Robot training data startup Mecka AI nears $500M valuation
Mecka AI, a startup collecting human motion data to train humanoid robots, is reportedly in talks for a new funding round led by Sequoia Capital valuing it at about $500 million, just three months after its previous $60 million raise.
Mecka AI, a startup that gathers and analyzes human motion data for training humanoid robots and other robotics systems, is reportedly closing in on a new funding round led by Sequoia Capital, according to two people familiar with the matter. The deal would value the company at approximately $500 million. The exact size of the new round has not been disclosed, and the terms are not yet finalized.
This potential round comes just three months after Mecka announced a $60 million raise led by Framework Ventures, with participation from Menlo Ventures, SV Angel, and Kindred Ventures. Neither Mecka AI nor Sequoia responded to requests for comment on the new deal.
About the company
Mecka AI was founded in 2024 by four entrepreneurs without prior backgrounds in robotics. Co-founders include 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. The fourth co-founder, Duy Nguyen, is the only non-Canadian on the team and focuses on operations.
The company's name derives from "mecha," a term from fiction referring to giant robots piloted by humans. The founders identified a shortage of physical-world data as the primary bottleneck preventing progress on general-purpose robots, including humanoids. Mecka's approach mirrors what companies like Scale AI, Mercor, and Surge have done for large language models, but applied to robotics.
The startup pays people to record themselves performing everyday tasks — such as making coffee or fixing cars — using body sensors and smartphones. As of early June, Mecka projected it would reach a $100 million annual run rate by the end of 2026. While the company hasn't publicly disclosed its client list, this type of "egocentric" data collection is widely used across the robotics industry alongside other methods such as teleoperation.
Other startups pursuing similar real-world data collection for robot training include XDOF, which was recently reported to be nearing a new round at a $1.2 billion valuation, as well as Scale AI and Micro1, which are expanding their human-data platforms beyond large language models.
