear path to expanding cross-functionally within the enterprise.

This isn’t just another SaaS product—our GTM AI platform is designed to autonomously and continuously learn and evolve as you unlock more use cases. For large, sophisticated enterprises, it’s not a matter of if you need this, it’s when. To stay competitive in a market where efficiency and intelligence are paramount, the ability to automate and scale your go-to-market strategy will determine whether you lead or follow.

The future is clear, and we’re excited to be at the forefront. The best days for Copy.ai are ahead, and we’re ready to power the GTM engine that will drive sustainable, enduring enterprise value for our customers. So excited, in fact, that we wrote the book on it. Notorious PLG readers get early access to the ebook and a free hardcover copy here: copy.ai/book

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango, Tome and Workmate.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

15 Biggest Stock Gainers (1 month):

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• ApertureData, a specialized database for multimodal data, has raised $8.25M. The round was led by TQ Ventures, with participation from WestWave Capital and Interwoven Ventures.

• Artisan AI, a startup aiming to replace traditional sales software with AI-powered virtual employees, has raised $11.5M. The round was led by Oliver Jung, with participation from HubSpot Ventures, Day One Ventures, Fellows Fund, Soma Capital, Mento VC, CoreNest, Y Combinator and Sequoia Scout.

• Aspect Build, a multi-language build and workflow management platform designed to code, review, test and build developer loops while navigating Bazel, has raised $3M. The round was led by FirstMark Capital.

• Avarra, an AI-avatar-based enterprise platform intended to train human salespeople, has raised $8M. The round was led by Lightspeed Management Company, with participation from GTMFund and FirstHand Alliance.

• BackOps AI, an AI-driven supply chain logistics and operations automation platform, has raised $2M. The round was led by Gradient Ventures, with participation from GV and 10vc.

• Billables, an AI-powered time tracking platform designed for lawyers, consultants and professional services, has raised $3.9M. The round was led by Wing VC, with participation from F7 Ventures, SignalFire, DarkMode Ventures and Alumni Ventures.

• Clerk Chat, an AI-powered conversational messaging platform for businesses, has raised $7M. The round was led by Race Capital, with participation from Soma Capital, Transpose Platform Management, Mento VC, AltaIR Capital and Hacker Fellowship Zero.

• Cove, a Palo Alto-based AI collaborative visual workspace, has raised $6M. The round was led by Sequoia Capital, with participation from Homebrew and Adverb Ventures.

• E2B, an open-source runtime for executing AI-generated code in secure cloud sandboxes, has raised $11.5M. The round was led by Decibel Partners, with participation from Kaya VC and Sunflower Capital.

• Early, a software testing platform designed to automate coding quality checking, has raised $5M. The round was led by Zeev Ventures, with participation from Dynamic Loop Capital.

• FullyRamped, an AI-powered sales simulation platform for organizations to onboard, train, and up-skill sales representatives, has raised $2.3M. The round was led by MaC Venture Capital, BoxGroup and NOMO Ventures, with participation from Greylock and Sequoia Capital.

• Infactory, a generative AI-based fact-checking search engine, has raised $4M at a $25M valuation. The round was led by Bee Partners, with participation from A16zScoutFund, Alumni Ventures and FJ Labs.

• Kapa.ai, a platform for creating LLM based chatbots that can answer developer questions about their product, has raised $3.2M. The round was led by Initialized Capital Management, with participation from Y Combinator.

• Keep, a startup that leverages AI to help ops teams manage and prioritize their alerts, has raised $2.5M. The round was led by Runa Capital, with participation from Firestreak Ventures.

• Kiva AI, an AI support company intended to develop specialized applications by employing human experts to label large datasets, has raised $7M. The round was led by CoinFund, with participation from Hashkey Group, PEER Venture Partners Protagonist.

• Reducto, a retrieval augmented generation platform designed for users to convert documents into chunks for LLMs, has raised $8.4M. The round was led by First Round Capital, with participation from Liquid 2 Ventures, BoxGroup, Y Combinator and SV Angel.

• Resolve AI, an AI software operations automation developer, has raised $35M. The round was led by Greylock, with participation from Unusual Ventures.

• Strella, a startup using AI to automate and accelerate customer research, has raised $4M. The round was led by Decibel Partners, with participation from Unusual Ventures.

• Tako, an AI search engine for data visualization, has raised $5.75M. The round was led by A* Capital and Abstract Ventures.

• Thread AI, a composable AI infrastructure platform intended to design, implement, and manage an organization's mission-critical workflows, has raised $6M. The round was led by Index Ventures, with participation from Greycroft.

• Vectorize, a platform that helps companies prepare and maintain their data for use in vector databases and large language models, has raised $3.55M at a $16.55M valuation. The round was led by True Ventures.

• Vieu, an AI-powered business network for enterprise sales, has raised $11M. The round was led by Trilogy Equity Partners, with participation from Incubate Fund US and Vela Partners.

• Zerve, a data science and AI development platform, has raised $7.74M. The round was led by Paladin Capital Group, with participation from Elkstone.

Series A:

• Autone, an AI-powered retail inventory management platform, has raised $17M. The round was led by General Catalyst, with participation from YCombinator, Speedinvest, Seedcamp, Motier, Financière Saint James and 2100 VC.

• Distributional, a startup building a platform to automate AI app and model testing, has raised $19M at a $90M valuation. The round was led by Two Sigma Ventures, with participation from NextEra Energy, Andreessen Horowitz, Operator Collective, Oregon Venture Fund, Essence Venture Capital and Alumni Ventures.

• DocJuris, an AI-powered contract negotiation software, has raised $8M at a $27M valuation. The round was led by Silverton Partners, with participation from Watertower Ventures, Surface Ventures and Seed Round Capital.

• Gladia, an audio intelligence API platform designed to extract, analyze, and understand data from sound, has raised $16M. The round was led by XAnge, with participation from XTX Ventures, Athletico Ventures, Roosh Ventures, Illuminate Financial Management, New Wave VC, Sequoia Capital, Cocoa Ventures, Soma Capital, Global Founders Capital, Gaingels, Mana Ventures and Motier Ventures.

• Herald, a digital infrastructure provider for commercial insurance, has raised $12M at a $53.5M valuation. The round was led by Lightspeed Venture Partners and Brewer Lane Ventures, with participation from Underscore VC and Afore Capital.

• Lightdash, an open-source business intelligence platform, has raised $11M at a $79M valuation. The round was led by Accel, with participation from Shopify Ventures, Operator Partners, Moonfire and Y Combinator.

• Noetica, an AI-powered software platform for benchmarking deal terms, has raised $22M. The round was led by Lightspeed Venture Partners, with participation from Thomson Reuters Ventures, Bling Capital, Flybridge Capital Partners, Company Ventures and The Legal Tech Fund.

• Numeric, an AI accounting automation platform, has raised $28M. The round was led by Menlo Ventures, with participation from Fifth Down Capital, Founders Fund, Access Industries, Long Journey Ventures, Friends & Family Capital, 8VC, Socii Capital and IVP.

• Omnea, an AI-based procurement orchestration and supplier risk management platform, has raised $20M. The round was led by Accel, with participation from First Round Capital and Point Nine Capital.

• Pydantic, an open-source data validation platform designed to validate data in Python using type hints, has raised $12.5M. The round was led by Sequoia Capital, with participation from Partech and Irregular Expressions.

• Qodo (fka CodiumAI), an AI-powered coding companion designed to enhance the software development cycle, has raised $40M. The round was led by Susa Ventures and Square Peg, with participation from Firestreak Ventures, ICON Continuity Fund, TLV Partners and Vine Ventures.

• Rogo, a secure enterprise AI platform for finance professionals, has raised $18.5M at an $80M valuation. The round was led by Khosla Ventures, with participation from AlleyCorp, ScOp Venture Capital, BoxGroup, Original Capital, Mantis VC and Alt Capital.

• Voyage AI, a startup building RAG tools to reduce AI hallucination, has raised $20M. The round was led by CRV, with participation from Wing VC, Conviction, Snowflake, Databricks, Pear VC, Tectonic Capital, Mayfield Fund and Fusion Fund.

Series B:

• 11x, a startup developing autonomous digital workers that automate Go-to-Market workflows, has raised $50M. The round was led by Andreessen Horowitz.

• Centaur Labs, a Boston-based health data annotation startup, has raised $16M. The round was led by SignalFire, with participation from Matrix, Accel, Susa, Omega, Y Combinator, Samsung Next and Alumni Ventures.

• Decagon, an AI customer support agents developer, has raised $65M. The round was led by Bain Capital Ventures, with participation from A* Capital, Accel, BOND Capital and ACME Capital.

• Galileo, a platform for enterprise GenAI evaluation and observability, has raised $45M. The round was led by Scale Venture Partners, with participation from Premji Invest.

• Numa, a startup that brings AI and automation to car dealerships, has raised $32M. Touring Capital and Mitsui led the round, with Costanoa Ventures, Threshold Ventures, and Gradient also participating.

