The news
Mecka AI funding news: the robot training data startup said on October 7, 2026, that it raised a $60 million Series B led by Sequoia Capital, at a valuation of about $500 million, according to TechCrunch and BetaKit.
Mecka collects human motion data that robot makers use to teach humanoids and other machines how to do physical work. According to TechCrunch, the company pays people to record ordinary tasks, such as making coffee or fixing cars, while they wear body sensors and use smartphones. BetaKit reported that the data comes from homes, kitchens, chemistry labs, metal fabrication shops and leather workshops.
New backers in the round include Nvidia (NVDA), Samsung and the corporate venture arms of Microsoft and Qualcomm (QCOM), BetaKit reported. Existing investors Kindred Ventures, Framework Ventures and Neo also took part, along with individuals including DoorDash co-founder and CEO Tony Xu, former Snowflake and ServiceNow CEO Frank Slootman, and Milan Kovac, the former head of Tesla's Optimus humanoid program.
Mecka was founded in 2024, according to TechCrunch, and BetaKit reported that it is based in Toronto and New York, with most staff in Toronto. The company told BetaKit it surpassed a $100 million annualized revenue run-rate in June and expects to reach $300 million by the end of 2026. Those figures are the company's own and were not independently verified.
BetaKit also reported that Mecka previously raised a $60 million Series A in two parts, $25 million in November 2025 and $35 million in summer 2026, and that it acquired Vancouver-based startup Docula. Mecka describes its goal as building the data and deployment layer for physical AI, a term for AI systems that act in the physical world through robots and machines.
The numbers
- Series B
- $60 million
- Valuation
- About $500 million
- Run-rate passed in June (company)
- $100 million
- Year-end run-rate target (company)
- $300 million
- Founded
- 2024
Why CEOs should care
For companies piloting robots in warehouses, factories or kitchens, the binding constraint is often not the hardware but the data needed to teach it a specific job. Text and images for chatbots could be scraped from the web; videos of a person stripping a wire or loading a dishwasher, with matching sensor readings, mostly cannot. Mecka's round signals that investors think this data will be bought, not collected in-house, by most robot builders.
Operations leaders evaluating robotics vendors should ask where the vendor's training data comes from, how closely it matches their own tasks and environment, and who owns data captured on their premises. Procurement teams should expect data licensing to show up as a separate line item, much as data labeling did for language models.
CFOs and boards should treat the reported run-rate figures with care. They are company claims shared with a news outlet, not audited revenue. The more useful signal is the investor list: Nvidia, Microsoft, Qualcomm and Samsung all have stakes in the robotics stack, and their participation suggests the data layer is becoming strategic for chip and platform companies.
The bigger picture
TechCrunch framed Mecka as an attempt to do for robotics what data-labeling firms such as Scale AI did for large language models. It is not alone. TechCrunch reported that rival XDOF has been in Series B talks at a $1.2 billion valuation, and that Micro1 also operates in the space. Competition for contributors, task coverage and data quality is likely to determine which suppliers last.
What’s next
Mecka has not said publicly how it will spend the new capital beyond its stated mission. Watch whether it reaches its year-end run-rate target, which robotics labs name it as a supplier, and whether larger data-labeling companies move into physical-world data collection.
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