Mecka AI, a startup that harvests human motion data to train humanoid and general robotics, is in late-stage talks for a funding round led by Sequoia Capital that would value the company at approximately $500 million. Details of the financing, expected soon, are still being finalized. This comes just three months after Mecka secured $60 million in backing from Framework Ventures and multiple venture firms.
Founded in 2024 by a quartet of entrepreneurs including Josh Gao and Mogen Cheng, Canadians who previously built a restaurant fintech company, and Jason Chong—formerly of a crypto exchange acquired by Coinbase—with Duy Nguyen in charge of operations, Mecka was born from the insight that real-world human interaction data is a major hurdle in advancing general-purpose robotics. None of the founders have robotics backgrounds, but they saw an opportunity in capturing everyday tasks—making coffee, fixing cars, etc.—using body sensors and smartphones to train models.
Scaling Toward Revenue
As of early June this year, Mecka projected that by the end of 2026 its revenue run rate would reach $100 million annually. That’s a rapid climb for a company focused on data collection rather than building hardware or finished robots. Mecka hasn’t publicly disclosed its clients, but its approach is part of a broader shift in the robotics industry: labs and startups increasingly depend on “egocentric,” real-world physical data capture, often supplemented by teleoperation and other methods, to train their models.
The competitive landscape includes startups like XDOF, which is itself nearing a $1.2 billion valuation in its own latest round, as well as established players expanding into adjacent spaces like Scale AI and Micro1. All of them aim to provide the data infrastructure that underpins advancements in robotics—much like the foundational human-data services that have driven growth in large language models.
Why This Round Matters
If the deal closes near the $500 million mark with Sequoia leading, it would signal strong investor conviction in robotics-focused datasets and an acceleration of funding flowing toward data-first models for physical-world AI. It also marks rapid value creation for a startup that is barely two years old. Mecka’s previous $60 million round showed early momentum; this one could underline just how hot—and competitive—the race for robot training data has become.
There are still uncertainties. The size of the new round hasn’t been confirmed, and the final terms could shift. Mecka and Sequoia have not offered public comment on the deal.
This isn’t just about valuation. It’s about how the tools that build AI and robotics systems are being reshaped. Mecka’s rise underscores that access to high-quality, real-world data—especially human motion and task-based interactions—is now a crucial bottleneck in robotics. As more labs and companies chase that scarce asset, Mecka’s positioning could give it not only financial leverage but also strategic importance in shaping what kinds of robots and AI-powered physical systems emerge in the years ahead.
