XDOF, just three months out of stealth, is in talks for a Series B at a $1.2B valuation
XDOF, a robotics data startup, is in advanced negotiations to raise a Series B round at a $1.2 billion valuation led by 8VC, less than three months after publicly launching. The company's rapid growth toward $50 million in annualized revenue prompted venture capitalists to initiate funding discussions despite the firm having just closed a $70 million Series A in June.
Why It Matters
The speed of XDOF's funding reflects investor confidence in the critical role data infrastructure plays in robotics development. As physical robots lack pre-existing large-scale training datasets unlike large language models, companies that can efficiently collect and organize real-world robot training data have become essential infrastructure for the emerging robotics industry.
Key Facts
- Founders: Philipp Wu (CEO) and Fred Shentu (CTO), UC Berkeley researchers
- Series A funding: $70 million raised in June 2024 from Thrive Capital, Andreessen Horowitz, Lux, and Spark Capital
- Annualized revenue: Approximately $50 million
- Series B valuation: $1.2 billion led by 8VC
- Customer base: 20 customers including multiple frontier AI labs
XDOF has moved remarkably quickly from stealth to significant venture funding. Founded in 2024 by two UC Berkeley researchers, the startup has captured investor attention with its approach to solving a fundamental problem in robotics: the scarcity of high-quality training data. Unlike large language models that benefited from vast amounts of internet text, robots require carefully collected real-world behavioral data that doesn't yet exist at scale.
The company emerged from research conducted by co-founder Philipp Wu, who during his doctoral studies struggled to find sufficient datasets for his robotics research. This challenge led him and Shentu to develop GELLO, an affordable teleoperation system allowing human operators to remotely control robotic arms while recording their actions. Their work produced an influential research paper that became the foundation for XDOF as a commercial venture.
XDOF's business model centers on acting as specialized data infrastructure for robotics companies and AI labs. The startup combines remote robot operation with human operators wearing sensors to capture everyday tasks like clothing folding and box flattening. It plans to build global teams of trained data collectors and has begun releasing ABC, which it describes as the largest curated collection of robot training data yet created, developed in partnership with UC Berkeley's AI Research lab.
The company's trajectory suggests strong market demand for its services. Having raised $70 million in Series A funding just months ago from prominent venture firms, XDOF now finds itself pursued by new investors seeking participation in this round. The $1.2 billion valuation reflects how investors view data infrastructure for robotics with the same strategic importance as earlier generations of data companies that enabled the AI boom.
With 20 existing customers spanning frontier AI labs and plans to expand its data collection workforce globally, XDOF is positioning itself as essential infrastructure in an industry racing to develop general-purpose robots. The company operates within a growing competitive landscape that includes other data-focused robotics startups, though XDOF's UC Berkeley ties and early traction have helped it secure prominent backing.
Keep Reading
First Xiaomi, then the world: why Arm might give phone gaming a huge graphics boost
Eric Wu’s newest company, out of stealth since May, is going after construction’s labor crunch
OpenAI Chief Scientist Warns AI Labs May Need to Slow Down
