Waabi's Physical AI Platform Targets Generalization, Pivoting from Highways to Urban Robotaxis

Raquel Urtasun founded Waabi to address one of the most complex challenges in modern engineering: creating reliable, all-encompassing AI that interacts safely with the unpredictable real world. Her core vision moves beyond building siloed vehicle functions; instead, Waabi developed a 'Physical AI' platform capable of generalized intelligence—treating self-driving vehicles as complex, rolling machines that can adapt their operational model to different environments and form factors.

This platform approach—combining a robust, verifiable end-to-end AI brain with a sophisticated simulation environment—is key. It establishes a highly generalized capability. This contrasts sharply with older industry approaches that often treated autonomy as a set of separate, optimized modules. By betting on a generalized model, Waabi positions its technology to be hardware agnostic and deployable across multiple verticals, proving its viability not just in the controlled loop of a long-haul truck, but in the erratic chaos of city streets and robotaxi fleets.