• Poolside, a French developer of AI for software development, has raised $500M. Bain Capital Ventures led the round, and was joined by DST Global, StepStone Group, Schroders Capital, Premji Invest, BAM Elevate and B Capital.

• Port, a platform designed to centralize multiple dev tools and workflows in a single dashboard, has raised $35M. The round was led by Accel, with participation from Bessemer Venture Partners, Team8 and TLV Partners.

Series C:

• Crescendo, an augmented-AI customer experience (CX) platform, has raised $45M at a $500M valuation. The round was led by General Catalyst, with participation from Alorica and Celesta.

Series D:

• Suki, a technology company that provides AI voice solutions for healthcare, has raised $70M at a $500M valuation. The round was led by Hedosophia, with participation from Venrock, Flare Capital Partners, Breyer Capital, InHealth Ventures and March Capital.

Later Stage:

• OpenAI, creator of ChatGPT, has raised $6.6B in a funding round that values the company at $157B. The round was led by Thrive Capital, which invested around $1.3B; Microsoft, Nvidia, SoftBank, Khosla Ventures, Altimeter Capital, Fidelity and MGX also participated in the fundraising.

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AI Growing Faster than SaaS

Stripe CEO Patrick Collison recently shared a fascinating observation: “we analyzed the AI sector on Stripe, and found that not only are AI-native businesses being built in large numbers, but that they're actually growing meaningfully faster than the fastest-growing SaaS antecedents.”

Stripe pulled data on its 100 fastest growing AI customers and compared their revenue growth to 100 of the most promising SaaS companies from 2018. Some of Stripe’s AI customers include the hottest names in AI such as Anthropic, OpenAI, Mistral, GitHub and Midjourney.

The data found that AI startups took a median of 11 months to reach $1M of annualized revenue following first customer sale compared to nearly 15 months for the SaaS cohort.

Stripe’s Emily Sands shared a good insight that “unlike past generations of software companies, AI companies pay substantial compute costs out of the gates, so are under pressure to build monetization faster.”

Stripe also found that AI companies have been much more global in their first year or two than SaaS companies:

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango, Tome and Workmate.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

15 Biggest Stock Gainers (1 month):

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• Bounti, an AI-powered platform designed to boost sales team productivity by automating repetitive tasks, has raised $16M. The round was led by Google Ventures, with participation from Floodgate, Bloomberg Beta, Haystack, Octave Ventures and MS&AD.

• c/side, a security platform intended for assessing third-party scripts, has raised $6M. The round was led by Uncork Capital, with participation from Scribble Ventures, Roar Ventures, Mantis VC and Prime Set.

• Chai Discovery, a multi-modal foundation model for molecular structure prediction, has raised $30M at a $150M valuation. The round was led by Thrive Capital, with participation from OpenAI and Dimension.

• Convergence, a startup developing personal AI assistants that learn, adapt, and remember, has raised $11.86M at a $42.71 valuation. The round was led by Balderton Capital, with participation from Salesforce Ventures and Shopify.

• DryMerge, an event-driven workflow automation engine designed to help developers automate tasks and build complex workflows, has raised $2.2M. The round was led by GarageCapital, with participation from Goodwater Capital, Ritual Capital, Breakpoint Capital and Y Combinator.

• Fifth Dimension AI, an AI-powered property assistant designed for sorting through unstructured data, has raised $7M. The round was led by Speedinvest, with participation from Seedcamp and Anthemis.

• Letta, an AI platform for building stateful LLM applications, has raised $10M at a $70M valuation. The round was led by Felicis and Astasia Myers, with participation from Essence Venture Capital and Sunflower Capital Partners.

• Mako AI, a startup building generative AI associates for the private-equity industry, has raised $1.55M. The round was led by Khosla Ventures.

• OffDeal, an AI broker platform designed for buying and selling small businesses, has raised $4.7M. The round was led by Radical Ventures, with participation from Centre Street Partners and Rebel Fund.

• Protege, an AI training data platform, has raised $10M. The round was led by CRV, with participation from Bloomberg Beta, Flex Capital, Liquid 2 Ventures and SV Angel.

• Ren, an AI-powered relationship intelligence platform designed to help business leaders strengthen relationships, has raised $3.5M at a $14M valuation. The round was led by JLL Spark, with participation from ZoomInfo Technologies, Camber Creek and Contour Venture Partners.

• Scribenote, an AI-powered medical scribe designed to help veterinarians streamline their documentation process, has raised $8.2M. The round was led by Andreessen Horowitz, with participation from Inovia Capital and Velocity.

• SplxAI, a startup which aims to identify vulnerabilities in customer service chatbots, has raised $2M. The round was led by Inovo.vc, South Central Ventures and Runtime Ventures.

• Supermaven, an AI coding copilot, has raised $12M. The round was led by Bessemer Venture Partners.

Early Stage:

• Distyl, a startup applying generative AI to enterprise workflows, has raised $20M. The round was funded by Millennium Technology Value Partners and Coatue.

• Morph, a startup developing AI-centric infrastructure to support artificially intelligent software engineers, has raised $5.75M. The round was led by Khosla Ventures, with participation from Betaworks, Irregular Expressions, Koko Xsu and Roar Ventures.

• rep.ai, a startup aiming to transform online sales interactions through AI-powered “digital twin” technology, has raised $7.5M. The round was funded by Browder Capital, Gradient Ventures and m]x[v Capital.

• Vana, a decentralized platform designed to assert control over the data increasingly being used to train generative AI models, has raised $5M. The round was led by Coinbase Ventures, with participation from SCB 10X, Auros Ventures, MH Ventures, DeFiance Capital, Contango Digital Assets, GSR, BoxGroup and Symbolic Capital.

• World Labs, a company that is trying to make AI technology that can understand how the three-dimensional physical world works, has raised $230M at a $1B valuation. The round was led by Radical Ventures, Andreessen Horowitz and New Enterprise Associates, with participation from AMD Ventures, Intel Capital, NVentures, Adobe Ventures, Databricks Ventures and NVIDIA.

Series A:

• 11x, a startup developing autonomous digital workers that automate Go-to-Market workflows, has raised $24M. The round was led by Benchmark, with participation from Quiet Capital, SV Angel, Abstract Ventures, Lux Capital, Operator Partners, Visionaries, Activant, HubSpot Ventures, Project A, 20VC, 20Growth and 20Sales.

• DeepOpinion, a generative automation platform designed for creating enterprise-grade AI agent apps, has raised $12.21M. The round was led by Red River West and Alpha Intelligence Capital, with participation from Lunar Ventures and Stride.VC.

• DeltaStream, a real-time stream processing platform with streaming analytics and database features, has raised $15M at a $52.4M valuation. The round was funded by New Enterprise Associates, Galaxy Interactive and Sanabil Investments.

• fal, a developer focused platform for AI-generated audio, video, and images, has raised $23M. The $14M Series A was led by Kindred Ventures, with participation from Andreessen Horowitz and First Round Capital, and the $9M Seed round was led by Andreessen Horowitz, with participation from Village Global.

• Fathom, an AI notetaker software designed to transcribe online meetings, has raised $17M. The round was led by Telescope Partners.

• Harmonic, a mathematical reasoning engine designed to explore the frontiers of human understanding, has raised $75M at a $325M valuation. The round was led by Sequoia Capital and Blossom Capital, with participation from GreatPoint Ventures, DST Global, Rainfall Ventures, Index Ventures, TIBAS Ventures and Era Funds.

• Mercor, an AI-powered hiring platform designed to streamline the hiring process for both candidates and companies, has raised $30M at a $250M valuation. The round was led by Benchmark, with participation from General Catalyst.

• Nurix AI, a startup building custom AI agents for enterprise services like sales and customer support, has raised $27.5M. The round was led by General Catalyst and Accel, with participation from Meraki Labs.

• Zenlytic, a self-serve business intelligence platform, has raised $9M. The round was led by M13, with participation from Bain Capital Ventures, Primary Ventures, Company Ventures, Correlation Ventures and 14 Peaks.

Series B:

• Connectly.ai, a company that leverages AI to help businesses, like retailers and enterprise e-commerce leaders, sell their products and services across any messaging platform, has raised $20M at a $90M valuation. Alibaba led the round, with Unusual Ventures, Volpe Capital, RX Ventures and Falabella Ventures joining.

• Jus Mundi, a multilingual AI-powered search engine designed to make international law accessible and understandable, has raised $22.16M. The round was led by Acton Capital and True Global Ventures, with participation from C4 Ventures and FJ Labs.

• Orb, a company that builds and sells billing software, has raised $25M. The round was led by Mayfield, with Basecase, Greylock Partners, Menlo Ventures, Scribble Ventures, South Park Commons and Uncorrelated Ventures joining.

• Raycast, a command bar software designed to assist developers to control their tools, has raised $30M. The round was led by Atomico, with participation from Atlassian Ventures, Coatue Management, WiL, Accel and Y Combinator.

Series C:

• Percipient.ai, an intelligence analysis platform intended to deliver artificial intelligence products and services for national security missions, has raised $18.8M at a $322.1M valuation. The round was led by Celesta Capital.

