PRODUCTION
INFRASTRUCTURE
Hardware-level synchronization across vision, proprioception, IMU, audio, and depth. Sub-millisecond timestamp alignment with nanosecond-precision Unix epochs.
Human-verified labels with automated quality checks. Distributed annotation infrastructure with inter-annotator agreement tracking.
TECHNICAL
SPECIFICATIONS
TRAINING
PIPELINES
IMITATION LEARNING
Success-labeled trajectories from real robot deployments. Complete state-action pairs with synchronized vision and proprioception. Ready for behavior cloning and inverse RL.
FOUNDATION MODELS
Large-scale multi-modal data across diverse tasks and robot morphologies. Vision-language-action triplets for generalist policy pre-training.
HUMAN-ROBOT INTERACTION
Multi-perspective human motion with 3D pose annotations. First-person and external viewpoints synchronized with body landmark tracking.
PRODUCTION DEPLOYMENT
Real-world failure modes and edge cases from live deployments. Continuous data collection for online learning and policy updates.
SCALE YOUR
TRAINING PIPELINE
Start with sample datasets to validate your approach. Scale to petabyte-batch production with custom collection infrastructure.