Axiomatic AI was founded in 2024 on a simple belief: the scientific method, our most trusted engine for discovery, deserves an AI counterpart grounded in the same principles of logic and evidence. At a time when hallucinated outputs undermine trust, we set out to build something different. Drawing on decades of experience in physics, engineering, and computer science, our team combines deep learning with formal logic and physics-based modeling so researchers and engineers can move faster with mathematical certainty.

Our vision is AI that reasons like a scientist, designs like an engineer, and optimizes like a mathematician: a trusted collaborator that lets small teams and individual researchers take on problems that used to require large organizations.

Team

We are researchers, engineers, and entrepreneurs across Boston, Barcelona, and Toronto, with backgrounds in AI systems, scientific machine learning, photonics, and large-scale software engineering.

Leadership

Jake Taylor

Jake Taylor

CEO

Former White House Office of Science and Technology Policy Assistant Director for Quantum Information Science

Co-founder, US Center for AI Standards and Innovation

Dirk Englund

Dirk Englund

CSO

Professor, MIT EECS

Quantum technologies, AI acceleration

Kavitha Buddharaju

Kavitha Buddharaju

Head of Photonics

Co-Founder, Advanced Micro Foundry (AMF)

Silicon photonics, integrated foundry design

Leopoldo Sarra

Leopoldo Sarra

Head of AI Research

Scientific Reasoning, AI4Science

Scientific Discovery, Machine Learning for Physics

Advisors

Marin Soljačić

Professor, MIT Physics

Nanophotonics and AI

MacArthur genius fellow

Frank Koppens

Professor, ICFO Physics

Photonics and Quantum Technologies

Joyce Poon

Professor, U of Toronto ECE

Integrated photonics for computing & neuroscience

Backed by leading investors

In the news

Join Our Team

We are looking for people passionate about bringing AI to science and engineering. Explore our open positions.