• Supabase, a Postgres-centric developer platform, has raised $80M. The round was led by Peak XV, with Avra Capital, Coatue, Felicis and Y Combinator also participating.

• Superb AI, a startup developing a suite of AI training data prep and verification tools, has raised $10.12M. The round was led by Doosan Investment, and participation from KT Investment, Premier Partners, Kakao Investment, Samsung NEXT Ventures and Hyundai Motors Group.

Series E:

• Glean, a company that is trying to build “Google for Work”, has raised $260M at a $4.6B valuation. The round was co-led by Altimeter Capital and DST Global, with participation from Coatue Management, SoftBank Investment Advisers, Lightspeed Ventures, Kleiner Perkins, General Catalyst, Sequoia Capital, ICONIQ Growth, IVP, Craft Ventures and Sapphire Ventures.

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Notorious Startup of the Week: Artisan

The current workforce wakes up to manual tasks that they hate every single day. While automation software has been quietly reshaping our work landscape, the explosion of AI onto the scene means a radical redefinition of human roles in the professional world.

There are many jobs that consist of manual tasks that can be replaced entirely – SDRs, copywriters, customer support specialists.

Enter Artisan. They’re one of the fastest growing early-stage startups in the GTM ecosystem. Founded in 2023, they’ve participated in Y Combinator and raised over $7.5M in seed funding from investors including Y Combinator, BOND Capital and Soma Capital.

They’re on the cutting edge of revolutionizing the future of work, creating a team of AI employees called Artisans that can automate entire job functions. They’re starting with sales, before moving into marketing, customer success, and other GTM verticals.

They’re fast on the heels of existing incumbents in the sales SaaS space, including Apollo and Outreach, as Artisan aims to replace every single outbound sales tool you need.

If that wasn’t enough, their product growth is currently through the roof. In the span of two months, they’ve closed 700K ARR in contract value.

 “We’re relentlessly focused on creating the best and most automated user experience in the sales space,” says 22-year-old CEO Jaspar Carmichael-Jack. “For us, product comes before everything else. That's how we'll build a generational company.”

But this success hasn’t been easy – it’s been a road of learnings for them to achieve the growth they're experiencing right now. Enjoy this special blog post from Jaspar:

Starting with PLG

“When we launched our beta product in February, we started with a self-serve model that everyone could access. We thought it would be the surest path to growth and that our users would naturally have a great experience on the platform by onboarding themselves. We had about 300-400 users by the end of April, but it quickly became obvious it wasn’t the right approach for us. People were signing up and falling through the net. Our platform required quite a lot of set up that was a bottleneck for most people, without the right support. 

But most importantly, what we realized was that outbound is a hard game. So many factors have to align in order for users to be successful – targeting the right people at the right time, with an in-depth level of personalization. This is something that we knew how to do well, but the average user would struggle with.

Transitioning to sales-led

We switched to a sales-led approach in May and that’s when our growth really took off.

We closed 700K ARR in 2 months.

We’ve built out our sales team and hired the best AEs who give custom demos to every inbound lead that comes in. This way, we’re able to answer questions and capture user needs much better than we were before. We have a direct line of sight into what people are looking for.

As for our product, we've been able to drastically increase the volume of outbound we do per user, do one-on-one white glove onboarding sessions, and provide people with a Customer Success Manager that guides users on how to optimize their campaigns.

We’re also able to ensure that we filter out unqualified leads, who would churn if using our platform.

50 Inbounds a Day

After we built a sales approach that catapulted our growth, we began building an inbound machine to generate us more leads and capture revenue.

Since then, we’ve tapped into a few key B2B growth channels that get us 50+ leads per day.

Here’s a breakdown:

Email

• One of the best parts of creating our AI BDR Ava is that we can use her ourselves! 

• Although it can be notoriously difficult to reach people’s inboxes and get them to respond, building our product has taught us the best practices for email outbound.

• Over the past few months, we've sent hundreds of thousands of emails, continuously refining our approach. 

Organic Search

• Organic search is our most efficient channel, generating the highest percentage of leads (44%) from just 26% of site visits. It has the second-highest lead conversion rate at 2.7% and, importantly, zero variable cost per lead. 

• SEO is an extremely valuable channel, as potential customers use search engines at the moment of intent. 

• Ranking high in Google searches allows us to capture users when they're actively looking to buy or comparing tools.

Organic Social

• LinkedIn is our main platform, as it’s where we can most effectively reach our target audience of startup CEOs and sales decision-makers. 

• We're also expanding our presence on X, Reddit, Instagram, TikTok, and YouTube. 

• Our most successful posts have a strong hook that convinces people to click ‘see more’.

Building the next Industrial Revolution

What’s on our immediate roadmap is making the best outbound AI SDR on the market. It’s a crowded space, but we’re moving fast to build the most innovative features that will give us a strong competitive edge. Once we’ve succeeded in making Ava the most successful AI SDR, then we’ll start building out the rest of our Artisans, including an Inbound Sales Artisan who can replace Chili Piper in automated lead qualification and meeting booking.

This is certain – we’re not afraid of competition and we’ll do whatever it takes to succeed in our mission to automate the work people hate, so that people can focus on the work they love.”

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango, Tome and Workmate.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

15 Biggest Stock Gainers (1 month):

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• All Hands AI, a startup building model-agnostic open-source AI agents for developers, has raised $5M. The round was led by Menlo Ventures, with participation from Rebellion Ventures, Pillar VC and Betaworks.

• Fastn, a no-code/low-code platform designed to integrate and orchestrate multiple data sources into a unified API, has raised $2.5M. The round was led by Antler and LiveOak Ventures.

Early Stage:

• Safe Superintelligence (SSI), an AI research lab co-founded by former OpenAI chief scientist Ilya Sutskever, has raised $1B at a $5B valuation. The round was funded by NFDG (an investment partnership run by Nat Friedman and SSI CEO Daniel Gross), a16z, Sequoia, DST Global, and SV Angel.

Series A:

• Brellium, a clinician-validated AI audit system designed to help automate medical chart review, has raised an undisclosed amount from First Round Capital.

• Mintlify, a platform designed to assist developers with writing software documentation, has raised $18.5M. The round was led by Andreessen Horowitz, with participation from Bain Capital Ventures and Y Combinator.

• Sakana AI, a Tokyo-based AI research lab building a foundation model focused on nature-inspired intelligence, has raised $137M at a $1.11B valuation. The round was led by Lux Capital, Khosla Ventures and New Enterprise Associates, with participation from Nvidia.

Series B:

• Mangomint, an operations automation platform designed to offer brand development and booking services for salons and spas, has raised $47M. The round was led by Altos Ventures and SaaStr, with participation from OpenView Venture Partners.

• You.com, a company that makes an AI-powered search engine and productivity tools, has raised $50M at a $374.09M valuation. The round was led by Georgian, with participation from Salesforce Ventures, SoftBank Ventures Asia, Nvidia, DuckDuckGo, Elevation Capital, MicroVentures, Untapped Ventures, Day One Ventures and Empty Set Group.

Series D:

• Oyster, a payroll and HR platform for distributed workforces, has raised $59M at a $1.2B valuation. The round was led by Silver Lake Waterman, with participation from Endeavor Catalyst, Stripes, Georgian, G2 Venture Partners and Emergence.

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Notorious Startup of the Week: Clay

If you’ve experienced working with manual outbound campaigns, you know the struggle of creating prospect lists and drafting outreach from scratch. But Clay has a better way: they’ve combined over 75 data providers in a single tool to fully automate data enrichment and personalized outreach, which can save weeks or even months of work for busy Go-To-Market (GTM) teams. 

Clay is experiencing one of those rare moments that startup teams dream of: They've grown 10x Year-over-Year (YoY) and now have tens of thousands of users as well as thousands of paying customers like Verkada, Anthropic, and Intercom. When Bruno Estrella joined Clay’s Growth Marketing team this year, his mission was clear: devise a strategy to propel Clay into exponential growth. Before joining Clay, Estrella was the Director of Growth Marketing at Webflow. During his nearly five years there, the company grew 20x and raised over $300M in funding. 

“I learned firsthand that for a company to achieve flywheel growth, you need a growth strategy rooted in understanding your business, product, and audience,” Estrella explains. 

In this post, we’ll walk through Estrella’s process for assessing his initial strategic bets at Clay.

Reflect on growth in the context of your business

As Clay set off to determine their core growth bets, they started with a framework often referred to as “The Four Fits,” or the “Market/Product/Channel/Model Fit Framework,” which was designed by Brian Balfour, the founder of Reforge.

This framework encourages businesses to think beyond product-market fit by ensuring that your product, market, channels, and monetization models are all in alignment during every phase of your business’ growth. 

Let’s take a closer look at the four pillars of this framework:

1. Model-channel fit: The context of your business model will inform which acquisition channels you choose. For example, if your business model involves selling a high-priced direct-to-consumer product, Google Ads may not be the most effective channel.

