Laplace Intelligence scales robot and autonomous vehicle testing ahead of Disrupt 2026 pitch

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Laplace expands robot testing

Highlights

Laplace Intelligence, founded a year ago at University of Michigan, will present its autonomous AI system testing platform at TechCrunch Disrupt 2026 on October 13 in San Francisco.
Laplace’s simulation tool, built atop Nvidia's Cosmos and enhanced with TomTom traffic data, automates red-teaming to identify weaknesses in robotics and autonomous vehicles ahead of real-world deployment.
Laplace has already secured revenue and a modest profit from clients including Isuzu and Bot Auto, while seeking further funding to meet increasing safety demands in physical AI testing.

Simulation platform and startup competition plans

As reported by TechCrunch, Laplace Intelligence is developing automated red-teaming tools that stress-test robotics and other physical AI systems by deliberately searching for weaknesses before those systems are used in the real world.

The company, founded about a year ago out of the University of Michigan by CEO Howie Sun and chief scientist Henry Liu, is among 20 startups competing in Startup Battlefield at TechCrunch Disrupt 2026 in San Francisco. Laplace is scheduled to present on Monday afternoon, October 13.

Its platform combines a high-fidelity simulation rebuilt from real-world conditions with an AI agent designed to probe for failure points. Laplace says the simulation layer is a post-trained version of Nvidia's Cosmos world simulation platform, while live traffic and congestion data from providers such as TomTom help create difficult corner cases for autonomous vehicles and other physical AI agents.

Commercial traction and broader safety demand

Laplace is positioning its technology around a growing need for verifiable safety in robotics, autonomous driving, and smart city systems. The company says the aim is not only to help clients detect and fix issues before deployment, but also to build evidence that customers, insurers, and regulators can trust.

Sun's academic work focused on challenging autonomous driving AI in simulation, and research he published with Liu in 2023 drew interest from autonomous vehicle companies looking to apply those ideas commercially. That research base now underpins Laplace's business model.

Despite being a young company without deep Silicon Valley roots, Laplace says it is already generating revenue and a modest profit. Its named customers include Isuzu and Bot Auto, and the startup is now seeking additional funding to scale as demand grows for safer physical AI testing.

In our earlier article on Canada’s expanded funding for AI adoption and commercialization, we covered Ottawa’s move to add $500 million over five years to the Regional Artificial Intelligence Initiative under the AI for All strategy. We noted that the program targets priority sectors including transportation, manufacturing, and robotics, aiming to help organizations adopt AI responsibly while enabling domestic AI companies to commercialize products, attract investment, and scale.

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