TL;DR
Former Tesla Optimus chief Jay Lee settled a trade secret lawsuit with Tesla and raised $11 million from startup Proception to ship flexible robot hands.
Proception is a robotics startup founded by former Tesla Optimus engineer Jay Lee. It settled a year-long trade secret lawsuit with Tesla and raised an $11 million seed round from First Round Capital to build flexible robotic hands. The company told TechCrunch that it is now shipping the first batch of its highly dexterous hand to researchers and robotics companies, and is taking larger orders. Y Combinator and early-stage fund BoxGroup also participated in the round.
Tesla sued Li and Proception in a federal court in Northern California in June 2025, accusing Li of downloading confidential files related to the robotic arm to personal devices before resigning and founding the startup six days later. The lawsuit claimed that Proception had hands.”striking similarities” to Tesla’s internal designs.After months of litigation, the two sides reached a settlement, and Tesla dismissed the case earlier this month.
Lee told TechCrunch that the experience “strength test or pressure test” and believes the company is stronger for surviving. He also said he wouldn’t be surprised if Tesla eventually came to Proception for help with its hand problem. Tesla did not respond to a request for comment.
Agile manipulation, the ability to grasp, rotate, and manipulate objects with human-like precision, remains one of the most stubbornly unsolved problems in robotics. Even Elon Musk called robotic hands one of the biggest engineering challenges yet to be solved. Kevin Lynch, director of Northwestern University’s Center for Robotics and Biosystems, told the Wall Street Journal last year that his team believes it will be a decade before robotic hands are functional and useful enough to do what humans do.
Li believes that Proception can move faster, largely because of how it collects training data. Most companies that train humanoid robots use teleoperators, where a human wearing a virtual reality headset remotely controls the robot and the system learns from commands. According to Li, the main drawback is that the operator does not receive any tactile feedback from the objects touched by the robot, and the approach is limited by how many robots the company has.
An alternative to Proception is a sensor-laden glove that captures human hand interaction data without requiring a robot in the circuit. The same glove also serves as a sensor-filled “skin” for a Proception-evolving robotic hand with 22 degrees of freedom and multiple joints for each finger. Li argues that this combination of scalable data collection and highly flexible hardware is what the market is missing.
The flexible hand market has attracted significant capital this year. China’s Linkerbot, which holds 80 percent of the global market in highly leveraged hands, is targeting a $6 billion valuation. after shipping more than 1000 units per month. Genesis AI, a European startup, has raised $105 million for a wheeled robot with flexible hands, while Chinese competitors like Xynova have raised nearly a billion yuan.
Most humanoid robot companies are betting on buying hands rather than building them in-house, mirroring how the auto industry treats specialized components. Round One partner Bill Trenchard, who led the investment, told TechCrunch that agile manipulation “the last mile for these robots to really perform.” He also praised Li’s leadership under the pressure of the Tesla lawsuit.
Tesla discussed production of Optimus at the Shanghai Gigafactory and has deployed more than 1,000 Gen 3 devices in its facilities, but the robot’s hands remain its weakest link. Musk set a target price of $20,000 to $30,000 per unit and predicted production would increase to tens of thousands by 2028. Whether Tesla builds its own hands internally or ends up sourcing them from companies like Proception is one of the open questions in the humanoid robot supply chain.
More than 150 companies are now chasing the humanoid robot marketWith a billion-dollar valuation, only 23 percent of partner and enterprise buyers are satisfied with existing products. In this environment, a startup that sells a component that everyone agrees on is the hardest to get right, even at the seed stage. Whether Proception can scale from its first shipping batch to a position that shapes how all categories of machines use their hands is a bet on first-round capital.