2. Product-channel fit: Your product needs to fit the characteristics of your ideal acquisition channels. For instance, would your product benefit from organic channels, like social media and SEO, or from paid channels like paid social and search ads?

3. Model-market fit: The number of customers in your market will influence your business model. If you aim to build a centi-million dollar business and your market only has a thousand customers, your business model must rely on large enterprise deals.

4. Product-market fit: Pinpoint a thriving market, and position your product in a way that effectively addresses real pain points.

Consider these four pillars as we move through the rest of the post, using Clay as an example. These pillars will also serve as a baseline for you as you work your way through your own growth strategies.

Ask these 5 questions to assess your growth bets

Clay’s goal for the foreseeable future is to increase self-serve user acquisition. To determine how they could reach this goal, Clay’s team turned to four key questions inspired by the framework above.

1. What’s your business model? 

Clay leverages a self-serve, product-led growth (PLG) strategy: They offer users a two-week free trial with access to all of Clay’s advanced features, CRM integrations, and high-usage thresholds. This reverse trial strategy exposes users to Clay’s full capabilities without even needing to input a credit card number, thereby simplifying the joining process and increasing the likelihood of conversion. 

After the trial, Clay converts users to one of four features-based credit tiers. Clay’s pricing ranges from  $0-800/month, with the first paid tier at $149/month. These tiers are designed to fit comfortably within the budgets of small and mid-sized businesses. Clay’s unique pricing model speaks directly to one of their value propositions: pay only for what you need. 

This model places Clay in stark contrast with large data providers, which often face barriers to conversion due to lack of self-serve motions, opaque pricing, and high friction during onboarding and adoption. 

2. What are your ideal user acquisition channels? 

Since Clay’s model relies on low-friction, self-serve trials, it was crucial to leverage acquisition channels with a high volume of users who would be interested in trying Clay. The best free channels for that? Social media and SEO. The best paid channels? Search and social ads. 

3. Based on your product’s characteristics, what are your ideal user channels? 

Clay’s product is highly flexible; users can use Clay to build workflows that were previously only accessible to extremely sophisticated GTM teams. For instance, Clay’s product makes waterfall data enrichment, data normalization, and CRM syncing available to everyone. Building these workflows can spark a sense of pride and ownership among users, similar to creating a beautiful site in Webflow or an impressive app in Airtable. This pride makes Clay a good fit for social channels like LinkedIn, where people want to position themselves as experts in order to amplify their brands.

Furthermore, for companies who are looking to level up their SEO, Clay offers several valuable data points that they can use to optimize their strategies. 

4. What’s your current market, and does it fit your business model?

Clay targets two key market segments: Freelancers and marketing agencies, who use Clay to build outbound campaigns faster, and in-house Growth teams, who use Clay to power their data enrichment and GTM motions. 

These targets fit Clay’s self-serve PLG business model nicely, as freelancers and marketing agencies can quickly onboard and find value, while in-house growth teams can evangelize the value of Clay. 

Determine the best ways to tap into your target market

By tackling the questions above, Clay aligned on social media and SEO as core channels for their business model, product, and market. To understand how they could most effectively leverage these channels, they looked at their current growth drivers, including word-of-mouth marketing, user-generated content (UGC), and referrals from agencies and service providers. 

Word-of-mouth marketing

Word-of-mouth marketing is Clay’s primary growth driver. Most word-of-mouth marketing follows a simple process that can be depicted in just four steps:

1. Sign up: Users sign up for a free account. 

2. Experience product value: Users can appreciate the product’s value.

3. Socialize to others: Users become relative experts and tell their friends about the product. 

4. Gain recognition: Users gain recognition for successfully using the product. 

As users complete the final steps of this word-of-mouth growth loop, the cycle starts all over again.

User-generated content (UGC)

UGC is Clay’s second major growth driver. It follows a similar process as word-of-mouth marketing, with only one key difference: content creation. 

1. Sign up: Users sign up for a free account. 

2. Experience product value: Users can appreciate the product’s value.

3. Create content: Users share outputs they’ve created using the product.

4. Gain recognition: Users gain recognition as innovators. 

As more and more content is generated about Clay, more new users will join in the loop, generate their own content, and be recognized in their own right. 

Referrals

Clay’s third most effective growth driver is referrals from agencies and service providers to in-house marketing teams. 

When service providers demonstrate Clay’s capabilities to in-house teams, those in-house teams give the product a try, and eventually start using it at their own companies. Think of it as a double growth loop: Agencies and service providers introduce in-house teams to the tool, sparking a new cycle of users who show the product to even more new users. 

Combine your business model, product, and market to create the ultimate growth strategy

When Clay shaped their growth bets, they wanted to optimize the ways in which they were already growing. They did this by amplifying word-of-mouth marketing, UGC, and referrals across their social media channels. They also aimed to scale their SEO strategy to increase their top-of-funnel (TOFU) user acquisition for their free trials. 

Social media

Clay wanted to tap into service providers who were interested in showcasing their wins to attract new clients. By creating content about their capabilities with Clay, these service providers could gain recognition while also evangelizing about Clay. This method is central to Clay’s growth, as it aligns with how service providers behave on social channels. 

SEO

Clay’s unique product and business model allow them to leverage data for SEO acquisition motions. They’re currently working on ways to deepen and scale this strategy. 

TL;DR: How can you assess your growth bets? 

Throughout this blog, we used Clay as an example to help you understand your existing growth model, and where you can place your big bets. 

You can start by asking the following fundamental questions: 

1. What’s your business model? 

2. Based on your business model, what are your ideal user acquisition channels?

3. Based on your product, what are your ideal user channels? 

4. What’s your current market, and does it fit your business model? 

Whether you’re scaling up your growth strategy or considering expansion into new markets, this framework will serve as a set of guardrails for every step of your journey.

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango and Tome.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

15 Biggest Stock Gainers (1 month):

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• Black Forest Labs, a developer of an open-source AI image generation model, has raised $31M. The round was led by Andreessen Horowitz.

• Hedra., an AI video creation platform, has raised $10M. The round was led by Index Ventures, Abstract Ventures and Andreessen Horowitz, with participation from Outset Capital.

• Not Diamond, a developer of network infrastructures designed to help developers dynamically route queries from their application to the AI models, has raised $2.3M. The round was led by Defy Partners Management, with participation from Karman Ventures, VitalStage Ventures, 640 Oxford and Inovia Capital.

• Tezi, a startup building an AI agent for hiring managers to automate the recruiting workflow, has raised $9M. The round was led by 8VC, with participation from Audacious Ventures, Liquid 2 Ventures, Afore Capital, South Park Commons and Prime Set.

• vals.ai, a third-party review system designed for vetting the performance of AI in areas like accounting, law and finance, has raised $5M. The round was led by Bloomberg Beta, Sequoia, and 8VC, with participation from Pear.

Series A:

• Credo AI, an AI governance platform designed to automate artificial intelligence oversight and risk management, has raised $21M at a $103M valuation. The round was led by Mozilla Ventures, FPV Ventures and CrimsoNox Capital, with participation from Booz Allen Ventures, Sands Capital, Decibel Partners and AI Fund.

• Ema, a generative AI company creating the universal employee of the future, has raised $36M. The round was led by Accel Partners and Section 32 , with participation from Prosus Ventures, Hitachi Ventures, Sozo Ventures, Wipro Ventures, SCB10X, Frontier Capital and Colle Capital.

Series B:

• Checkly, a Germany-based provider of synthetic monitoring powered by Monitoring as Code (MaC) and Playwright, has raised $20M. The round was led by Balderton Capiital, with participation from existing Accel and CRV.

• Protect AI, a security and artificial intelligence startup, has raised $60M at a $400M valuation. The round was led by Evolution Equity Partners, with participation from Salesforce Ventures, Samsung Electronics, 01 Advisors, Acrew Capital, Boldstart Ventures, Knollwood Capital, Pelion Venture Partners and StepStone Group.

Series C:

• Gradient AI, a provider of artificial intelligence solutions for the insurance industry, has raised $56.1M. The round was led by Centana Growth Partners, with participation from MassMutual Ventures, Sandbox Industries, Forté Ventures, Wavemaker Three-Sixty Health and Plug and Play Tech Center.

Later Stage:

• DeepScribe, an AI-based medical scribe technology designed to automate medical documentation, has raised $60M. The round was funded by undisclosed investors.

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Focus to Find PMF

Many founders I speak with aim to go horizontal, meaning they want to serve a wide range of customer types with various use cases. They often draw inspiration from companies like Airtable and Zapier. The allure is understandable—large markets, diverse customers, and products used daily, leading to multi-billion dollar valuations.

However, the hidden truth about horizontal companies is that a small handful of use cases, driven by one or two key personas, account for over 75%+ of their revenue. For instance, Airtable’s core users are marketing teams, while Zapier's primary use cases are sales workflows.

I admire Bobby’s post above. Bobby is a talented founder who is building Equals, backed by A16Z and Craft. Equals has ambitious plans to build a next-gen spreadsheet and initially pursued a horizontal strategy. Through learned experience, Bobby is convinced that focus leads to success. He is now sharing his insights with the founder community, urging them to narrow their focus to achieve repeatable and scalable growth.

