CAMBRIDGE, Mass.--(BUSINESS WIRE)--Mar 9, 2026--
Axiomatic AI, the company building the verification standard for engineering-focused artificial intelligence, today announced an $18 million seed round, bringing total funding to $25 million. The company integrates frontier AI models with formal mathematical and physics-based verification to deliver interpretable, provable reasoning for critical and emerging technology. As engineering complexity accelerates across semiconductors, photonics, and advanced manufacturing, Axiomatic AI is establishing the intelligent infrastructure layer required for AI to operate reliably inside physical law. The round was led by Engine Ventures, with additional participating investors including Kleiner Perkins, Big Sur Ventures, Global Vision Capital, Propagator Ventures, and Liquid 2. Axiomatic will use the new capital to expand enterprise deployments and deepen integration of its verification platform into complex science and engineering workflows.
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Axiomatic’s core technology, Axiomatic Intelligence™, is purpose-built for engineering and science. It combines frontier AI models with both mathematical and physics-based verification and domain-specific knowledge that compound in value with use. Unlike conventional AI systems, which can generate plausible-sounding outputs but can’t verify those outputs against the laws of physics, validate assumptions, or quantify uncertainty, Axiomatic Intelligence delivers interpretable, physics-grounded reasoning with formal auditability. This enables Axiomatic’s products to automate and orchestrate complex engineering workflows, all while verifying correctness and consistency at multiple levels: fundamental physical principles, design principles, and logical reasoning.
Today’s AI can suggest designs. It cannot prove they obey physics. Even the most advanced generative models require extensive human oversight in high-stakes scientific and engineering workflows, limiting productivity gains and introducing systemic risk. The National Institute of Standards and Technology (NIST) identifies hallucinations and ‘cheating’ as key challenges in deploying large language models (LLMs) safely. Engineers and scientists require systems that reflect physical reality and provide formal guarantees. Manual verification erodes productivity and increases risk, particularly as industries face significant workforce shortages. In the semiconductor industry alone, the U.S. is already facing a workforce shortage, requiring ~160,000 new engineering roles by 2032 to support domestic expansion and reshoring efforts.
“We are defining the standard that science and engineering AI must meet,” said Jake Taylor, CEO of Axiomatic AI. “As demand for the hardware underpinning our economy accelerates, machine learning systems must move beyond assistance into accountable collaboration. AI that cannot justify its reasoning, to the level needed for engineering, cannot scale into high-stakes technical domains. Our focus must be on shifting the baseline of technical intelligence to verifiable outcomes that connect to physical reality.”
Axiomatic’s early access program includes several enterprises in the Fortune 100 and 500, including major semiconductor equipment manufacturers, foundries and fabless design organizations, technology companies focused on photonics, as well as engagements with top-tier non-profit research institutions. Axiomatic AI’s long-term ambition is to become the authoritative workflow platform for science and engineering organizations operating in high-stakes domains. As more solvers, constraints, and enterprise workflows are integrated, the platform compounds in value and establishes verification and orchestration as baseline requirements for engineering AI.
“Science and engineering are the backbone of modern civilization. The shift from prediction to provable reasoning will define the next era of AI adoption in critical industries,” said Israel Ruiz, President and General Partner at Engine Ventures. “Axiomatic is building the infrastructure layer that makes that shift possible.”
Axiomatic was founded by a team of globally recognized experts in physics, photonics, and electrical engineering including Dirk Englund, an MIT Professor of Electrical Engineering and Computer Science, Frank Koppens, a Group Leader and Professor at the Institute of Photonic Sciences (ICFO), Joyce Poon, a University of Toronto Professor of Electrical and Computer Engineering, and Marin Soljačić, Cecil and Ida Green Professor of Physics at MIT and MacArthur Fellow. The company is led by CEO Jake Taylor, formerly Assistant Director for Quantum Information Science at the White House and Senior Advisor for Critical and Emerging Technologies at NIST.
"Humanity's greatest achievement– the scientific method– could become sidelined by black-box AI. When we started Axiomatic AI, the core mission was to build a different kind of system–one in which reasoning would be rooted in math, deductive reasoning, and interpretability, so that engineers and scientists are empowered rather than replaced by machines," said Dirk Englund, co-founder of Axiomatic and MIT Professor of Electrical Engineering and Computer Science.
For more information on Axiomatic, or to sign up for beta access or view open career opportunities, visit axiomatic-ai.com. The company will also be presenting at OFC in Los Angeles March 17-21 – email contact@axiomatic-ai.com to coordinate a meeting.
About Axiomatic AI
Founded in 2024, Axiomatic AI builds the infrastructure required for verified engineering intelligence. Its proprietary platform, Axiomatic Intelligence™, integrates frontier models with formal verification and uncertainty quantification to deliver reliable AI for science and critical hardware systems. Axiomatic is headquartered in Cambridge, Massachusetts and backed by Engine Ventures, Kleiner Perkins, Big Sur Ventures, and more. For more information, visit axiomatic-ai.com or follow the company on LinkedIn.
Jake Taylor, CEO
