Training-Ready Data for Embodied AI and Robotics
We design and operate real-world data programs for embodied AI, robotics, VLA models, and Physical AI. From collection protocol and sensor setup to annotation, quality assurance, and training-ready delivery, every dataset is built around your target tasks, embodiment, and deployment environment.
Our Services
Embodied AI Data Services
Five collection methods designed around task fidelity, environmental coverage, sensor requirements, and deployment goals.
UMI Data Collection
Portable UMI data collection using synchronized cameras, IMUs, and gripper state to capture scalable manipulation demonstrations for imitation learning and VLA models.
Egocentric Data Collection
First-person, multi-sensor data collection for robotics and embodied AI, capturing synchronized video, motion, hand interaction, and task context in real-world environments.
Teleoperation Data Collection
High-fidelity teleoperation data collection with synchronized robot state, actions, vision, force, and task metadata for policy learning and validation.
Human Demonstration Data Collection
Structured human demonstration data captured across real workflows, including actions, object interactions, outcomes, and quality labels for embodied AI training.
Custom Multimodal Data Collection
Custom multimodal datasets combining vision, depth, audio, IMU, force, robot state, and task metadata - designed around your model and deployment requirements.
- End-to-end delivery — collection design, multimodal capture, annotation, quality assurance, and training-ready dataset packaging.
Applications We Support
Our data programs support robot learning across manipulation, mobile robotics, industrial automation, home environments, logistics, and other real-world settings. We define the task ontology, coverage matrix, sensor stack, and acceptance criteria around the conditions your model will face in deployment.