The company leverages the expertise of leading research institutions to develop an AI platform that technology organizations can use to design, validate, and deploy complex hardware systems at scale.
Cambridge, Massachusetts, March 9, 2026–(BUSINESS WIRE)–Axiomatic AI, an engineering-focused company building verification standards for 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 provide interpretable and provable inferences for critical and emerging technologies. As engineering complexity accelerates in semiconductors, photonics, and advanced manufacturing, Axiomatic AI is establishing the intelligent infrastructure layer needed to ensure AI operates within the laws of physics. The round was led by Engine Ventures, with additional investors including Kleiner Perkins, Big Sur Ventures, Global Vision Capital, Propagator Ventures, and Liquid 2. Axiomatic will use this new capital to expand its corporate footprint and deepen the integration of its validation platform into complex scientific and engineering workflows.
Axiomatic’s core technology, Axiomatic Intelligence™, is purpose-built for engineering and science. It combines cutting-edge AI models with math- and physics-based validation and domain-specific knowledge that becomes more valuable the more you use it. Unlike traditional AI systems that can produce plausible outputs but cannot verify those outputs against the laws of physics, test assumptions, or quantify uncertainties, Axiomatic Intelligence provides interpretable physics-based reasoning with formal auditability. This allows Axiomatic’s products to automate and orchestrate complex engineering workflows while validating accuracy and consistency at multiple levels, including fundamental physical principles, design principles, and logical reasoning.
Today’s AI can suggest designs. You can’t prove that they follow physics. Even the most advanced generative models require extensive human oversight in high-stakes scientific and engineering workflows, limiting productivity gains and introducing systemic risks. The National Institute of Standards and Technology (NIST) has identified hallucinations and “cheating” as key challenges to securely deploying large-scale language models (LLMs). Engineers and scientists need systems that reflect physical reality and provide formal assurance. Manual verification hurts productivity and increases risk, especially when industries are facing severe labor shortages. In the semiconductor industry alone, the U.S. is already facing a labor shortage, with approximately 160,000 new engineering jobs needed by 2032 to support domestic expansion and support for domestic locations.
“We are defining the standards that science and engineering AI must meet,” said Jake Taylor, CEO of Axiomatic AI. “As demand for the hardware that powers our economy accelerates, machine learning systems must move beyond assistance to responsible collaboration. AI that cannot justify inference to the level required for engineering cannot scale up to high-stakes technology areas. We must focus on moving the baseline of technical intelligence to verifiable outcomes that translate into physical reality.”
Axiomatic’s early access program includes several Fortune 100 and 500 companies, including partnerships with leading semiconductor equipment manufacturers, foundry and fabless design organizations, photonics-focused technology companies, and leading nonprofit research institutions. Axiomatic AI’s long-term goal is to become the trusted workflow platform for science and engineering organizations working in high-stakes fields. As more solvers, constraints, and enterprise workflows are integrated, the platform becomes more valuable and establishes validation and orchestration as baseline requirements for engineering AI.
“Science and engineering are the backbone of modern civilization, and the shift from prediction to provable reasoning will define the next era of AI adoption in critical industries,” said Israel Lewis, President and General Partner of Engine Ventures. “Axiomatic is building the infrastructure layer to enable that change.”
Axiomatic is a collaboration between Dirk Englund, professor of electrical engineering and computer science at MIT, Frank Koppens, group leader and professor at the Institute for the Science of Optics (ICFO), Joyce Poon, professor of electrical and computer engineering at the University of Toronto, and Marin, Cecil and Ida Green Professor of Physics and MacArthur Fellow at MIT. It was founded by a team of internationally recognized experts in physics, photonics, and electrical engineering, including Mr. Soljačić. The company is led by CEO Jake Taylor, former White House assistant director for quantum information science and senior advisor for critical and emerging technologies at NIST.
“Humanity’s greatest achievement, the scientific method, could be sidelined by black-box AI. When we started Axiomatic AI, our core mission was to build a different kind of system where reasoning is rooted in mathematics, deductive reasoning, and interpretability, where engineers and scientists are empowered rather than replaced by machines,” said Axiomatic co-founder and MIT Professor of Electrical Engineering and Computer Science. said Dirk Englund, professor of science.
To learn more about Axiomatic, sign up for beta access or view open career opportunities, visit axiomatic-ai.com. The company will also be speaking at OFC in Los Angeles from March 17-21. Please email contact@axiomatic-ai.com to arrange a meeting.
About axiomatic AI Founded in 2024, Axiomatic AI builds the infrastructure needed for verified engineering intelligence. Axiomatic Intelligence™, a unique platform, integrates frontier models with formal validation and uncertainty quantification to deliver reliable AI for science and critical hardware systems. Axiomatic is headquartered in Cambridge, Massachusetts and is backed by Engine Ventures, Kleiner Perkins, Big Sur Ventures and others. For more information, visit axiomatic-ai.com or follow the company on LinkedIn.
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