What does it mean to focus? Founders can concentrate on a few areas to find Product-Market Fit (PMF):

• Focus on a specific company type and size.

• Focus on a particular persona (e.g., Head of Marketing) within that company.

• Focus on this persona’s most pressing pain points and problems.

• Tailor the product positioning to catch the attention of this persona.

• Design the product experience to highlight features that address the most urgent pain points. For every new feature you add, remove 1.5 old features. Check out this great interview with Figma CEO (12.5B valuation) on the importance of simplifying the product as much as possible. “The more you add, the more complex it gets, the worse it gets.”

• Align the team around a specific, well-defined go-to-market (GTM) strategy.

Be honest with yourself and your team—are you focused enough? For most early-stage startups, the answer is likely no.

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango and Tome.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

15 Biggest Stock Gainers (1 month):

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• Gumloop, a no-code platform designed for automating workflows with AI, has raised $3.1M. The round was led by First Round Capital, with participation from WndrCo, Theory Forge Ventures, Liquid 2 Ventures, Ludlow Ventures and Y Combinator.

• Noded AI, a developer of note-taking and task management software, has raised $4M. The round was led by Boldstart Ventures, with participation from Bessemer Venture Partners, 20VC and First Hand Ventures.

• Promptfoo, a CLI and library for evaluating and red-teaming LLM apps, has raised $5M. The round was led by Andreessen Horowitz.

• Rift, a sales platform focusing on automating operational sales work, has raised $5M. The round was led by Sequoia, with participation from Y Combinator and Soma Capital.

• Cypris, a NYC-based provider of an AI research platform for R&D teams, has raised $5.3M. The round was led by Vocap Partners, with participation from Activate Venture Partners and Blue Tree Venture Capital.

Series A:

• Docket, a startup aiming to transform revenue enablement through AI-driven solutions, has raised $15M. The round was led by Mayfield and Foundation Capital.

• Lakera, a startup that protects enterprises from LLM vulnerabilities, has raised $20M. The round was led by Atomico, with participation from Citi Ventures, Dropbox Ventures and Redalpine.

• Momentum, a customer intelligence platform that enables enterprise listening and automation, has raised $13M at a $36M valuation. The round was led by FirstMark Capital, with participation from Stage 2 Capital, Basis Set Ventures and Leadout Capital.

• TigerBeetle, an open-source database engineered for financial online transaction processing, has raised $24M at a valuation of ~$100M. The round was led by Spark Capital, with participation from Amplify Partners and Coil.

• Uplimit, an AI enterprise learning company, has raised $11M at a $56M valuation. The round was led by Salesforce Ventures, with participation from GSV Ventures, Greylock, Cowboy Ventures, Translink Capital, Workday Ventures and Conviction.

Series B:

• Pearl, one of only three startups that has an FDA clearance to use AI to assist dentists make accurate diagnoses, has raised $58M. The round was led by Left Lane Capital, with participation from Smash Capital, Alpha Partners, Craft Ventures and Neotribe Ventures.

• QA Wolf, a platform that makes QA for mobile and web apps easier by automating aspects of creating and running tests, has raised $36M. The round was led by Scale Venture Partners, with participation from Threshold Ventures, Ventureforgood, Inspired Capital and Notation Capital.

Series C:

• Chainguard, an open-source security startup, has raised $140M at a $1.09B valuation. The round was led by Redpoint Ventures, Lightspeed Venture Partners, and IVP, with Amplify, Mantis VC, Sequoia Capital and Spark Capital also participating.

• Harvey, a startup building an AI-powered copilot for lawyers, has raised $100M at a $1.5B valuation. The round was led by GV, with OpenAI Startup Fund, Sequoia Capital, Kleiner Perkins and SV Angel participating.

• Level AI, a startup that offers a suite of AI-powered tools to automate various customer service tasks, has raised a $39.4M. The round was led by Adams Street Partners, with participation from Cross Creek, Brightloop, Battery Ventures and Eniac Ventures.

Series D:

• Cohere, a generative AI startup co-founded by ex-Google researchers, has raised $500M at a $5.5B valuation. The round was led by Public Sector Pension Investment Board, with participation from Nvidia, Salesforce Ventures, Oracle, Cisco Investments, Fujitsu, AMD Ventures, Export Development Canada, IronArc Ventures, Gauntlet Ventures, Strategxy Ventures and Thomvest Ventures.

Series F:

• Clio, a Canadian software company that aims to help law practices run more efficiently with its cloud-based technology, has raised $900M at a $3B valuation. New Enterprise Associates led the round, with participation from JMI Equity, Sixth Street Partners, CapitalG, Tidemark, Ebridge Ventures, TCV and Goldman Sachs Asset Management.

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Notorious Startup of the Week: 11x

11x is a trailblazing startup that is growing very fast! It is pioneering a new category of AI-powered applications that is selling outcome-based work. 11x is building an AI-powered SDR (sales development rep). GTM teams can augment their SDR teams with Alice, 11x’s AI rep. Alice will research potential target accounts, draft personalized and targeted emails, and then engage in back-and-forth Q&A with the objective of scheduling a qualified meeting for a sales rep. Alice is outperforming humans in many cases. There is infinite demand for more qualified meetings. We have a special edition today as 11x CEO and Founder Hasan Sukkar takes us behind the scenes of how they are building a powerful growth flywheel. Stay tuned for some big announcements from 11x in the near term! Enjoy:

11x’s Powerful Growth Flywheel

When we founded 11x, we had a simple yet audacious dream. We didn’t want to just create a tool that would enhance productivity. We envisaged a world of digital workers, capable of filling roles end-to-end and delivering work outcomes. Fast forward to today, and we're witnessing the fruits of that vision. We're growing at an improbable pace – nearly 50% month-over-month since the beginning of the year. But here's the kicker: the engine behind this growth isn't a massive sales team or a huge marketing budget. It's Alice, our own AI-powered Sales Development Representative (SDR).

This story isn't just about growth in numbers. It's about the emergence of a powerful AI growth flywheel that's redefining how B2B companies can scale. We're using our product to grow, our product helps customers grow, and we grow as our customers grow. It's a virtuous cycle that's propelling us forward at an unprecedented rate.

But, before we dive into the mechanics of this flywheel, let's rewind a bit and set the stage.

Alice is an AI Sales Rep. She automates the BDR/SDR process in an end-to-end, autonomous, and scalable way. Imagine having an AI sales rep who works 24/7, learns from all interactions, and never sleeps. The exciting thing about this product is that we can use it to grow with no real human-labor bottlenecks. Alice is relentless.

There are some key principles that helped us grow - and some key learnings:

1. Work vs software: Alice is a Digital Worker, meant to operate on autopilot and at scale, in a self improving way. This principle underpins how we build product, how our customers buy product, and how we service our customers. One of our big early learnings - people don’t want to buy tools for reps, they want to buy an actual AI rep that does the work and delivers outcomes.

2. Growth flywheel: Relying on our product for growth forces us to be incredibly product focused. As Alice gets smarter, we grow faster: 

1. We use Alice to generate leads and meetings for 11x.

2. This usage provides us with real-world data and insights to improve Alice.

3. As Alice improves, she generates better results for us and our customers.

4. Better results lead to faster growth and more customers.

5. More customers mean more data and use cases to further refine Alice.

3. Getting creative:  One of the challenges of automation is maintaining creativity – a crucial element in sales. We've tackled this head-on by baking creative playbooks into Alice's repertoire. Our most successful experiment? The meme strategy.

We began by testing typical follow-up formats: sharing case studies, additional research, confirming interest, and offering freebies. These worked well, but we wanted to push the envelope. So, we tasked Alice with being more creative than traditional SDRs, leading to experiments with images and GIFs in follow-up emails.

The results were staggering. Not only did this strategy deliver higher response rates in our outbound sequences, but it also led to a 35% response rate when used to re-engage cold pipeline prospects. Here's an example of a meme Alice might use:

This approach breaks through the noise of typical sales outreach, catching prospects off guard (in a good way) and sparking genuine conversations.

Lessons:

1. Focusing on ideal customers in such a massive TAM:

We started with a focus on SMB customers, and had a self-serve motion. We quickly learned that our best and most successful customers are sophisticated sales organisations with clear PMF and ability to benefit from scale, automation, and complex workflows/use cases. Since then, we’ve been focused on mid market and enterprise customers which are benefitting tremendously from Alice.

2. AI reliability:

Operating an autonomous employee comes with challenges. How do you make sure Alice is constrained, verticalized, and trained on best practices? We invested a lot of time in building guardrails that govern how Alice operates autonomously at scale.

3. Scaling at the right pace:

We received ten thousand inbound demo requests in the last 10 months, since launching Alice. The market demand is extremely high. That said, we are obsessed with delivering exceptional experiences for our customers. We are still strongly gating growth, despite being one of the world’s fastest growing companies in 2024. 

