dexset

About dexset

Robots do not learn from clean theory. They learn from messy reality. dexset is the real-world data layer for robotics and physical AI. We help teams that build humanoids, warehouse robots, industrial automation, and autonomous systems collect, annotate, structure, validate, and deliver the training data their models actually need — captured from the environments where those machines will work. What we do: • Real-world video collection across commercial, industrial, warehouse, residential, and controlled environments • Egocentric and exocentric capture — head-mounted, wrist-mounted, and calibrated multi-camera rigs, frame-synced • Human task demonstrations designed around your model's requirements, with controlled variation and outcome labels • Robotics-specific annotation: bounding boxes, segmentation masks, 21-point hand pose, task states, and failure events • Teleoperation data loops that turn every operator intervention into a training signal • Deliberate failure-case capture — occlusions, mis-grips, slips, clutter — the scenarios that break deployment • ML-ready delivery in COCO, YOLO, Pascal VOC, JSON, CSV, or your custom schema, versioned and validated Every dataset ships with consent records, capture provenance, and quality scores. Our workflows are designed to align with GDPR, UK GDPR, CCPA/CPRA, PIPL, APPI, and LGPD, and our operators and annotators are fairly paid — quality data should never come from exploitative labor. Simulation has value. But deployment needs variation, friction, and unpredictable human behavior. We capture the data robots need to improve: real tasks, real environments, real interactions, real failures.