Mecka AI Raises $60M Series B Led by Sequoia Capital

Mecka AI's $60M Series B round, led by Sequoia Capital, signals growing investor appetite for robot training data as competition intensifies.

Last Updated: October 8, 2026 Editorial Process
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Published on: October 8, 2026

October 8, 2026, (Inside AI) — Robot training data startup Mecka AI has raised $60 million in a Series B round led by Sequoia Capital, with participation from NVIDIA and Microsoft's venture fund M12. The company previously approached a $500 million valuation, according to sources familiar with the matter.

Founded in 2024, Mecka pays individuals to record themselves performing everyday tasks. Workers wear body sensors and use smartphones to capture actions like making coffee or fixing cars. The startup then processes this human motion data to train humanoid and other robots. In essence, Mecka aims to do for robotics what Scale AI and Mercor did for large language models.

The funding round highlights growing investor interest in the infrastructure layer for robotics, as general-purpose robots inch closer to commercial reality. Mecka's approach addresses a critical bottleneck: the scarcity of real-world interaction data needed to make robots reliable in unpredictable environments.

Egocentric Data Collection Sets Mecka Apart

Mecka's method differs from teleoperation, where a human remotely controls a robot to generate training data. Instead, the company uses an "egocentric" approach, capturing tasks from the performer's own point of view. This yields data that is more natural and scalable, according to the company.

Read: China Humanoid Makers Face Challenge of Putting Robots to Work

"We believe the key to unlocking general-purpose robotics is data that reflects how humans actually move and interact with the world," said Josh Gao, CEO and co-founder of Mecka AI. "Our egocentric approach allows us to collect that data at a fraction of the cost of traditional methods."

Gao and co-founder Mogen Cheng previously built a restaurant fintech startup in Canada. Jason Chong ran a crypto exchange that Coinbase later acquired, and Duy Nguyen handles operations. Notably, none of the founders come from a robotics background, a fact that Gao has said forced them to question assumptions and innovate.

The team identified the data bottleneck early. General-purpose robots need massive amounts of real-world interaction data to function reliably. Mecka's solution taps into the gig economy, paying people to perform tasks while wearing sensors. This creates a scalable pipeline of training data that can be tailored to specific industries.

Competition Heats Up in Robot Data Market

The market for robot training data is heating up fast. Competitor XDOF reportedly nears a $1.2 billion valuation for its own Series B. Meanwhile, Scale AI and Micro1 have expanded into robotics data. As a result, the space has become one of the fastest-growing segments in AI infrastructure.

Mecka projects an annual revenue run rate of $100 million by the end of 2026, according to comments Gao made to Fortune. The company plans to use the new funding to scale its data infrastructure and expand into additional industry verticals.

Gao has argued that robotics is nearing an inflection point. Better models, more capable hardware, and growing commercial demand all drive this shift. Yet the key challenge remains the same: scaling real-world experience for machines that must operate in unpredictable environments.

Read: Unitree CEO Says Robots Are Nearing a 'ChatGPT Moment'

Investors seem convinced that Mecka's approach can help overcome that challenge. Sequoia Capital's backing signals confidence in the team's ability to execute, despite their non-robotics background. NVIDIA's participation is also strategic, given its dominance in AI compute and growing interest in robotics.

Mecka's success will depend on its ability to collect diverse, high-quality data at scale. The company currently operates in several verticals, including household chores and automotive repair. It plans to expand into healthcare and manufacturing next.

As robots move from factories to homes and offices, the demand for training data will only grow. Mecka's bet is that egocentric data collection can become the standard. If it succeeds, the company could become a cornerstone of the robotics ecosystem, much like Scale AI did for language models.

For now, the startup remains focused on scaling its operations and delivering on its revenue projections. With fresh capital and strategic partners, Mecka is positioned to capitalize on the coming wave of robotic automation.

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