Flow Engineering raises $50M at $750M valuation to bring AI-driven continuous verification to hardware design

Flow Engineering raises $50M at a $750M valuation

Flow Engineering has raised $50 million at a $750 million valuation to accelerate AI investment in hardware design verification, founder Pari Singh says. The customer base spans aerospace, automotive, and defense, with names including Joby, Stoke Space, Rivian, and Anduril.

The problem

The central bottleneck in hardware development is systems integration and verification. Singh's example is instructive: change a single injector in a rocket's first-stage engine, and you trigger a cascade through fluid flow, combustion, thrust, and mission profile. The third, fourth, and fifth-order impacts are where failures originate. Because full verification has historically been expensive and slow, most hardware companies can only afford to run it every six to twelve months.

Flow Engineering's bet is that AI makes continuous verification viable, bringing the software engineering concept of CI/CD to hardware. Engineers can commit changes in CAD, Git, or simulation on an hourly basis, and the AI agent surfaces the downstream implications in real time rather than months later.

“The single biggest problem in hardware companies is systems integration and verification... What AI enables for us is this idea that we can move from manual verification — which is once every year — to continuous verification, just like we have in software engineering with CI/CD... Today, 96% of our customers come to us inbound, and they're able to get up and running within thirty days.”

Wedge and expansion

Flow enters through requirements management, the system of record that all design data traces back to. It replaces what Singh describes as "old school stodgy" tooling and acts as the verification layer against which every change in CAD, simulation, or code is checked. From there, the product expands into a broader collaboration layer connecting engineering teams with suppliers. Several of Flow's largest customers, including in defense and EV, work natively with their supply chain partners inside the platform so that a supplier change propagates into the customer's system immediately.

Adoption signal

96% of customers come inbound, and Singh says they are up and running within 30 days. Legacy vendors typically require nine to twelve months to onboard. Singh attributes the fast adoption partly to the AI layer doing the integration work that previously required long professional services engagements.

The design cycle argument

Singh frames the broader opportunity as compressing hardware design cycles from twelve months to twelve weeks to twelve hours. The analogy to software is deliberate: as AI models have gotten better at domain-specific tasks, they are beginning to assist not just on CAD geometry but across the earlier and more labor-intensive stages of mechanical, electrical, software, and regulatory engineering that precede any 3D design work.