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Flow Engineering Raises $50M to Accelerate Agentic Hardware Development

Flow Engineering Raises $50M at $750M Valuation Flow Engineering has raised $50 million in Series B funding at a $750 million valuation. The round was co-led by Antonio Gracias and The post Flow Engineering Raises $50M to Accelerate Agentic Hardware Development appeared first on Ventureburn .

Flow Engineering Raises $50M to Accelerate Agentic Hardware Development

Flow Engineering has secured $50 million in Series B funding, bringing its valuation to $750 million. The round was led by Antonio Gracias and Gavin Baker, with Sequoia Capital joining after co-leading Flow's Series A. The investment round includes participation from Human Capital, Evantic, SV Angel, Odyssey, EQT, Hugging Face co-founder Thomas Wolf, and Mercedes-Benz CIO Jonas von Malottki, among others.

Notably, Formula 1 world champion Nico Rosberg also invested in the company. Flow's platform, designed for complex hardware engineering programs, uses AI agents to track design changes across multiple engineering systems and help propagate updates and verify results. The company aims to accelerate hardware development cycles from months to days.

Flow's AI platform can continuously monitor changes across engineering teams and verify whether updated designs still satisfy required constraints, such as technical specifications and regulatory standards. Rivian has adopted Flow across its engineering teams, with the user base growing from 40 to 1,500 in just seven months. The company plans to use the funding to build an AI harness for hardware engineering, allowing frontier AI models to work securely with sensitive engineering data.

Flow also intends to expand review, branching, and evaluation capabilities and develop stronger controls for increasingly complex engineering programs. The company aims to pursue FedRAMP authorization and other industry certifications to support adoption among regulated sector customers.

Written by urgent.news from Ventureburn's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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