We're excited to share that Mintlify has raised a $45M Series B at a $500M valuation, led by a16z and Salesforce Ventures, with participation from Bain Capital Ventures, Y Combinator, Rahul Mehta, Managing Partner @ DST Global, MVP Ventures, Avra, HubSpot Ventures, and TwentyTwo Ventures.

Mintlify now powers documentation for over 20,000 companies, with content reaching more than 100 million people every year. This round accelerates our mission to become the knowledge layer that makes products understandable, usable and discoverable by AI agents.

I want to share a bit about how we got here, what's changed, and where we're going.

When Hahnbee and I started Mintlify in 2022, it was on a very simple mission: empower builders and make it effortless for developers to understand how software works. We're developers ourselves, and we've always believed that giving people the right technical knowledge leads to products that change the world.

We embarked on improving developer documentation because it was a core problem we understood deeply. We were the developers at 2am trying to integrate an API, piecing together answers from a stale README and a GitHub issue from three years ago. Documentation was everywhere, and it was broken almost everywhere too.

We went through Y Combinator's W22 batch, obsessed over the space, and built what became the documentation platform that thousands of companies rely on today. For a while, that felt like the whole story: make docs beautiful, make them fast, make them actually useful.

Then the world changed with AI.

Since we started, the role of documentation has shifted more dramatically than we ever expected.

Documentation used to be written for humans scanning a page: someone looking for a quick answer, a code snippet, a guide to get unblocked. That's still true, but it's no longer the full picture. Today, nearly 50% of traffic to documentation comes from AI agents and AI-assisted workflows and that number is only going up.

This changes what documentation needs to be. AI agents don't learn about your product from your marketing site. Marketing pages are designed to evoke human emotion, but they tell you very little about how a product actually works. When an AI agent needs to understand what your product does, how to use it, and how to interact with it, it goes to your docs. Your documentation is now your product's interface to AI and a system of record that agents rely on to take action. If it's incomplete, inaccurate, or poorly structured, your product can become invisible to AI entirely.

And the stakes go beyond discovery. When a company builds agents on top of knowledge that's scattered, outdated, or inconsistent, those agents give wrong answers. We've seen it firsthand: a company changes its pricing, the help center doesn't get updated, and every support agent built on that content starts telling customers the wrong thing. The problem is the knowledge layer underneath the model.

This is the critical shift: documentation is no longer just content. It's infrastructure. Every company will need a reliable, structured and continuously updated knowledge layer to compete in an AI-native world. The companies that invest in this layer will have a compounding advantage as AI-native workflows become the default. The ones that don't will find it very hard to catch up.

This isn't a theoretical bet for us. We've been building toward knowledge infrastructure for a while now, and our customers have been pulling us in this direction just as fast.

It started with the public-facing documentation that Mintlify has always been known for. But increasingly, our customers are bringing us into their organizations. They're using Mintlify to power their internal knowledge bases, engineering handbooks, design systems, internal best practices, because they realized the same thing that works for external developer docs works for the AI-powered tools and agents that all teams depend on. If you want your internal agents to give accurate answers, you need the knowledge they're built on to be maintained, structured, and connected. In other words, AI systems are only as good as the knowledge they're built on, and most companies are not ready, as their knowledge today is fragmented and unreliable.

On the product side, everything we're building is designed around the idea that your docs are now the interface to every AI agent in the world, and their content has to be accurate.

• Workflows: Always-on doc automation keeps content accurate
• MCP support: Connect your knowledge directly to external agents
• AI agent: Write and update new content based on your prompts

With integrations across codebases, project management platforms, the other tools companies already use, Mintlify fits into your existing workflows and becomes the layer that organizes, maintains and serves knowledge across your company.

The goal is straightforward: if an AI agent needs to understand your company, your product, or how anything in your organization works, that information should be accurate, structured, and available. That's the infrastructure we're building.

We believe this is a once in a decade shift in how software will be built, and we're scaling aggressively. We're hiring across engineering, sales, marketing, and more.

We're fully in-person in San Francisco, and we're looking for people who want to build the AI knowledge infrastructure layer with us. If you've read this far and you want to define a new category at the center of the AI stack, we'd love to hear from you. Check out our open roles at mintlify.com/careers.

To our customers, the 20,000+ companies that trust Mintlify to be the front door to their products, thank you. You're the reason we get to do this. Every time we hear that Mintlify changed how developers experience a product, it reminds us why we started.

To our team, thank you for building something that reaches 100 million developers a year and for caring as much as you do about getting the details right.