Mecka AI Approaches $500M Valuation in Sequoia-Led Round

Motion-capture startup raises capital at rapid pace

Mecka AI, a startup that captures human motion data to train humanoid robots, is closing in on a new funding round led by Sequoia Capital that would value the company at approximately $500 million, according to two sources familiar with the transaction.

The financing arrives just three months after Mecka announced a $60 million round led by Framework Ventures with participation from Menlo Ventures, SV Angel, and Kindred Ventures. The size of the new round has not been disclosed, and deal terms remain subject to change.

Neither Mecka AI nor Sequoia Capital responded to requests for comment on the funding.

Why it matters

The rapid valuation increase reflects investor conviction that physical-world data will become as valuable to robotics as text and image datasets have been to large language models. Companies building general-purpose humanoid robots face a fundamental bottleneck: they lack sufficient examples of how humans actually move through and manipulate the physical world. Startups that solve this data collection problem at scale stand to capture significant value as the robotics industry matures.

Four non-roboticists building the data layer

Mecka AI was founded in 2024 by four entrepreneurs without traditional robotics backgrounds. Co-founders Josh Gao and Mogen Cheng, both Canadian, previously built a restaurant fintech startup together. Jason Chong joined Coinbase after the exchange acquired his crypto company. Duy Nguyen, the only non-Canadian on the founding team, leads operations.

The founders identified a critical gap in the robotics ecosystem: the scarcity of real-world physical interaction data. Their company name derives from "mecha," the science fiction term for giant human-piloted robots.

Mecka pays individuals to record themselves performing everyday activities—making coffee, repairing vehicles, and similar tasks—using body sensors and smartphones. This "egocentric" data collection approach captures human movement from a first-person perspective.

When announcing its previous fundraise in early June, Gao told Fortune that Mecka projected reaching a $100 million annual run rate by the end of 2026.

Growing market for physical-world data

While Mecka has not publicly named its customers, numerous robotics companies and AI research labs depend on real-world data captured through egocentric recording and other methods like teleoperation to train their models.

The startup operates in an increasingly competitive landscape. XDOF, another company collecting physical-world training data, is nearing a funding round at a $1.2 billion valuation, TechCrunch reported last week. Established human-data platforms including Scale AI and Micro1 are also expanding beyond their original focus on large language models into robotics applications.

Mecka's approach mirrors what data labeling and collection companies have built for LLMs—creating the foundational datasets that enable AI systems to learn and improve.

These details were first reported by TechCrunch.