Jay Li doesn't recommend getting sued by Tesla while trying to launch a startup. However, he believes his company, Proception, may have come out stronger because of the ordeal. "People say that what doesn't kill you makes you stronger, right," he remarked.

Li, formerly a technical lead on Tesla's Optimus humanoid robot program, was accused last year by his former employer of taking trade secrets to found Proception. After months of legal battles, he reached a settlement with Tesla, which dropped the lawsuit earlier this month. (Tesla did not respond to a request for comment.)

Now free to focus on what he considers an even greater challenge—making robotic hands function like human hands—Proception announced Monday that it has raised an $11 million seed round. The round was led by First Round Capital, with support from Y Combinator and early-stage fund BoxGroup. Proception also revealed that it is shipping the first batch of its "high-dexterity robotic hand" to researchers and robotics companies, while opening up to broader orders. Li's goal is to become the leading supplier of hands to companies that prefer not to invest time or resources in developing what the industry calls "dexterous manipulation."

While robotics has attracted a flood of funding and attention, Li believes not enough has gone into making robotic hands truly mimic human hands. One prominent voice on this challenge has been his former boss, Tesla CEO Elon Musk, who has described robot hands as one of the biggest unsolved engineering problems. Although Musk has suggested Optimus robots could start working in factories within a few years, the general consensus is that achieving human-like robotic hands remains many years off. Kevin Lynch, director of Northwestern University's Center for Robotics and Biosystems, told the Wall Street Journal last year that his team expects it will be a decade before they are "functional and useful and able to do some of the things that humans do."

Li believes Proception can achieve this much faster, largely due to its data collection methods. Most companies training humanoid robots use teleoperators—humans wearing VR headsets who see what a robot sees and control its actions. The robot then learns from these commands. A major drawback, according to Li, is that teleoperators receive no feedback from objects the robot touches. This approach is also limited by the number of robots available at any time. Proception's solution involves a sensor-laden glove. By having human testers wear these gloves along with a headset, Proception and its clients can capture "human hand interaction data without requiring a robot in the loop," as stated in Proception's press release. This same glove also serves as the sensor-packed "skin" for Proception's robotic hand, which features 22 degrees of freedom and multiple joints per finger for a "wide range of dexterous motions." Li says this method allows for finer, more task-specific data collection, enabling the robotic hands to more closely replicate human motion. He also believes it scales better. "You need both hardware and data, and those need to come hand-in-hand to get [dexterous manipulation] to work. A lot of companies solely focus on hardware, or like hardware plus non-scalable data [collection]," he explained. "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 in Proception, cited this as a major reason for backing Li. "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."

Trenchard also praised Li's composure during the lawsuit from his former employer. "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. "I think it will happen," he said.