Laplace Intelligence, a startup spun out of the University of Michigan, is developing automated red-teaming for robotics and physical AI. The company aims to stress-test systems by deliberately attempting to make them fail in simulation before they are deployed in the real world.
Co-founder and CEO Howie Sun stated that the goal is to help companies discover and fix problems prior to deployment, and to build a foundation of evidence for customers, insurers, and regulators. The startup's approach uses high-fidelity simulations, reconstructed from real-world data, combined with AI agents that continuously search for weaknesses and potential failure points.
Laplace Intelligence is currently generating revenue, primarily from autonomous driving applications, with customers including Texas-based autonomous trucking firm Bot Auto and a major Japanese automotive manufacturer. The company is also involved in a smart city pilot for San Jose, California, in collaboration with Nvidia and T-Mobile, and is in early discussions with partners developing humanoid robotics for warehouses.
Founded a year ago by Sun and chief scientist Henry Liu, Laplace is competing in Startup Battlefield 200 at TechCrunch Disrupt in San Francisco, which took place from October 13-15.