The data layer for embodied AI
Turn egocentric video into training-ready robotics datasets
We legally source, filter, annotate, and quality-score real-world human video — exported in the format your robot-learning pipeline needs.
The physical world has no Common Crawl.
Language models had the internet. Robot foundation models don't. Collecting robot demonstrations is slow and expensive — while millions of videos already show humans doing real physical tasks. We build the infrastructure that turns that video into structured, trainable robot data.
The pipeline
From raw clip to training-ready episode
Source→Filter→Annotate→Segment→Pseudo-actions→Score→Export
Not raw video. Not generic labels. Training-ready robotics data — hands, objects, task phases, pseudo-action trajectories and quality scores, exported to LeRobot, Parquet/MP4, Hugging Face, or your lab's own schema.
Need data for a physical task?
Tell us what your robot is learning. We'll build a pilot dataset.