Robot hand startup Proception settles Tesla trade secret suit, announces $11M seed round

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Robot hand startup Proception settles Tesla trade secret suit, announces $11M seed round

Jay Li, a former technical lead on Tesla’s Optimus humanoid robot program, has settled a trade secret lawsuit filed by his former employer and secured an $11 million seed round for his robotics startup Proception. The company is now shipping its first batch of high-dexterity robotic hands to researchers and robotics companies, aiming to become the leading supplier of hands that can mimic human manipulation.

Settlement clears path for Proception’s robotic hand ambitions

Tesla sued Li last year, accusing him of taking proprietary information to launch Proception. The lawsuit was dismissed earlier this month after both parties reached a settlement. Tesla did not respond to a request for comment. Li told Bitcoin World that the experience served as a “resilience test” for his young company. “People say that what doesn’t kill you makes you stronger, right?” he said.

With the legal dispute resolved, Proception is now focused on what Li calls an even harder problem: building robotic hands that function like human hands. The company announced Monday that it has raised an $11 million seed round led by First Round Capital, with participation from Y Combinator and BoxGroup. Proception is also shipping its first batch of “high-dexterity robotic hand” units to customers and opening orders to a wider market.

Why robotic hands are the last mile for humanoid robots

While investment in humanoid robotics has surged, Li believes too little attention has been paid to dexterous manipulation — the ability for a robot hand to grasp, feel, and manipulate objects as a human does. Tesla CEO Elon Musk has publicly called robot hands one of the biggest unsolved engineering problems. 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 and able to do some of the things that humans do.”

Li thinks Proception can achieve that much faster, largely due to its approach to data collection. Most companies training humanoid robots rely on teleoperation: a human wearing a VR headset controls the robot remotely, and the robot learns from those commands. But Li notes that teleoperators receive no tactile feedback from objects the robot touches, and the approach is limited by the number of robots available at any time.

Proception’s data advantage: sensor-packed gloves

Proception’s solution is a glove laden with sensors. Human testers wear the glove and a headset, capturing “human hand interaction data without requiring a robot in the loop,” according to the company. The same glove technology is used as the “skin” on Proception’s robotic hand, which has 22 degrees of freedom and multiple joints per finger. Li says this allows the company and its customers to gather finer, task-specific data that can make robotic hands more accurately resemble human hands.

“You need both hardware and data, and those need to come hand-in-hand to get [dexterous manipulation] to work,” Li said. “A lot of companies solely focus on hardware, or like hardware plus non-scalable data [collection]. We’re working on this highly dexterous hardware plus highly scalable data. We believe that’s a key combination to solve this problem.”

First Round partner Bill Trenchard, who led the investment, echoed that reasoning. “We think they will have the best hand in the market, maybe the most sophisticated hand today, and the underlying data and models to support that,” he told Bitcoin World. “Dexterous manipulation is a very, very, very important part of the whole humanoid story going forward, and as many people have said, it’s sort of the last mile of getting these robots to be truly performant.”

Conclusion

Proception emerges from its legal battle with Tesla not only intact but with fresh capital and a clear product roadmap. The company’s focus on combining advanced hardware with scalable data collection positions it as a potential key supplier in the humanoid robotics ecosystem. Li remains confident that Proception’s technology will eventually attract even his former employer. “I think it will happen,” he said, referring to the possibility of Tesla becoming a customer. For now, Proception is shipping its first hands and betting that solving dexterous manipulation is the key to making humanoid robots truly useful.

FAQs

Q1: What is Proception?
Proception is a robotics startup founded by Jay Li, a former Tesla engineer, that builds high-dexterity robotic hands for use in humanoid robots and research applications.

Q2: Why was Tesla suing Proception?
Tesla accused Jay Li of taking trade secrets from its Optimus humanoid robot program to start Proception. The lawsuit was settled and dismissed earlier this month.

Q3: How is Proception’s robotic hand different from others?
Proception uses a sensor-packed glove to collect human hand interaction data without requiring a robot, then applies the same sensor technology as “skin” on its robotic hand. The hand has 22 degrees of freedom and multiple joints per finger for more human-like movement.

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