Going ahead:

We are big believers in the Compound startup model, publicized by Rippling - we plan to launch a variety of adjacent Digital Workers before the end of the year, enabling autonomous GTM functions - across channels, modalities, and use cases. Our goal is to create the AI GTM team.

We will be launching an AI Voice product that automates outbound and inbound SDR calling capabilities and can handle 10-15 minute conversations with SOTA latency by the mid of August - alongside a big exciting announcement.

Reflections on the Future of AI in Sales

As we continue to push the boundaries of what's possible with AI in sales, we're constantly amazed by the potential. The AI growth flywheel we've created with Alice is just the beginning. We're not just building a product; we're pioneering a new way of thinking about work, sales, and business growth.

The future of sales isn't about replacing humans with robots. It's about creating crucial and complimentary relationships between human creativity and AI efficiency. It's about freeing up human talent to focus on high-value, strategic activities while AI handles the repetitive, time-consuming tasks that have traditionally bogged down sales teams.

As we look ahead, we're excited about the possibilities. We're committed to continuing our "technically fearless" approach, pushing the boundaries of what AI can do in the world of sales and beyond. 

For other founders and teams working on AI startups, my advice is this: don't be afraid to use your own product in creative ways. The insights you'll gain are invaluable, and the alignment it creates between your team and your customers is powerful.

The future of work is being written right now, and AI is holding the pen. At 11x, we're thrilled to be part of this story, and we can't wait to see what the next chapter holds.

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango and Tome.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Great: 10%

• Good: 5%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

15 Biggest Stock Gainers (1 month):

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• EdgeRunner AI, a generative AI platform designed to run on edge devices, has raised $5.5M. The round was led by Four Rivers Group, with participation from Madrona Venture Group.

• Fibr, an AI personalization platform, has raised $2M. The round was led by Accel, with participation from Sprint VC and 2 a.m. Ventures.

• Lemonado, a no-code platform intended to help non-developers create custom business applications, has raised $1.4M. The round was led by Node Ventures.

Early Stage:

• World Labs, an AI company started by Stanford University’s artificial intelligence leader Fei-Fei Li, has raised ~$100M at a $1B valuation. Andreessen Horowitz and Radical Ventures participated in the round.

Series A:

• Adaptive, a provider of workflow automation for construction financial management, has raised $19M at a $70M valuation. Emergence Capital led the round, and was joined by a16z, Definition, Exponent, 3kvc and Box Group.

• Anysphere, an applied research lab building productive human-AI systems, has raised $60M at a $400M valuation. The round was funded by Andreessen Horowitz.

• Arcee.ai, a domain-adapted language model system designed to enhance the AI landscape for businesses, has raised $24M. The round was led by Emergence, with participation from Centre Street Partners, Long Journey Ventures, Flybridge Capital Partners and Arcadia Capital.

• Exa, an AI-powered search engine designed to perform web searches at a large scale, has raised $17M. The round was led by Lightspeed Venture Partners, with participation from WndrCo, NVentures and Y Combinator.

• Leya, an AI-powered workspace designed for law firms and legal professionals, has raised $25M. The round was led by Redpoint Ventures, with participation from Benchmark Capital, Wayfinder Ventures, Alt Capital and Y Combinator.

• Shaped, an AI recommendation and search platform for marketplaces, e-commerce, and content companies, has raised $8M. The round was led by Madrona Venture Group, with participation from Y Combinator.

• Thoughtful, an AI operating system for healthcare RCM teams, has raised $20M. The round was led by Drive Capital, with participation from TriplePoint Capital.

Series B:

• Hercules, a startup that develops AI software for law firms and large enterprises, has raised $26.1M at a $56.1M valuation. The round was led by Streamlined Ventures, with participation from Thomson Reuters Ventures, PROOF, Davidovs Venture Collective, Decart Ventures, Network VC, Evolution VC, Alumni Ventures, Vision Capital Group and Hybridge Capital Management.

Series D:

• Groq, an AI interface technology designed to address the industry's demands of computing speed, quality, and energy efficiency, has raised $300M at a $2.5B valuation. The round was led by BlackRock, with participation from IronArc Ventures.

• Kanji, a company that is helping IT manage the growing list of Apple devices inside an organization in a modern and streamlined way, has raised $100M at an $850M valuation. General Catalyst funded the round.

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OpenAI’s Revenue Breakdown (A Closer Look)

Recently, it was reported that OpenAI’s annualized revenue is approaching $3.4 billion, doubling from just six months ago. This remarkable growth trajectory highlights the increasing demand for OpenAI's innovative products. Based on recent estimates, here is a breakdown of OpenAI's revenue streams:

• 55% from Consumer-facing ChatGPT Subscriptions: Priced at $20 per month, these subscriptions form the largest revenue bucket.

• 8% from ChatGPT Teams: At $25 per month, this tier caters to collaborative use cases in smaller teams.

• 21% from ChatGPT Enterprise: This premium offering, costing $50 per month, serves larger organizations with advanced needs.

• 15% from API Sales: Businesses and developers utilize OpenAI’s API to build applications on top of its models.

Approximately 85% of OpenAI’s revenue is derived from its ChatGPT product. This significant reliance on a single product line is both a strength and a potential risk. The API business, while currently a smaller portion of the overall revenue, is arguably the most promising. It offers a stickier revenue stream with significant expansion potential as developers and businesses continue to build and scale their applications using OpenAI’s models. This contrasts with the consumer-facing chat product, which may experience higher churn rates. For comparison, Netflix and Spotify have annual churn rates of around 20-25% and 30%, respectively.

Analyzing Google Trends for chatgpt.com, there has been a noticeable increase in interest over the past few months. SimilarWeb’s traffic analysis corroborates this, showing a robust 14% month-over-month growth in web traffic to chatgpt.com. This suggests a sustained and growing user interest in ChatGPT.

Despite its current success, maintaining the $20/month price point in the face of increasing competition might be challenging. Competitors could undercut prices to attract users, potentially affecting OpenAI’s subscription base. It will be fascinating to observe how OpenAI navigates this competitive landscape and whether it can sustain its pricing strategy.

Overall, while ChatGPT subscriptions currently dominate OpenAI's revenue, the API business holds substantial promise for future growth and stability. The evolving market dynamics and user trends will be critical factors in shaping OpenAI’s continued success.

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango and Tome.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Freemium (Self Serve):

  • Great: 7%

  • Good: 4%

• Freemium (Sales Assist):

  • Great: 12%

  • Good: 6%

• Free Trial:

  • Great: 15%

  • Good: 8%

• Reverse Trial:

  • Great: 15%

  • Good: 8%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

15 Biggest Stock Gainers (1 month):

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• Ario, an AI-powered assistant for parents, has raised $16M. The round was led by Floodgate, with participation from Wing VC, Bain Capital Ventures and Moxxie Ventures.

• Inventive, a startup building embedded AI for SaaS products, has raised $6.5M. The round was led by Wing VC, with participation from Tokyo Black.

• Browserbase, a browser automation platform designed to run, manage, and monitor browser automation scripts, has raised $6.5M. The round was led by Kleiner Perkins, with participation from Base Case Capital and AI Grant.

• CuspAI, a startup that is building an AI-driven search engine for new materials, has raised $30M. The round was led by Hoxton Ventures, with participation from Basis Set Ventures and Lightspeed Venture Partners.

• Day.ai, an AI-powered conversation intelligence platform designed to offer customer relationship management, has raised $4M. The round was led by Sequoia Capital.

• Emergence, a company that claims to be building an “agent-based” system that can perform many of the tasks typically handled by knowledge workers, has emerged from stealth with $97M. Learn Capital provided the funding.

• EvolutionaryScale, a startup building AI models that can generate novel proteins for scientific research, has raised $142M. The round was led by Nat Friedman, Daniel Gross and Lux Capital, with participation from Amazon and Nventures.

• Greptile, a startup that allows engineers to use natural language to index and search large codebases, has raised $4.1M. The round was led by Initialized Capital Management, with participation from Y Combinator.

• Guide Labs, a coding interpretable foundation model intended to ease the alignment process, has raised $9.3M at a $35M valuation. The round was funded by Lombardstreet Ventures, Initialized Capital Management, Pioneer Fund and Y Combinator.

• Hoop, a NYC-based provider of an AI-powered task management platform, has raised $5M. The round was led by Index Ventures, with participation from Origin Ventures, Divergent Capital, and Chingona Ventures.

• Liminal AI, a data security solution designed to enable enterprises to safely interact with generative artificial intelligence, has raised $5M at a $20M valuation. The round was led by Fin Capital, with participation from Matchstick Ventures, High Alpha and Craft Ventures.

• Maxim, an enterprise-grade stack for building AI applications, has raised $3M at a $13M valuation. The round was led by Elevation Capital.

• OmniAI, a data transformation platform designed to convert unstructured data into useful insights, has raised $3.2M at a $30M valuation. The round was led by FundersClub, with participation from Imagination Capital.

