We produce high-quality robotics datasets, visual data, and computer use traces that power the next generation of embodied AI and multimodal systems.
Start a ProjectEgocentric human demonstration videos, manipulation trajectories, and VLA-ready datasets for training humanoid robots. First-person POV recordings with action segmentation, natural language descriptions, and JSONL annotations for imitation learning and policy training.
Comprehensive image and video annotation including segmentation masks, bounding boxes, keypoints, temporal tracking, action labels, and before/after transformation pairs.
Screen recordings, UI interaction traces, and desktop navigation datasets for training AI agents that operate computer interfaces.
Bespoke data collection and annotation pipelines tailored to your unique model requirements, edge cases, and domain specifics.
High-quality before/after image pairs spanning exposure correction, color grading, object removal, and style transfer for training diffusion-based editing models.
Comprehensive dataset of human-computer interactions including mouse movements, keystrokes, and screen states for training autonomous computer-using agents.
We believe the quality of AI systems is fundamentally limited by the quality of their training data.
Every dataset we produce is designed to maximize information density and minimize annotation artifacts that confuse models. We partner with research teams to understand model failure modes and design targeted data interventions.
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