Mintlify Raises $45 Million Series B led by Andreessen Horowitz and Salesforce Ventures

Mintlify, the intelligent knowledge platform, led by Han Wang and Hahnbee Lee, 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, reaching more than 100 million users annually. This funding round advances the mission to become the knowledge layer that makes products understandable, usable, and discoverable by AI agents.

Empowering Builders

Founded in 2022, Mintlify was built with a simple mission: to empower builders by making software easier to understand through better documentation. Rooted in firsthand developer experience, the focus emerged from the widespread challenge of fragmented and outdated technical resources.

After participating in Y Combinator’s W22 batch, the platform evolved into a widely adopted documentation solution used by thousands of companies. Initial efforts centered on making documentation faster, more intuitive, and genuinely useful, until the shift brought on by AI expanded the scope of the problem.

Documentation as Infrastructure

The role of documentation has shifted significantly, evolving beyond human-readable guides into a core interface for AI systems. While traditional use cases remain, a growing share of traffic now comes from AI agents and AI-assisted workflows, reshaping how documentation must be structured and maintained.

Unlike marketing content, documentation serves as the primary source through which AI systems understand and interact with products. Incomplete, outdated, or poorly structured documentation can limit visibility and lead to incorrect outputs when agents rely on flawed information.

This marks a fundamental shift: documentation is no longer just content, but critical infrastructure. A reliable, structured, and continuously updated knowledge layer is becoming essential for companies operating in an AI-native environment, with long-term advantages accruing to those that invest early.

Building for This Shift

The transition toward knowledge infrastructure is already underway, driven by both product direction and customer demand. What began as a platform for public documentation has expanded into internal use cases, including knowledge bases, engineering handbooks, and design systems, ensuring that AI-powered tools rely on accurate, structured information.

Product development is centered on treating documentation as the interface for AI agents, supported by automated workflows, integrations, and AI-driven content generation. This approach enables knowledge to remain continuously updated, connected, and accessible across systems.

The objective is clear: create a reliable, structured knowledge layer that allows AI systems to accurately understand and interact with an organization.