Mecka AI nears $500M valuation in Sequoia-led round for human motion data

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. The precise size of the new round has not been disclosed, and terms are not final and could still change. Mecka AI did not respond to a request for comment, and Sequoia declined to comment.

Founded in 2024 by four entrepreneurs — Canadians Josh Gao, Mogen Cheng, and Jason Chong, alongside Duy Nguyen — Mecka AI pays people to record themselves performing everyday tasks such as making coffee or fixing cars, using body sensors and smartphones. The company's name derives from "mecha," a fictional giant robot controlled by humans. The co-founders, who do not have backgrounds in robotics, identified the lack of physical-world data as the primary bottleneck holding back general-purpose robots, including humanoids.

Mecka aims to do for robotics what Scale AI, Mercor, Surge, and other human data companies have done for large language models. As of early June, Mecka was projecting it would end 2026 at an annual run rate of $100 million, co-founder Gao told Fortune when the startup announced its previous fundraise.

While Mecka has not publicly disclosed its customer list, many robotics companies and AI labs rely on real-world data captured through this egocentric approach, alongside methods like teleoperation. Other startups collecting real-world data for robot training include XDOF, which TechCrunch reported last week was nearing a round at a $1.2 billion valuation, as well as human-data platforms expanding beyond LLMs, such as Scale AI and Micro1.

Why This Matters

The $500 million valuation reflects investor confidence in the robotics data market, which is emerging as a critical layer for training general-purpose robots.
Mecka’s rapid fundraising — two major rounds within months — signals a gold rush for physical-world data, similar to the earlier scramble for LLM training data.
If Mecka hits its projected $100 million run rate, it would validate the business model of paying humans to generate structured robotic training data.

Background

Humanoid and general-purpose robots have advanced rapidly in recent years, but one persistent challenge is gathering enough real-world data to teach them complex physical tasks. While simulated environments help, they cannot fully replace interactions with actual objects and spaces. Companies like Mecka fill this gap by employing people to demonstrate everyday actions, capturing motion data that can then be used to train robotic models.

Key Perspectives

Investors (Sequoia Capital, existing backers): Sequoia is leading the new round at a near-$500M valuation, betting that Mecka’s egocentric data approach becomes essential infrastructure for the robotics industry. Existing investors like Framework Ventures are likely following on. Robotics companies and AI labs: These are the customers — they need high-quality, diverse motion data to train their robots. Mecka’s method offers a scalable alternative to teleoperation or in-house data collection. Critics/Skeptics: Questions remain about data quality, privacy implications of recording people in their homes or workplaces, and whether the egocentric approach can capture enough nuance for complex manipulation tasks. Competitors like XDOF and Scale AI are also vying for the same market.

What to Watch

Whether the round closes at the ~$500M valuation or adjusts given market conditions.
Mecka’s first public customer announcements, which would reveal which robotics companies are using its data.
The trajectory of rival firms like XDOF, which is also raising at a high valuation, indicating potential oversupply or a bubble in robotics data startups.

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