Proception, Robotics Startup From Ex-Tesla Engineer, Settles Lawsuit and Raises $11M

Proception, Robotics Startup From Ex-Tesla Engineer, Settles Lawsuit and Raises $11M Robotics startup Proception has emerged from a year-long legal fight with Tesla just as it secures fresh funding to push one of the hardest frontiers in humanoid robotics: truly capable robot hands.

Founded in 2025 by former Tesla Optimus technical lead Jay Li, Proception quickly drew fire from his old employer. In June 2025, Tesla sued Li and the company in federal court in Northern California, accusing him of downloading confidential files on robotic hand actuation onto personal devices shortly before resigning and founding Proception six days later. The automaker alleged Proception’s hands bore “striking similarities” to Tesla’s internal designs.

After months of legal wrangling, the two sides quietly reached a settlement, and Tesla dismissed the trade secret case earlier in June 2026. Tesla has not commented publicly on the deal.

Li, meanwhile, has framed the episode as a brutal but clarifying stress test for his young company. He described the lawsuit as “a resilience test, or pressure test,” adding, “People say that what doesn’t kill you makes you stronger, right?”

With the legal cloud lifted, Proception moved quickly to showcase momentum. On June 29, 2026, the startup announced an $11 million seed round led by First Round Capital, with participation from Y Combinator and BoxGroup, to scale production of its high-dexterity robotic hands. The company says it is now shipping its first batch to researchers and robotics firms and opening up to wider orders, aiming to become the “top hand supplier” for humanoid and industrial robots.

Proception’s pitch to investors centers on a different way of teaching robots to use their hands. Instead of teleoperated robots controlled via VR headsets, the startup uses sensor-laden gloves to capture rich human hand interaction data without requiring a robot in the loop, a method it argues is more scalable and closer to human-like manipulation.

Li is betting this approach will help solve what even Elon Musk has called one of robotics’ toughest open problems: making robot hands that can grasp, rotate, and manipulate objects with human-level precision.

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