Laplace Intelligence red-teams robots and self-driving cars before they hit the real world
Startup Laplace Intelligence is developing automated red-teaming tools to stress-test robotics and autonomous vehicle AI before they are deployed in the real world. Founded by University of Michigan researchers, the company aims to create a safety foundation that regulators and insurers can trust.
Why it matters
As AI agents move into physical environments, robust safety testing is essential to prevent unpredictable failures that could have real-world consequences.
If there’s one lesson the OpenAI-Hugging Face incident taught us, it’s that AI agents can be unpredictable.
“Imagine if something like that happened in the physical world,” Howie Sun, CEO and co-founder of Laplace Intelligence , told TechCrunch. “AI agents are moving from computers into the real world, and we don’t really want physical AI to fail in the real world.”
Ann Arbor-based Laplace is building automated red-teaming — essentially, stress-testing a system by deliberately trying to make it fail — for robotics and physical AI. The company is betting that the only way to make sure physical AI is safe is to have AI test it.
“Our goal is to help companies discover and fix problems before deployment—and, over time, build a shared foundation of evidence that customers, insurers, and regulators can trust,” Sun said.
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