Maxinsights pays people to wear cameras while they cook, clean and work. The Santa Clara startup has now raised $30M in seed funding to turn that footage into training data for robots. Peak XV led the round, the company announced on Thursday. Tola Capital, South Park Commons, INCE Capital and Alumni Ventures also took part.
It launched two products alongside the round. MaxLoop is software that checks footage as it arrives. MaxGlove is a sensor glove that records how hard a hand grips. Founder and chief executive Yuguang Yuan explained the bet to John Koetsier at Forbes.
“Language models learned to write by reading the internet, which people spent decades filling with text. Robots have nothing like that. There’s no archive of people loading dishwashers from a first-person view with their hands in frame,” Yuan told Forbes.
Cameras on 5,000 contractors
More than 5,000 contractors in six countries wear the company’s head, wrist and chest cameras. They film themselves loading dishwashers, making smoothies or washing cars. Local staffing firms hire them, and Maxinsights manages them directly.
The company says it records real work at natural speed in homes, restaurants and hotels. Rivals stage tasks in mock settings and ask operators to slow their hands down, it says.
Maxinsights says it has captured more than 2 million hours of footage. Of those, 1.5 million hours are ready for models. It has more than 30 customers, including frontier AI labs, and eight are on recurring contracts.
The data behind Genesis AI and Dyna
The startup says it supplied all 200,000 hours of first-person data behind GENE-26.5, the latest model from Genesis AI. Genesis was in talks to raise about $500m for its robot software in July. Maxinsights also calls itself the largest data provider behind Dyna-2, a model from Dyna Robotics.
“Robots need to learn from the complexity and variation of everyday life, and carefully controlled datasets alone cannot capture that,” Genesis AI co-founder Johnson Wang said in a statement.
The two companies are building MaxGlove together. It records grip force, object weight and how contact shifts during a task, in sync with the video. Gloves already on sale need long calibration, Maxinsights says. They give only 10 to 20 minutes of usable capture a day. The company wants 1 million hours of force data in 2027.
MaxLoop scores each clip as it lands. It checks that the operator is working, that the cameras sit properly and that the task gets finished. Operators now hear back the same day, not one to two weeks later. The company puts the drop in review costs at roughly 80%. Its release says the human review team shrank by 90%. It processes about 450,000 hours of footage a month.
How much footage robots need
Investors put $47.4bn into physical AI in the first half of 2026, according to Crunchbase. That is nearly four times the total for the second half of 2025. The data to train those machines is scarcer.
Others are chasing the same gap. NEURA Robotics is building gyms to train robots. Encord raised €50M in February for its own data platform, and Enigma raised a $70M seed round to let people online control its robots. Figure pays people to film their chores through a programme called Index. Yuan told Forbes that Index serves Figure’s own models, while Maxinsights sells to many companies.
He also told Forbes that robots able to adapt as people do may need ten million hours of data or more. Not everyone agrees on that scale. At least one startup has raised money on the bet that robots will not need that much real-world data, Forbes noted. Yuan said customers are telling him demand is rising sharply.
“Almost every company in this category is selling hours. Maxinsights is the only one that treated quality control as an engineering problem rather than a staffing cost,” said Rohit Agarwal, managing director of Peak XV.
Yuan previously co-founded Mega Gear Robotics, which another company bought. Chief technology officer Kun Wang was an early engineer at Google X and Waymo. He then co-founded QCraft, a self-driving company. Maxinsights has offices in China and Indonesia and plans to open in Turkey and Mexico. Within about two years, Yuan told Forbes, he expects customers’ models to feed back into what the company collects and tests.