Leverage Physical Superintelligence, with real-world data.
humaid.co · LinkedIn · GitHub · info@humaid.co
We collect real-world egocentric demonstration data for robotics — across manufacturing, warehouse, hospitality and food-service environments. Trained operators wear calibrated multi-sensor rigs on real jobs, and we run the whole pipeline from capture through annotation, quality control and delivery.
Not lab data. Not scripted. People doing their actual work.
| Egocentric | Stereo RGB-D, global shutter, 1920×1200 @ 30 fps |
| Wrists | Dual wrist cameras, synchronized |
| Depth | 16-bit, losslessly compressed |
| IMU | ~200 Hz, head and both wrists |
| Hands | 21-keypoint 3D model per hand |
| Labels | Temporal action segmentation + natural-language descriptions |
| Format | MCAP, every signal on a shared clock |
120 hours · 5,392 clips · 7.25 TB · CC-BY-4.0
Synchronized egocentric demonstrations of real cleaning, cooking and facility work. Stereo ego video, two wrist cameras, depth, three IMUs, 3D hand pose and frame-level action labels, in a single self-contained MCAP per clip.
We build custom datasets against a spec: environments, tasks, sensor configuration, annotation schema and volume. 50+ companies served, 12+ countries, 55,000+ operators across our partner networks.
If you are training manipulation or humanoid policies and the bottleneck is real-world data, get in touch — info@humaid.co.