• Openledger, an AI platform designed for decentralized and verifiable data infrastructure, has raised $8M. The round was co-led by Polychain Capital and Borderless Capital, with participation from Mask Network, STIX Global, TRGC, Finality Capital Partners, Hash3, Hashkey Capital, MH Ventures and WAGMI Ventures.

• Restate, a lightweight workflows-as-code platform, has raised $7M. The round was led by Redpoint Ventures, with participation from Essence VC and firstminute.capital.

• Seven AI, a Boston-based startup that uses AI to help enterprises boost their defenses against cyberattacks, has raised $36M at a $100M valuation. Greylock led the round, with participation from CRV and Spark Capital.

• Substrate, an AI infrastructure designed to make multi-step programs that run fast, has raised $8M. The round was led by Lightspeed Venture Partners, with participation from South Park Commons and Craft Ventures.

• Synthflow, an AI voice assistant platform designed to offer cold call, answer inbound calls, and schedule appointments, has raised $7.4M. The round was led by Singular, with participation from Atlantic Labs.

• Tektonic AI, a Seattle, WA-based company developing GenAI agents for enterprise processes, has raised $10M. The round was led by Point72 Ventures and Madrona Venture Group.

• Thoughtly, a company building AI voice agents for contact centers, has raised $3M. The round was funded by Afore Capital, Expansion Venture Capital and Greycroft.

• Tomato.ai, an artificial intelligence-based voice clarity software designed to offer more efficient agent calls, has raised $12.09M at a $25M valuation. The round was led by Recursive Ventures and Cardumen Capital, with participation from Point72 Ventures, Tribe Capital, JAZZ Venture Partners, Octave and Gaingels.

• Zeta Labs, a developer of an AI assistant designed to automate routine web-centric tasks, has raised $2.9M. The round was led by  Daniel Gross and Nat Friedman, with participation from Kaya VC, AI Grant and Earlybird Venture Capital.

Series A:

• Aim Security, a generative AI security platform designed to offer a guide to secure GenAI adoption, has raised $18M. The round was led by Canaan Partners, with participation from YL Ventures, Operator Partners and Cyber Club London.

• Decagon, a generative AI company empowering enterprise customer support, has raised $30M. The round was led by Accel, with participation from A* Capital, Neo and Andreessen Horowitz.

• Factory, a company using AI to help businesses streamline coding tasks, has raised $15M at a $100M valuation. Sequoia led the round, with participation from Lux Capital and Mantis VC.

• GPTZero, an AI detector software platform designed to identify text generated by AI and certify human writing, has raised $10M at a $40M valuation. The round was led by Nikhil Basu Trivedi, with participation from Uncork Capital, Reach Capital, Alt Capital and Neo.

• HeyGen, an AI startup that lets users quickly create realistic-looking avatars, has raised $60M. The round was led by Benchmark, with participation from Conviction Partners, Thrive Capital, SV Angel and Bond Capital.

• LegalFly, an AI copilot platform designed to amplify and refine the myriad facets of a legal professional's workflow, has raised $16.1M. The round was led by Notion Capital, with participation from Fortino Capital Partners and Redalpine.

• LiveKit, a platform for building and scaling voice applications, has raised $22.7M at a $115.7M valuation. The round was led by Altimeter Capital, with participation from Redpoint Ventures.

• SurrealDB, a platform that allows developers to model data using multiple different data models at once, has raised $20M. The round was led by FirstMark and Georgian, with participation from Crew Capital and Alumni Ventures.

• Tembo, a scalable and secure platform designed for building, deploying, and managing a range of data services and applications on Postgres databases, has raised $14M. The round was led by GreatPoint Ventures, with participation from Venrock, Defined Capital, Cintrifuse Capital, Bearcat Ventures, Wireframe Ventures and Grand Ventures.

• Twelve Labs, a company that bills itself as a multimodal AI that understands videos like humans, has raised $50M. The round was led by Nvidia, with participation from New Enterprise Associates, Radical Ventures, Index Ventures SA and Korea Investment Partners.

Series B:

• Clay, an AI startup focused on sales and marketing for businesses, has raised $46M at a $500M valuation. The investment was led by Meritech Capital Partners, with participation from BoxGroup, Boldstart Ventures, First Round Capital and Sequoia Capital.

• Coder, a startup that provides preconfigured, geared-toward-the-enterprise cloud environments for developer use cases, has raised $35M at a $205M valuation. The round was led by Georgian, with participation from Uncork Capital, Notable Capital and Redpoint Ventures.

• Fireworks AI, a platform that lets companies access multiple AI models, has raised $52M at a $552M valuation. The round was led by Sequoia Capital, with participation from Databricks Ventures, Advanced Micro Devices, MongoDB Ventures, Benchmark Capital Holdings and Nvidia.

• Hebbia, a New York-based document search AI startup, has raised $130M at a $710M valuation. The round was led by Andreessen Horowitz, with participation from GV and Index Ventures.

• HerculesAI, an AI-powered automation software designed to automate time-consuming administrative tasks, has raised $26M. The round was led by Streamlined Ventures, with participation from Thomson Reuters Ventures, PROOF, Davidovs Venture Collective, Decart Ventures, Network VC, Evolution VC, Streamlined Ventures, Vision Capital Group and Hybridge Capital Management.

• Mistral AI, a company that has made proprietary models designed to be repackaged as API-first products, has raised $640M at a $6B valuation. The round was led by General Catalyst and DST Global, with participation from Cisco Systems, Samsung Electronics, International Business Machines, Belfius Investment Partners, Bertelsmann Investments, Salesforce, Eurazeo, Korelya Capital, Lightspeed Venture Partners, Headline, Andreessen Horowitz, Millennium Technology Value Partners, Nvidia, Bpifrance and BNP Paribas.

• Onehouse, a Sunnyvale, CA-based data lakehouse company, has raised $35M. Craft Ventures led the round, and was joined by Addition and Greylock.

• Pika, a Palo Alto, CA-based text-to-video AI platform, has raised $80M at a $470M valuation. The round was led by Spark Capital, with participation from Conviction Capital, Lightspeed Venture Partners, NYX Ventures Partners, Greycroft, Makers Fund, Neo and SV Angel.

• Rocketlane, an automation platform that helps enterprises better understand customer feedback, has raised $24M. The round was co-led by 8VC, Matrix Partners India and Nexus Venture Partners.

Series C:

• Captions, an AI-powered video creation platform, has raised $60M at a $560M valuation. The round was led by Index Ventures, with participation from Kleiner Perkins, Andreessen Horowitz, Sequoia Capital, Adobe Ventures and HubSpot Ventures.

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Getting Fit

This week, Karri Saarinen (CEO and Co-founder of Linear) shared Linear’s headcount numbers at each financing milestone. Linear has built a beloved product and is backed by some of the best VCs including Sequoia and Accel. Through the go-go years of ZIRP, Linear stayed lean and kept its headcount growth reasonable. In 2020 when Linear raised its Series A, it has 8 employees. In 2020, the norm was for Series A companies to have 40+ employees. For perspective, in 2021, David Sacks published a blog post about the SaaS Org Chart listing the optimal 50-person org for a company that raised its Series A.

Startups are getting fit. Some teams, like Linear, were smart to start lean and remain disciplined. There are many forces driving startups getting fit:

• Venture capital funding has dried up, especially in the growth-stage rounds (Series B+)

• AI is increasing productivity, so teams can do more with less.

• The biggest tech companies are being rewarded in the public markets for getting fit and reducing headcount. This has a trickle-down effect on startups.

• Leaner orgs execute highest priorities faster (see below for Zuck’s letter):

  

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango and Tome.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Freemium (Self Serve):

  • Great: 7%

  • Good: 4%

• Freemium (Sales Assist):

  • Great: 12%

  • Good: 6%

• Free Trial:

  • Great: 15%

  • Good: 8%

• Reverse Trial:

  • Great: 15%

  • Good: 8%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

15 Biggest Stock Gainers (1 month):

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• Ducky, an AI-powered support platform, has raised $2.7M. The round was led by Penny Jar Capital, with participation from Bread & Butter Ventures, Wilson Sonsini Goodrich & Rosati and NOMO Ventures.

• Zefi, a platform that allows companies to centralize and analyze all conversations with their end customers automatically using AI, has raised $1.73M. The round was led by 14Peaks Capital and 360 Capital, with participation from BIT, Secways Capital, Vento, B Heroes, Growth Engine, Exor, Halo Growth Ventures, and Aticco Ventures.

• Zendata, a provider of AI governance and data privacy solutions, has raised $2M. The round was led by PayPal Ventures, with participation from Altari Ventures, Geek Ventures, FirstHand Alliance, Race Capital and Sputnik ATX.

Series A:

• Maven AGI, an AI customer support startup, has raised $20M at a $90M valuation. The round was led by M13, with participation from E14 Fund and Lux Capital.

Series B:

• xAI, Elon Musk’s AI company, has raised $6B at a $24B valuation. The round was led by Sequoia Capital, Andreessen Horowitz and Fidelity International Strategic Ventures, with participation from Valor Equity Partners, Kingdom Holding Company, Redstone VC, Flat Capital, HOF Capital, Vy Capital, Tribe Capital, Lightspeed Venture Partners, ARK Investment Management and Redefine Ventures.

