Causal Labs is a research company developing what it terms general causal intelligence: AI systems designed to predict future outcomes and identify optimal actions to alter those outcomes. Its central technical bet is that physical systems, governed by verifiable cause-and-effect relationships, offer a more reliable foundation for AI than text or images. This approach is embodied in its Large Physics Foundation Model (LPM), a foundation model built on physical systems data.
The company's work sits at the intersection of causal reasoning, physics-based AI, and large-scale modelling, with applications in domains such as weather forecasting and physical systems prediction. It has raised $6 million in seed funding.
The team brings together researchers and engineers with backgrounds in self-driving, drug discovery, and robotics, including prior experience at DeepMind, Waymo, Cruise, Insitro, Nabla Bio, and CERN.
