Nomadic provides an understanding layer for Physical AI, helping teams working in robotics and autonomous vehicles make better use of operational data. Its platform ingests multimodal data, including video, LiDAR, radar, telemetry, audio, and robot sensor signals, to uncover failures, safety-critical events, rare scenarios, and gaps in dataset coverage. Teams can investigate why a model or system failed by connecting events to relevant evidence, then turn valuable examples into targeted, training-ready data.

Nomadic’s capabilities include scenario discovery, safety triage, root-cause analysis across modular and end-to-end models, dataset intelligence, and dataset curation. Its tools support use cases such as automotive driving violations and behavior recognition, industrial and humanoid robotics failures, action segmentation and annotation, and construction, infrastructure, aerial, and maritime data workflows. The company also offers SDKs, documentation, and secure deployment options. Nomadic serves autonomous-vehicle developers, Fortune 500 companies, OEMs, Tier-1 suppliers, and robotics teams. Customer examples describe using the platform to find rare events, organize footage, and reduce time spent on manual review, helping engineers focus on diagnosing problems and improving models.