Mecka AI, a startup that collects human motion data to train humanoid robots, is nearing a significant funding round led by Sequoia Capital at a valuation of approximately $500 million. This new financing comes just three months after the company raised $60 million from Framework Ventures, with participation from Menlo Ventures, SV Angel, and Kindred Ventures.
The company was co-founded in 2024 by four entrepreneurs with diverse backgrounds. Josh Gao and Mogen Cheng, both Canadian, previously built a restaurant fintech startup together. Jason Chong joined Coinbase after the company acquired his crypto exchange. Duy Nguyen, who focuses on operations at Mecka, rounds out the founding team. Notably, none of the four co-founders have traditional backgrounds in robotics.
Mecka’s name derives from “mecha,” a term referring to fictional giant robots controlled by humans. The company’s core business involves collecting real-world physical data that robotics companies and AI labs need to train their models. Mecka pays people to record themselves performing everyday tasks using body sensors and smartphones, capturing activities ranging from making coffee to fixing cars.
The startup’s growth trajectory has been steep. As of early June, Mecka projected it would reach an annual run rate of $100 million by the end of 2026. This aggressive growth reflects the surging demand for physical-world data in the robotics industry, where real-world interactions represent a primary bottleneck for developing general-purpose robots.
Mecka operates in an increasingly competitive landscape of companies providing training data for artificial intelligence systems. While the company hasn’t publicly disclosed its customer list, many robotics companies and AI labs rely on the type of egocentric data collection approach that Mecka specializes in, alongside other methods like teleoperation.
The market for robot training data is attracting substantial investor interest. XDOF, another startup in this space, is nearing a Series B round at a $1.2 billion valuation. Meanwhile, established human-data platforms like Scale AI and Micro1, which initially focused on large language models, are expanding their services beyond LLMs into robotics applications.
