Nominal Raises $240 Million at $3 Billion to Tell Engineers Whether Their Machines Work

Nominal, a startup that makes AI software for engineering and testing hardware, has raised $240 million in a Series C round at a $3 billion valuation. Lightspeed Venture Partners led the round, and Insight Partners co-led it. The valuation is triple what Nominal was worth eight months ago, when it raised its last round.

The company already has a solid customer lineup. It counts more than 80 customers, including Anduril and five of the seven largest defense contractors. In October, Nominal was selected for a $71.2 million package through the Air Force's Strategic Funding Increase (STRATFI) program, including $41.2 million in government funding for Air Force and Navy aircraft programs. Nominal says its revenue has more than tripled so far this year, aided by a boom in defense technology spending.

Surprisingly, at most hardware companies, test data is still stored locally by default. Engineers download it to their own laptops and analyze it separately in MATLAB or Python, the avionics engineer in one file and the thermal engineer in another. Then they share their results, "often via screenshot." "PowerPoint engineering is, like, still the bleeding edge for many, many of these companies," said Nominal co-founder and CEO Cameron McCord on a Sequoia Capital podcast.

Lightspeed's framing makes the picture clearer: Nominal wants to be for hardware engineers what Harvey is for lawyers and Abridge is for doctors, AI built around one highly skilled profession that the people in it can actually trust.

To get there, Nominal starts by pulling a team's scattered test data onto one shared timeline, so everyone works from the same record. The difference shows up in speed. When hypersonic aircraft startup Hermeus made its first flight in May 2025, it had two hours on the runway to run a taxi test, review the data and take off. A review that used to take weeks "was done by the time we'd towed the airplane back to the other end of the runway," said Hermeus CEO AJ Piplica.

That shared record is now the foundation for what Nominal calls a "Hardware Intelligence Platform." The company describes it in four layers: software that connects to and controls test equipment, a data layer that organizes every signal and file, AI agents that investigate that data and, finally, applications that Nominal and its customers build on top. Its first agent, Nominal Analyst, runs analyses on engineering data and traces its answers back to the underlying evidence.

How did a 4-year-old startup grow so fast and win over such conservative customers? The founders' backgrounds help explain it.

McCord spent eight years in the US Navy, including 484 days underwater on a submarine. While deployed, he taught himself AI by watching Stanford lectures he had downloaded before going to sea. "Learning AI, and then going into the control room where you have 1970s software, old hardware—it was a crazy cognitive dissonance," he said in a Sequoia Capital profile of Nominal.

The idea for Nominal came later, at Anduril. McCord's team tested the company's counter-drone system in the California desert. "It was so difficult with the tools we had to capture that data, intuitively organize it, and just answer the question: Did the test work?" McCord said. If a company as well funded as Anduril struggled with this, he figured, older defense companies had it worse.

After 15 months at Anduril, he left to build a company around the problem. He pitched the idea to Lux Capital and joined the firm as a part-time entrepreneur-in-residence while he studied for his MBA at Harvard Business School.

There he met Bryce Strauss, a former Lockheed Martin spacecraft engineer who had been the "internal tools person" on his Lockheed team. For a third co-founder, McCord called his MIT roommate Jason Hoch, who had spent five years at Palantir. Strauss named the company after "all systems nominal," the phrase launch controllers use when every check has passed.

Lux wrote Nominal's first check 30 days before McCord and Strauss graduated. General Catalyst, Sequoia and Founders Fund followed, and Lightspeed, which joined the Series B, now leads the Series C. Lockheed Martin Ventures also invested in this round, and Lockheed itself appears on Nominal's customer list.

Nominal's string of big rounds reflects a wider shift in where investors are putting their money. For now, Nominal's work is most visible in defense. Its customers include Anduril, the Air Force and the Navy, along with several companies building rival aircraft and autonomy software for the same military programs. A decade ago, few venture firms would have backed a business like this so aggressively.

But things have changed recently. Defense companies around the world have seen their shares rise sharply since Russia invaded Ukraine in February 2022. In venture capital, firms such as 8VC and Marlinspike Partners have raised new funds with defense as a major focus.

At the same time, Nominal has another market in view: physical AI. As AI moves from screens into robots, vehicles and aircraft, more machines will need proof that they work in the real world, not just in simulation. "In engineering, physics gets a vote," the company wrote.

The founders argue that only a few companies can build this kind of testing software for themselves. SpaceX built its own early on, and Hoch has called that a big reason for its success. "A thousand companies that are now being started this year, next year, it doesn't make sense for all of them to build a platform like that," he said.

Nominal's customers already reach past defense. They include nuclear developer Antares and the Corvette Racing team. This month, Nominal also bought Pull Systems, a startup that built vehicle monitoring software with Porsche and other Volkswagen Group brands.

Still, given its founders and its biggest customers, Nominal is best described for now as a physical AI testing company that is making its money in defense first. It sits at a curious intersection of the two industries drawing the most attention right now: defense and physical AI.