Blacksmith’s Valuation Jumps Nearly 10x to $550 Million as AI Coding Surges
The sudden proliferation of artificial intelligence coding tools such as Cursor, OpenAI’s Codex, and Claude Code has revolutionized the development process. However, as programmers generate huge amounts of automated code, the bottleneck of the process is now no longer generation but validation.
Leveraging this development in the sector, Blacksmith, which develops software for code testing, has raised $45 million in its Series B financing round and reached a valuation of $550 million, an increase of about ten times since its valuation of $60 million a year before.
In the financing round, Peak XV Partners was the lead investor, while other venture investors such as GV and Y Combinator invested three times more in the company. Founded in 2024 by CEO Aditya Jayaprakash, Blacksmith is a San Francisco-based firm that provides high-quality CI infrastructure.
Built as an alternative to existing CI platforms such as GitHub Actions, Blacksmith automates testing using bare-metal machines with gaming CPUs for quick build processes at low computing costs. With respect to the corporate clients of the company, there were around 700 engineering teams at the beginning of its existence, and now there are more than 6,000.
The revenue reached tens of millions of dollars due to the lean engineering department consisting of only 30 people. To augment the existing testing framework, the company also developed Codesmith, an autonomous AI agent that will be able to automatically fix code checks in case of continuous integration failures.
In spite of the strong competition from hyperscaler companies and developer platforms like GitHub or GitLab, Blacksmith has its unique niche in which it can offer something important for software teams: speed.
As the number of generative tools and automatic pull requests keeps increasing in repositories, it is crucial to check code quality before deploying it to production. It becomes absolutely necessary to have specialized infrastructure for the quality control of AI-generated software.
