Humanoid robots, autonomous vehicles, and world models all need the same thing: massive, diverse video of real-world physics and human activity. We deliver continuous, task-targeted web video clips + metadata at petabyte scale.
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Whether you're training a robot arm, a self-driving stack, or a foundation world model, the pipeline is the same: discover, extract, deliver.
Task-family targeted video of human manipulation, locomotion, and object interaction. Replace the teleoperation bottleneck with web-scale demonstrations that enable zero-shot generalization.
Diverse driving footage across geographies, weather conditions, and traffic scenarios. Edge cases your simulation fleet can't generate: construction zones, unmarked roads, emergency vehicles.
Rich video of real-world physics for training predictive models that understand how objects move, deform, and interact. The visual prior your world model needs to predict what happens next.
Need a custom scenario pipeline?
Talk to an expert →Three steps from scenario definition to a pipeline-ready video stream.
Specify your target scenarios: task families for robotics, driving conditions for AV, or physical interactions for world models. We map your requirements to discovery filters across our 90 PB Web Archive.
Filter massive web-scale video archives by environment, lighting, camera angle, action type, and more. Surface high-quality demonstrations that match your exact training requirements.
Isolate relevant footage, extract action-specific scenes, and deliver pre-cut, tagged clips optimized for your pipeline. Export to RLDS (TFRecords), LeRobot v3 (Parquet/MP4), or custom formats.
High-granularity filtering across 90 PB of web archives to surface exactly the demonstrations, driving footage, or physical interactions your model needs.
Search and filter through massive web archives to find fresh video sources that match your specific scenario requirements.
Surface new sources through rich, filterable metadata including modality, environment type, camera angle, and domain context.
Pinpoint videos by specific conditions: "rainy highway merges", "low-light kitchens", "industrial assembly lines", or "object collisions".
Simulation has a domain gap. Teleoperation doesn't scale. Fleet data is narrow. Web-scale video gives your model the diversity it needs to generalize.
Expensive. ~$50-100/hour per operator. Limited diversity.
Web video: 1000x cheaper per clip, infinite environmental variety.
Synthetic domain gap. Physics approximations degrade transfer.
Web video: real physics, real materials, real lighting. No sim-to-real gap.
Narrow distribution. Only your vehicles, your routes, your conditions.
Web video: every geography, every weather condition, every edge case.
Bring your target scenarios and throughput requirements. We'll map them to sources and discovery filters so you can deliver a high-fidelity video stream directly into your training pipeline.