๐Ÿ“ฐ Key Takeaways

Mecka AI, a startup that collects and analyzes human motion data to train humanoid and other robotic systems, is close to closing a new funding round led by Sequoia Capital at a valuation of around $500 million, according to two people familiar with the matter. This comes just three months after its last round, which raised $60 million and was led by Framework Ventures with participation from Menlo Ventures, SV Angel, and Kindred Ventures. TechCrunch doesn’t yet know the exact size of this round, and the terms haven’t been finalized, so they could still change. Neither Mecka AI nor Sequoia responded to requests for comment.

Mecka AI was co-founded in 2024 by four entrepreneurs with no robotics background: Canadians Josh Gao and Mogen Cheng, who previously built a fintech startup for restaurants; Jason Chong, who joined after his crypto exchange was acquired by Coinbase; and Duy Nguyen, who runs operations and is the only non-Canadian on the founding team. The four noticed a lack of real-world physical data in robotics, and that capturing real interactions is the main bottleneck holding back general-purpose robots, including humanoids. Mecka’s approach (the name is a nod to sci-fi giant robots, “mecha”) is to pay people to record themselves performing everyday tasks โ€” brewing coffee, fixing a car โ€” using wearable sensors and smartphones, essentially replicating what companies like Scale AI, Mercor, and Surge did for LLM human-data collection. As of early June, co-founder Gao told Fortune the company expects to hit $100 million in annualized revenue by the end of 2026. While Mecka AI hasn’t disclosed its client list, many robotics companies and AI labs rely on this kind of “first-person” data alongside other physical data collection methods like teleoperation to train their models. Competitors in the space include XDOF, which was reportedly raising at a $1.2 billion valuation last week, along with Scale AI and Micro1, both of which are expanding from LLM work into robotics data.

๐Ÿ’ฌ JudyAI Lab Take

Mecka AI closing its second round in three months โ€” this time led by Sequoia at a $500M valuation โ€” tells us the money flowing into robot data is accelerating fast.

What stands out here is that none of the four founders came from a robotics background. They spotted the bottleneck instead: general-purpose robots don’t have enough real-world physical data to learn from. So they started paying regular people to record themselves doing everyday tasks โ€” brewing coffee, fixing a car โ€” with wearable sensors and smartphones, essentially porting the Scale AI / Mercor / Surge playbook from LLM human data over to robotics. It’s a good reminder that when an emerging technology lacks foundational data, data collection itself can become a standalone business โ€” you don’t need domain expertise to get in.

For AI builders, it’s worth asking whether your own space has a similar data bottleneck that could be spun off into its own product.

๐Ÿ“… Original Article Info

๐Ÿ”— Further Reading