gerra

A multi-modal data platform for physical AI delivers sensor fusion from real-world robot deployments with hardware-synchronized streams and sub-millisecond to nanosecond-precision alignment across vision, proprioception, IMU, audio, and depth, enabling scalable production pipelines from pilot datasets to petabyte-scale data batches. It solves real-world data quality, cross-modal alignment, and failure-mode coverage problems by providing human-verified labels with automated quality checks, distributed annotation infrastructure, unified schemas, zero preprocessing delivery, and ready-to-run training and policy pipelines for imitation learning, foundation-model pre-training, motion capture, and continuous online learning, serving researchers, robotics engineers, ML practitioners, and organizations building physical AI systems.

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