Blacksmith, an AI code-testing startup, has raised $45 million in a Series B round led by Peak XV Pa...
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Series B funding for a known player in AI DevTools, but the 10x valuation jump highlights growing demand for AI testing, making it segment-level significant.
Blacksmith, an AI code-testing startup, has raised $45 million in a Series B round led by Peak XV Partners, valuing the company at $550 million, up nearly 10x from its $60 million valuation at the Series A just a year ago. Existing investors GV and Y Combinator participated, bringing total funding to $58.5 million. Founded in 2024, Blacksmith helps companies build, test, and verify software before production, and now serves over 5,000 customers, including Mercury, Supabase, Clerk, Ashby, and Expensify, up from just 700 a year ago, per the AI Market Watch index, which tracks about 5,000 companies, though coverage is not a census.
The surge reflects a critical bottleneck created by AI coding tools like Cursor, OpenAI's Codex, and Anthropic's Claude Code: generating code is now faster, but validating its quality is not. Blacksmith's CEO Aditya Jayaprakash emphasizes that "validating code is still a bottleneck, and it's an even bigger bottleneck because people are writing even more." The company started as a cloud provider for continuous integration workloads and has expanded with Codesmith, an AI agent that automatically fixes failed code checks. With just 30 employees, Blacksmith claims revenue in the "tens of millions" and some customers spending over $1 million annually, highlighting strong demand for AI-accelerated testing infrastructure.
For builders, this signals a growing market for AI-powered validation and QA as demand for faster software delivery intensifies. For investors, the 10x valuation jump underscores the value of integrating AI into the testing layer, rather than just code generation. Blacksmith faces competition from giants like GitHub Actions, Cursor Automations, and cloud providers' native testing tools, but its differentiation on speed and cost could help it carve a niche. As AI coding adoption grows, the need for reliable testing will only increase, making validation a key battleground.