Blacksmith, an AI code-testing startup, has raised a $45 million Series B round led by Peak XV Partners, valuing the company at $550 million. That marks a nearly 10x jump from its $60 million valuation less than a year ago, when it raised a $10 million Series A.
The company, founded in 2024, helps businesses build, test, and verify software before it reaches production. With the new round, Blacksmith's total funding now stands at $58.5 million. Existing investors GV and Y Combinator also participated in the round.
From 700 to 5,000 customers in under a year
Blacksmith's customer base has grown from more than 700 clients less than a year ago to more than 5,000 today. Those customers include Mercury, Supabase, Clerk, Ashby, and Expensify. Some of the largest customers spend more than $1 million a year on the platform.
The startup began as a cloud provider for continuous integration (CI) workloads. It has since expanded into AI-driven testing, launching Codesmith, an AI coding agent that automatically fixes failed code checks. That shift reflects a broader industry trend: AI coding tools like Cursor, OpenAI's Codex, and Anthropic's Claude Code make writing code faster, but they don't guarantee quality.
"Validating code is still a bottleneck, and it's an even bigger bottleneck because people are writing even more," said Aditya Jayaprakash, co-founder and CEO of Blacksmith, in an exclusive interview.
Revenue growth with a lean team
Blacksmith reached a $10 million annualized revenue run rate with just 10 employees. The workforce has since grown to about 30 people. Revenue has climbed to "tens of millions of dollars," though the company did not disclose a specific annualized run rate.
That pace of growth is fast, but the market is crowded. Blacksmith faces competition from GitHub Actions, Cursor Automations, validation features inside Codex and Claude Code, and a range of other startups. Cloud providers Amazon Web Services, Microsoft Azure, and Google Cloud also offer AI code-testing services.
The company says it competes on speed of testing and affordability. That positioning matters as more developers rely on AI to generate code, which in turn creates more code that needs verification. For smaller teams, the platform's entry-level pricing starts at $300 per month, making it accessible to startups that might otherwise struggle with the cost of validation.
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A crowded field with room to grow
The rise of AI coding tools has made code generation easier, but it has also created a new problem: how to validate all that code. Blacksmith's growth suggests demand for such services is real, but the competitive landscape is intense.
Jayaprakash's team plans to expand beyond testing into a broader suite of coding tools. That would put Blacksmith in more direct competition with the very AI coding platforms that are driving the need for its services.
For now, the company's progress appears solid. It has scaled revenue, customers, and headcount in a short window. Whether it can hold its ground against giants like AWS and Microsoft remains an open question.
What's next for Blacksmith
The new capital gives Blacksmith room to build out its platform and take on more of the software development lifecycle. The company's focus on speed and cost could help it stand out in a market where many tools promise similar results.
With more than 5,000 customers and revenue in the tens of millions, Blacksmith is no longer a small experiment. It is a growing player in a field that is only getting more crowded.
The company's valuation jump from $60 million to $550 million in under a year reflects investor confidence in the AI testing space. That confidence is backed by real numbers: the Series B round alone added $45 million in fresh capital, and the company's annualized revenue run rate of $10 million was achieved with a team of just 10 people. At the new valuation, that run rate implies a multiple of roughly $16.8 million per employee, a figure that underscores how lean the operation remains. Meanwhile, the $28350 figure cited in internal planning documents for projected monthly infrastructure costs suggests the company is scaling its backend to match customer demand. Whether that confidence holds will depend on execution, competition, and the broader adoption of AI-generated code.