Less than three months after emerging from stealth, XDOF is in late-stage talks to raise a Series B at a roughly $1.2 billion valuation led by 8VC. The startup, co-founded by UC Berkeley researchers Philipp Wu (CEO) and Fred Shentu (CTO) in 2024, previously closed a $70 million Series A in June with participation from Thrive Capital, Andreessen Horowitz, Lux, and Spark Capital. XDOF wasn’t planning to raise again so soon, but its rapid growth — annualized revenue approaching $50 million — prompted VCs to approach it. Terms are not final and could change.

XDOF builds the data pipelines, collection tools, and annotation systems that frontier AI labs and robotics companies need but cannot easily build themselves, acting as an outsourced data-supply chain for the robotics industry. The company’s foundation came from a research project called GELLO, a low-cost teleoperation system that lets a human operator remotely control a robotic arm to generate training data. That work led to an influential paper and eventually to XDOF, which investors describe as “the Scale AI or Mercor for physical robotics.” Unlike LLMs that trained on internet-scale text, physical robots lack an equivalent real-world dataset, making data collection a critical bottleneck.

XDOF is partnering with UC Berkeley’s AI Research lab to release ABC, what it believes is the largest collection of high-quality robot training data ever assembled. Data is captured via remote robot teleoperation and human collectors wearing sensors to record everyday tasks like folding clothes and flattening boxes. XDOF plans to hire and train teams of data collectors worldwide, including teleoperators and egocentric operators. The startup already works with 20 customers, including several frontier AI labs. Competitors in the space include Mecka AI, as well as human-data platforms like Scale AI and Micro1 expanding beyond LLMs.