In 2024, a team of world-renowned professors from MIT, the University of Toronto, and ICFO Barcelona recognized a fundamental limitation in artificial intelligence: while Large Language Models excelled at language and poetry, they struggled with the rigorous logic required for scientific and engineering applications. Traditional black-box AI couldn't provide the verification and reliability that engineers and scientists needed for mission-critical work in photonics, semiconductor design, and hardware development. This realization sparked the creation of Axiomatic AI - a company built on the belief that AI should empower human reasoning, not replace it.
Axiomatic AI developed Automated Interpretable Reasoning (AIR), a revolutionary approach that combines reinforcement learning, LLMs, world models, and formal verification to create AI systems that prove their own correctness. Rather than generating hallucinated outputs, Axiomatic's platform delivers mathematically verifiable, error-free results by integrating formal proof systems with deep learning. Their mission, dubbed 'Mission 10X30,' aims to achieve a tenfold decrease in the time engineers spend tackling technical challenges by 2030. With backing from Kleiner Perkins and a team spanning Boston and Barcelona, Axiomatic AI is transforming how scientists and engineers approach discovery - enabling faster iteration without sacrificing rigor, and making the world's technical information truly intelligible.