Mecka Raises $60M Series B to Build Robot Data Infrastructure

Robot data infrastructure startup Mecka closed a $60 million Series B led by Sequoia Capital, the company said on October 7, 2026, with NVIDIA, Qualcomm Ventures, Samsung and Microsoft's M12 venture fund joining as new investors.

Existing backers Kindred, Framework Ventures and Neo also participated. Angel checks came from DoorDash founder and CEO Tony Xu, former ServiceNow and Snowflake CEO Frank Slootman, and former Tesla Optimus head Milan Kovac.

The round pushes Mecka deeper into a niche it calls the "data and deployment layer" for robotics — the work of capturing human motion, turning it into training-grade datasets, and wiring the resulting models into real-world operations. Mecka argues that robotics is gated less by algorithms than by the absence of physical-world data.

"Motion, contact, force and geometry aren't on the internet. You can't scrape them, license them or buy them," the company wrote in its Series B announcement.

What does the $60M actually fund?

Mecka said the capital scales its capture hardware fleet, deepens an internal research lab, and accelerates commercial robot deployment. The company designs and manufactures its own multi-sensor hardware and runs capture operations that record human demonstrations in homes and commercial environments.

An in-house team builds the computer vision and multimodal models — covering motion tracking, 3D reconstruction and sensor alignment — that convert raw footage into structured training signal. Mecka reports sub-centimeter hand-pose accuracy on in-the-wild data and lists signal primitives including depth, tactile force, point cloud, surface contour and localization.

How big is the business today?

Mecka said it surpassed $100 million in run-rate revenue in June 2026, within months of starting operations, and projects a $300 million run rate by year-end. The company counts "several of the top frontier robotics labs and multiple Mag 7 companies" among its customers. It did not name them.

Mecka also positions itself as a robotics integrator for enterprises without internal teams, handling hardware, data capture, post-training and ongoing operations. The company says its deployments capture data on site, post-train on it, and improve with every hour of operation — a closed-loop arrangement it calls the Mecka Loop.

What did the EgoVerse study show?

Mecka tested its bet on real-world human demonstration through EgoVerse, a multi-institution transfer study conducted with researchers at Georgia Tech, Stanford, UC San Diego, ETH Zürich, MIT and Meta. The associated paper, first submitted on April 8, 2026, and last revised on July 7, 2026, describes a shared platform for data collection, processing and access.

The current EgoVerse release includes:

• 1,362 hours of human demonstrations
• 80,000 episodes spanning 1,965 tasks
• 240 scenes with 2,087 unique demonstrators

The paper finds that policy performance generally improves with more human data, but only when that data is aligned with the robot learning objective. The author list includes Josh Gao and Jason Chong, Mecka's founders.

Why the trillion-dollar claim?

Mecka argues that physical-world data will become a trillion-dollar market, framing robotics as the largest productivity opportunity ahead. Whether that headline figure holds is a separate question. What is documented is revenue growth from zero to a nine-figure run rate inside a few months, a customer list that includes frontier AI labs, and a round led by one of the most aggressive backers of foundational AI infrastructure.

The financing lands as humanoid and industrial robotics programs at Tesla, Figure and a handful of well-funded competitors hunt for exactly the data layer Mecka is building. The company's next test is whether its integrator model can convert research traction into multi-year enterprise contracts — and whether the trillion-dollar bet on physical data outlasts the current AI capex cycle.