Mecka AI approaches $500 million valuation for robot training data

Mecka AI, a startup that collects and analyzes human motion data to train humanoid robots and other automated systems, is reportedly nearing a new funding round led by Sequoia Capital at a valuation of about $500 million. The financing follows a $60 million funding round announced just three months prior, which was led by Framework Ventures with participation from Menlo Ventures, SV Angel, and Kindred Ventures.

The terms of the new agreement remain unfinalized and could still change, and the exact financial size of the round has not been disclosed. Representatives for Mecka AI and Sequoia Capital declined to comment on the transaction.

Origins and background

Founded in 2024, Mecka AI was established by four entrepreneurs: Josh Gao, Mogen Cheng, Jason Chong, and Duy Nguyen. While the co-founders did not come from traditional robotics backgrounds, they identified a significant shortage of physical-world data as the primary bottleneck holding back general-purpose robots and humanoid systems.

The startup derives its name from "mecha," a fictional giant robot controlled by humans. Its operational model mirrors the human-in-the-loop data platforms built for large language models by companies like Scale AI. Mecka compensates individuals to record themselves performing everyday tasks—such as making coffee or fixing cars—using body sensors and smartphones.

Market context

Demand for egocentric and teleoperated physical data has grown as robotics developers seek to train robust foundational models for real-world deployment. Mecka previously projected that it would end 2026 at an annual run rate of $100 million.

The broader market for physical training data includes several competitors and parallel efforts. Other startups focusing on real-world data collection for robotics include XDOF, alongside established human-data platforms expanding their scope beyond traditional language models to support physical AI systems.