Mecka AI, a startup focused on gathering and analyzing human motion data for training humanoid and other robots, is close to securing a new funding round led by Sequoia Capital that would value the company at around $500 million. This potential financing comes just months after Mecka raised $60 million in a Series A round headed by Framework Ventures with additional participation from Menlo Ventures, SV Angel, and Kindred Ventures. Although the deal’s exact size and terms remain unsettled, it underscores the strong investor interest in robot training data as a critical input for advancing general-purpose robotics.

Founded in 2024 by four entrepreneurs—Canadian co-founders Josh Gao and Mogen Cheng, Jason Chong from Coinbase, and operations lead Duy Nguyen—Mecka tackles a notable shortage of real-world physical interaction data necessary for robot learning. The team, coming from fintech and crypto backgrounds rather than robotics, identified this data gap as a key bottleneck. Mecka’s approach involves paying individuals to record everyday activities using body sensors and smartphones, providing material that roboticists use to train smarter, more capable machines.

The startup aims to replicate the success of data-centric companies like Scale AI, Surge, and Mercor, which have similarly transformed AI model development by supplying high-quality human-generated datasets. Mecka anticipates closing 2026 with an annual run rate nearing $100 million, reflecting robust demand from robotics firms and AI labs eager to build smarter robots by leveraging “egocentric” first-person data combined with other collection techniques such as teleoperation. Though Mecka has not publicly disclosed its customer base, its data products are integral to the development of several general-purpose and humanoid robots.

Mecka is part of a broader wave of ventures investing heavily in real-world robot training datasets to overcome development hurdles. Competitors and complementary platforms include XDOF, which recently approached a $1.2 billion valuation, and firms like Scale AI and Micro1, all betting on human-generated data as the foundation for robotics breakthroughs. The surge in funding rounds and valuations highlights the industry’s recognition that sophisticated robotic capabilities require expansive, high-fidelity data capturing human physical actions in natural contexts.