Mecka AI, a two-year-old startup that collects and analyzes human motion data to train humanoid robots and other robotics platforms, is nearing a new funding round led by Sequoia Capital at a valuation of about $500 million, according to two people with knowledge of the deal.
The new financing comes just three months after Mecka announced it raised $60 million in a round led by Framework Ventures, with participation from Menlo Ventures, SV Angel, and Kindred Ventures.
Mecka AI was co-founded in 2024 by four entrepreneurs, including Canadians Josh Gao and Mogen Cheng, who previously built a restaurant fintech startup, and Jason Chong, who joined Coinbase after it acquired his crypto exchange. Duy Nguyen, the only non-Canadian on the team, focuses on operations.
None of the co-founders have backgrounds in robotics. But they identified a critical bottleneck in the field: a dearth of physical-world interaction data. Mecka set out to do for robotics what Scale AI and Mercor have done for large language models by paying people to record themselves performing everyday tasks like making coffee or fixing cars, using body sensors and smartphones.
As of early June, Mecka was projecting it would end 2026 with an annual run rate of $100 million.
Other startups collecting real-world data for robot training include XDOF, which is reportedly nearing a new round at a $1.2 billion valuation, as well as Scale AI and Micro1 expanding beyond LLMs into physical-world data. The surge in funding underscores a growing industry consensus: as language model capabilities plateau, the race to build general-purpose robots hinges on who can secure the best physical-world training data pipeline.
