interpretable-ai
(2)
Axiomatic AI
Axiomatic AI is a Cambridge, Massachusetts deep-tech company building AI that engineers can actually trust. It pairs frontier language models with formal mathematical and physics-based verification so that the reasoning behind a design decision can be checked, proven, and traced. Its first commercial focus is photonics and semiconductor engineering - fields where simulations are sophisticated but fragmented and a fabrication error is expensive. Founded in 2024 by a group of MIT and ICFO physicists and led by former White House quantum-policy lead Jake Taylor, the company raised an $18M seed in March 2026 to build what it calls the intelligence infrastructure for verified science and engineering.
Guide Labs
Guide Labs is a San Francisco AI research company building interpretable foundation models - large language and diffusion models that can reliably explain how they reach an answer, trace outputs back to their training data, and be steered without retraining. Founded in 2023 by machine-learning researcher Julius Adebayo and colleagues from the academic interpretability world, the company argues that the black-box status quo is a solvable engineering problem, not an unavoidable cost of scale. Its flagship open-source release, Steerling-8B, is pitched as the first large-scale inherently interpretable language model, and its Clarity platform packages interpretability tools for teams in regulated, high-stakes fields like lending, medicine, and drug discovery.