Physicl announced a $10 million seed funding round led by Inovia Capital with participation from US Venture Partners. The capital will support the company's teams in Paris and San Francisco and fund Studio, its platform for generating synthetic training data for physical AI. Physicl addresses the lack of training data for edge cases in robotics and autonomous systems, such as partially obscured objects or misaligned boxes. The company plans to help AI teams generate high-quality, labeled examples of scenarios where their models fail.
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Company Information
Company
Physicl
About
Physicl is a synthetic data generation platform designed to address the edge-case problem in physical AI by creating controlled training data for robots, autonomous systems, and world models. The company leverages a library of 10,000 environments and 100,000 assets built from real 3D geometry to generate rare failure scenarios that are difficult to capture at scale in real-world conditions. Physicl's Studio application enables researchers to describe failures in plain language and generate variations with precise labels for vision, robotics, and world-model training. Founded by Alex de Vigan, the company has 30 team members across Paris, San Francisco, and New York.
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