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. ## What we capture | | | |---|---| | **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 | ## Open datasets ### 🎬 [EgoViz-120](https://huggingface.co/datasets/humaidtech/EgoViz-120) **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. ## Working with us 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](mailto:info@humaid.co).