Code Metal announced it has completed a $36.5 million Series A funding round, led by venture-capital firm Accel and joined by investors such as RTX Ventures, Bosch Ventures and Shield Capital. The round values the company at approximately $250 million.
Founded to help industries move faster from legacy systems to AI-enabled development, Code Metal’s platform uses a mix of formal methods and generative AI to translate code across languages, hardware and environments.
The process aims to guarantee correctness, performance and compliance, features that matter deeply in sectors like aerospace, automotive and defence.
The startup claims its technology can reduce code-conversion timelines from weeks to days, and notes it already holds contracts generating eight-figure revenue this year from enterprise customers.
AI Coding Moves From Autocomplete To Architecture
In a market crowded with AI coding assistants like GitHub Copilot, Code Metal places itself in a different category. Rather than offering generic code suggestions, it focuses on mission-critical systems where errors are not acceptable.
“We recognized that many industries could not use current AI assistants because they lacked formal verification and cross-hardware support,” said CEO Peter Morales in a press release.
Accel partner Steve Loughlin described the investment as part of a broader trend:
“The next generation of software infrastructure requires systems that understand code context, workflows and certification, not just typing speed.”
This positioning suggests Code Metal believes the developer-tooling wave now moves beyond novelty and into depth, focusing not only on how code is generated but how it is translated, deployed and maintained at scale.
Relevance Across Industries Facing Tight Constraints
The use cases are compelling in sectors where mistakes carry outsized consequences. In defence systems, for instance, software often needs to run on specialised hardware under strict regulatory oversight.
In automotive, software must operate within real-time and safety-critical environments. Code Metal’s clients reportedly include organisations working in embedded systems translation and chip-specific optimisations.
For enterprise customers, the draw is obvious: faster innovation without relaxing safety or compliance. In turn, this market remains under-addressed by generic coding tools and open-source models. Investors appear to believe that bridging AI coding to industrial software could unlock a strong return pathway.
With fresh funding and a clear mission, Code Metal is now entering a growth phase. Its challenge will be scaling operations globally, expanding its technical team and building volume without compromising the rigor that defines its offering.
As AI continues to reshape software workflows, the question is whether Code Metal can close the gap between experimental tools and enterprise-ready platforms.
