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    Code Metallic Raises $125 Million to Rewrite the Protection Business’s Code With AI

    Naveed AhmadBy Naveed Ahmad20/02/2026Updated:20/02/2026No Comments4 Mins Read
    Buzzy Startup Business Code Metal 10 30 25 30


    Code Metallic, a Boston-based startup that makes use of AI to write down code and translate it into different programming languages, simply closed a $125 million Collection B funding spherical from new and present buyers. The information comes only a few months after the startup raised $36 million in collection A financing led by Accel.

    Code Metallic is a part of a brand new wave of startups aiming to modernize the tech trade by utilizing AI to generate code and translate it throughout programming languages. One of many questions that persists about AI-assisted code, although, is whether or not the output is any good—and what the results may be if it’s not.

    Over the previous two years corporations like Antithesis, Code Rabbit, Synthesized, Theorem, and Harness have all secured tens of millions in backing from enterprise capitalists for his or her approaches to automating, validating, testing, and securing AI-generated code. These startups are promoting the “picks and shovels” of the AI gold rush—tech instruments that serve a bigger trade. Whereas a number of the methodologies behind their expertise stay unproven, buyers are keen to gamble that no less than a couple of will pan out.

    Code Metallic, which was based in 2023, has targeted its efforts on code translation and code verification for the protection trade. It boasts L3Harris, RTX (previously generally known as Raytheon), and the US Air Power as early prospects. The startup can be working with Japanese electronics firm Toshiba and says it’s in talks with a big chip firm to work on code portability throughout chip platforms, although the corporate declined to say which one.

    The startup’s software program platform interprets code from high-level programming languages like Python, Julia, Matlab, and C++ to lower-level languages or code that runs on particular {hardware}, like Rust, VHDL, and chip-specific languages like Nvidia’s CUDA.

    Code Metallic CEO Peter Morales, who beforehand labored at Microsoft and the MIT Lincoln Laboratory, says the market is beginning to acknowledge “the large tentpole issues” in an trade that would, within the not-so-distant future, be propped up by AI-generated code. A type of issues is porting outdated code into new purposes. If a authorities company or protection contractor wants coding work performed shortly, Morales says, however solely has entry to engineers who’ve specialised in a legacy programming language, that slows everybody down.

    Morales cites a recent post on X from well-known AI researcher Andrej Karpathy, who noticed the “rising momentum behind porting C to Rust,” amongst different issues. Karpathy concluded: “It feels doubtless that we’ll find yourself rewriting giant fractions of all software program ever written many occasions over.”

    “That’s all of what we do in a single tweet,” Morales says.

    Considered one of Code Metallic’s buyers, Yan-David Erlich, a common associate at B Capital, says the fact is that a number of the code that controls important communications infrastructure, and even satellites, “is outdated, it’s crufty, it’s written in programming languages that folks may not use anymore. It must be modernized.”

    “However in the middle of translation,” Erlich added, “you may be inserting bugs—which is catastrophically problematic.”

    That’s the place Code Metallic says its proprietary tech is available in. Morales says that at every step of translation, Code Metallic’s software program generates a collection of check harnesses—a digital container of information and instruments—that consider the code and present prospects alongside the best way that it’s working. When requested about Code Metallic’s error price for translation, Morales says it relies upon largely on how tough the code conversion is, however that for the pipelines Code Metallic presently runs, “there’s no option to generate an error. The software program will simply say, ‘There’s no answer for this’ if we will’t full the interpretation.”

    The startup is skittish about sharing too many particulars about its methodology. One ingredient of the enterprise it’s not shying away from speaking about, nonetheless, is its method to pricing.



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    Naveed Ahmad

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