Proception is moving from a legal fight with Tesla into a broader push to supply robotic hands for the companies trying to build more capable humanoid robots. The startup, led by former Tesla Optimus technical lead Jay Li, has settled Tesla's trade secret lawsuit and announced new funding as it begins shipping its first products.
A Tesla dispute ends as Proception raises capital
Tesla accused Li last year of taking trade secrets to start Proception. After months of legal exchanges, Li reached a settlement with Tesla, and Tesla dismissed the lawsuit earlier this month. Tesla did not respond to a request for comment in the source article.
Li described the experience as a demanding early test for the company. "I think it's kind of like a resilience test, or pressure test," he told TechCrunch. "People say that what doesn't kill you makes you stronger, right?"
With the lawsuit resolved, Proception announced Monday that it raised an $11 million seed round. First Round Capital led the financing, with Y Combinator and BoxGroup also contributing.
The funding arrives as Proception begins commercial activity around its robotic hand. The company said Monday that it is shipping the first batch of its "high-dexterity robotic hand" to "researchers and robotics companies," while also opening the product to wider orders.
Why robotic hands remain a hard problem
Li is focusing Proception on a specific robotics challenge: making robot hands work more like human hands. He argues that, despite heavy investment and attention across robotics, not enough effort has gone into the details of human-like hand movement and manipulation.
The issue is central to humanoid robots because hands are where many useful tasks become difficult. Moving through a space is one part of the problem; touching, holding, turning, grasping, and adjusting objects with precision is another.
Elon Musk has also pointed to robot hands as one of the major unsolved engineering challenges. Musk has said Optimus robots could begin working in factories in a matter of years, but the broader view described in the source is that human-equivalent robotic hands remain many years away.
Kevin Lynch, the 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 until they are "functional and useful and able to do some of the things that humans do."
Proception's bet: pair hardware with scalable data
Proception's approach combines a robotic hand with a data-collection system built around a glove filled with sensors. Li believes that combination can help the company move faster than teams that rely mainly on traditional teleoperation.
Many companies training humanoid robots use teleoperators. In that setup, a person wearing a virtual-reality headset sees what the robot sees and controls the robot's actions. The robot can then learn from those human commands.
Li sees two limits in that model. First, the human operator does not receive feedback from the objects the robot touches. Second, the amount of training is constrained by how many robots a company can use at a given time.
Proception's glove is designed to collect human hand activity without depending on a robot for every training session. According to Proception's press release, the glove lets Proception and its customers capture "human hand interaction data without requiring a robot in the loop."
The same glove also functions as the sensor-rich "skin" for the robotic hand Proception is developing. The hand has 22 degrees of freedom and multiple joints per finger, which Proception says can support a "wide range of dexterous motions."
The supplier strategy behind the robotic hand
Proception does not appear to be positioning itself as another full humanoid robot company. Li's stated goal is to become the top hand supplier for other companies that do not want to spend the time or resources building their own dexterous manipulation systems.
That strategy reflects a practical split in robotics development. Companies working on humanoids may need advanced hands, but building those hands requires deep hardware work, sensor design, and task-specific data collection. Proception wants to own that layer.
Li argues that the hardware and data have to develop together. "You need both hardware and data, and those need to come hand-in-hand to get [dextrous manipulation] to work. A lot of companies solely focus on hardware, or like hardware plus non-scalable data [collection]," he said. "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, said that pairing helped convince him to back the company. "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 TechCrunch.
Trenchard framed dexterous manipulation as a crucial part of humanoid robot progress. "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."
What comes next for Proception
The settlement removes a major overhang for Proception as it starts shipping hardware and seeking customers. It also leaves Li free to test whether the company's sensor-glove data strategy can help robotic hands improve faster than conventional training methods.
Trenchard also praised how Li handled the lawsuit while building the company. "He was very upfront with us when this came out, and I think the team did an amazing job of keeping their heads down," Trenchard said. "Jay's a very strong leader."
Li remains confident about Proception's prospects, even when it comes to Tesla. After facing what he called Tesla's "hardcore litigation department," he told TechCrunch he would not be surprised if Tesla eventually seeks Proception's help as the startup grows.
"I think it will happen," he said.