Laplace Intelligence uses AI to red-team robots and self-driving cars
Laplace Intelligence, an Ann Arbor-based startup founded by Howie Sun and Henry Liu, is building automated red-teaming tools for physical AI. The company uses high-fidelity simulations to stress-test robots and autonomous vehicles before they are deployed in the real world. By leveraging a post-trained version of Nvidia’s Cosmos platform, Laplace reconstructs real-world environments, such as…
Key points
- Laplace Intelligence uses AI agents to automatically design failure scenarios for physical AI systems.
- The company uses a post-trained version of Nvidia’s Cosmos for high-fidelity real-world simulation.
- Current customers include Isuzu, Bot Auto, and Nvidia, with a focus on autonomous driving.
The core of the system involves AI agents that automatically design corner cases and failure scenarios to probe weaknesses in physical AI systems. This approach moves away from relying solely on recorded footage or human-designed edge cases, which is particularly important for generalized robotics where real-world data is scarce. Laplace claims its simulations are interactive, with simulated actors reacting realistically to test vehicles.
The startup is currently generating revenue from autonomous driving customers, including Isuzu, Bot Auto, and Nvidia. It is also working with partners on humanoid robotics for warehouses. Laplace is competing in the Startup Battlefield at TechCrunch Disrupt, aiming to raise funds to scale and compete with rivals like Applied Intuition, which has raised $1.2 billion at a $15 billion valuation.
Laplace Intelligence red-teams robots and self-driving cars before they hit the real world
TechCrunch AI · 13 October 2026
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