FailSim AI is a multi-robot failure analysis platform that helps robotics companies discover why their robots fail before building physical prototypes. Instead of weeks of manual testing, teams can run 1000+ physics-based simulations overnight using PyBullet with real robot specifications (Kuka iiwa7, Franka Panda, UR5, or custom robots). Our platform uses Gemini 3 Flash AI to automatically analyze failure clusters and explain the physical mechanisms causing failures. The system provides interactive features including experiment configuration, real-time 5-frame simulation visualization, failure distribution charts, and click-to-analyze AI insights for individual runs. Built on Vultr infrastructure with a React dashboard, FastAPI backend, and deployed 24/7 at http://80.240.20.49. FailSim AI reduces testing time by 10x, cuts costs by 90%, and enables teams to fix issues in simulation rather than expensive hardware iterations. Perfect for robotics startups, QA teams, and research labs validating designs before real-world deployment.
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