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The Musk Algorithm

Whether you like Elon or not, his ability to successfully build hard companies is irrefutable. I pulled this section from Walter Isaacson’s biography on Elon as I was struck by the clarity and simplicity of Elon’s framework:

1. “Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department”. You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb.

2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough.

3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist.

4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted.

5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out.”

Although Musk is primarily discussing hardware assembly at Tesla and SpaceX factories, his insights are equally valuable for AI-powered startups and companies adopting AI for automation. The key takeaway is that automation should be the final step in a process. Preliminary work is required to delete unnecessary steps and simplify workflows before leveraging AI to automate the remaining crucial tasks. I've observed companies struggle when they prematurely apply AI to complex, multi-step workflows. The most successful teams break down processes into smaller steps, eliminate the unnecessary ones, simplify what's left, and then automate only what truly needs automating. This methodical approach ensures that AI is used effectively and efficiently, leading to better outcomes.

Thanks for reading. By way of background, I am an early-stage investor at Wing and a former founder. Please reach out to me on X @zacharydewitt or at zach@wing.vc. Some of the early-stage PLG + AI companies that I have the privilege to work with and learn from are: AirOps, Copy.ai, Deepgram, Hireguide, Slang.ai, Tango and Tome.

Operating Benchmarks (from PLG Startups):

I will continue to update these metrics and add new metrics. Let me know what metrics you want me to add (zach@wing.vc)

Organic Traffic (as % of all website traffic):

• Great: 70%

• Good: 50%

Conversion rate (website → free user):

• Great: 10%

• Good: 5%

Activation rate (free user → activated user):

• Great: 50%

• Good: 30%

Paid conversion rate (free user → paid user):

• Freemium (Self Serve):

  • Great: 7%

  • Good: 4%

• Freemium (Sales Assist):

  • Great: 12%

  • Good: 6%

• Free Trial:

  • Great: 15%

  • Good: 8%

• Reverse Trial:

  • Great: 15%

  • Good: 8%

Enterprise conversion rate (free user → enterprise plan):

• Great: 4%

• Good: 2%

3-month user retention (% of all users still using product after 3 months):

• Great: 30%

• Good: 15%

Conversion from waitlist to free user:

• <1 month on waitlist: ~50%

• >3 months on waitlist: 20%

For more detail on acqusition rates by channel (Organic, SEM, Social etc), please refer to this prior Notorious episode.

Financial Benchmarks (from PLG Public Companies):

Financial data as of previous business day market close.

Best-in-Class Benchmarking:

15 Highest EV/ NTM Revenue Multiples:

15 Biggest Stock Gainers (1 month):

Complete Dataset (click to zoom):

Note: TTM = Trailing Twelve Months; NTM = Next Twelve Months. Rule of 40 = TTM Revenue Growth % + FCF Margin %. GM-Adjusted CAC Payback = Change in Quarterly Revenue / (Gross Margin % * Prior Quarter Sales & Marketing Expense) * 12. Recent IPOs will have temporary “N/A”s as Wall Street Research has to wait to initiate converge.

Recent PLG + AI Financings:

Seed:

• ChainML, an AI research and development company dedicated to shaping a better future powered by AI agents, has raised $6.2M. The round was led by Hack VC, with participation from Figment Capital, Huobi Ventures, Hypersphere Ventures, Alumni Ventures, NxGen xyz, Newtribe Capital, Inception Capital and Foresight Ventures.

• Dosu, a GitHub AI teammate that helps users respond to issues, triage bugs, and build better documentation, has raised $8.52M. The round was led by Innovation Endeavors.

• Eto, a modern data store for computer vision, built on open standards, has raised $11M at a $44M valuation. The round was led by CRV, with participation from Soma Capital, Tango VC, Wayfinder Ventures, Rogue Capital, E14 Fund, Swift Ventures, Essence Venture Capital and Y Combinator.

• Founder AI, an automated fundraising agent that helps users identify investor leads, has raised $3M. The round was led by Pioneer Fund, Davidovs Venture Collective and Liquid2Ventures, with participation from AltaIR Capital, Rebel Fund and Y Combinator.

• HoundDog.ai, a startup that helps developers ensure their code doesn’t leak personally identifiable information, has raised $3.1M. The round was led by E14 Fund, with participation from Mozilla Ventures.

• Pythagora, an AI developer that builds apps through natural language interaction, has raised $4.3M. The round was funded by 500 Emerging Europe, Inovo VC, Moonfire, Rebel Fund, UpHonest Capital, Y Combinator, and SQ Capital.

• Rollup, a collaborative platform designed to help teams build the next generation of complex hardware and models, has raised $5.6M. The round was led by Andreessen Horowitz and Thiel Capital, with participation from Space.VC, Alumni Ventures, JAM Fund, and Spacecadet Ventures.

• Stack, a no-code generative artificial intelligence platform intended to automate enterprise-grade business processes, has raised $3M. The round was led by True Capital Partners, Lambda and Epakon Capital Management, with participation from Soma Capital, Beat Ventures, Gradient Ventures and Y Combinator.

Series A:

• Gamma, an AI powered presentation platform, has raised $12M. The round was led by Accel, with participation from South Park Commons, Script Capital, Lorimer Ventures and Susa Fellows Fund.

• Patronus AI, a company that makes a governance tool for LLMs, has raised $17M. The round was led by Notable Capital, with participation from Lightspeed Venture Partners, Factorial Capital and Datadog.

• WitnessAI, a startup that applies risk-mitigating policies and safeguards to generative AI, has raised $27.5M. The funding was led by Ballistic Ventures and GV.

• Rows, a collaborative cloud platform-based spreadsheet app, has raised $8.62M. The round was led by Indico Capital Partners, with participation from Cherry Ventures, Accel, Lakestar and Armilar Venture Partners.

Series B:

• Coactive, an application programming interface designed to empower data practitioners and data-driven teams to unlock insights into unstructured image and video data, has raised $30M. The round was led by Cherryrock Capital and Emerson Collective, with participation from Andreessen Horowitz, Bessemer Venture Partners, Exceptional Capital, Tech Square Ventures and Greycroft.

• Hebbia, a developer of user interfaces designed to improve use of Artificial General Intelligence (AGI), has raised $92.9M at a $705M valuation. The round was funded by undisclosed investors.

• Hydrolix, a Portland, OR-based streaming data lake platform, has raised $35M. S3 Ventures led the round, and was joined by Nava Ventures, Wing Ventures, AV8 Ventures and Oregon Venture Fund.

• Voxel51, an AI-based software designed to transform raw video footage and images into actionable intelligence, has raised $30M. The round was led by Bessemer Venture Partners, with participation from Tru Arrow Partners, Shasta Ventures, Drive Capital, Top Harvest Capital and iD Ventures America.

Series C:

• Gorgias, a customer experience platform developing AI-powered solutions, has raised $28.5M at a $548.5M valuation. The round was led by SaaStr and Alven Capital Partners, with participation from Shopify, Horsley Bridge Partners, Amplify Partners, CRV, Sapphire Ventures and Transpose Platform Management.

• PolyAI, a company that produces AI voice assistants for call centers, has raised $50M at a $500M valuation. The round was led by Hedosophia and NVentures, with Khosla Ventures and Point72 Ventures joining.

Series D:

• Sigma, a cloud data warehouse analytics software designed to analyze complex databases, has raised $200M at a $1.8B valuation. The round was led by Avenir Growth Capital and Spark Capital, with participation from Snowflake Ventures, NewView Capital, Sutter Hill Ventures, Altimeter Capital Management, D1 Capital Partners and XN.

Series E:

• Vercel, a cloud-based workflow platform intended to optimize the entire development and deployment experience for frontend teams, has raised $250M at a $3.25B valuation. The round was led by Accel, with participation from GV, 8VC, Tiger Global Management, Notable Capital, CRV, Bedrock Capital, Geodesic Capital and SV Angel.

• Weka, a platform for building data pipelines that handle a range of data sources, types and sizes, has raised $140M. The round was led by Valor Equity Partners, with participation from Nvidia, Norwest Venture Partners, Micron Ventures, Qualcomm Ventures and Hitachi Ventures.

Series F:

• Scale AI, a company that provides data-labeling services to companies that want to train machine learning models, has raised $1B at a $13.8B valuation. The round was led by Accel, with participation from Cisco Investments, DFJ Growth, Intel Capital, ServiceNow Ventures, AMD Ventures, WCM Industries, Amazon.com, Meta Platforms, Coatue Management, Spark Capital, Thrive Capital, Tiger Global Management, Greenoaks Capital Partners, Index Ventures, Founders Fund, Y Combinator, Nvidia, Geodesic Capital and Wellington Management.

Later Stage:

• DeepL, a company that builds automated text translation and writing tools, has raised $300M at a $2B valuation. The round was led by Index Ventures, with participation from ICONIQ Growth, Teachers’ Venture Growth, IVP, Atomico and WiL.