VideoDB
Build intelligence for the visual world
VideoDB is a data infrastructure platform for video aimed at teams training and deploying visual AI. It addresses the problem of turning large video archives, live streams and robot recordings into searchable, annotated data: locating model failures, finding relevant episodes, ingesting additional sources, annotating footage and feeding samples back into training runs.
The platform is organized into modular products: video primitives (in-house transcoding, frame tiling, frame-addressable streaming, real-time ingestion and high-throughput pipelines), machine annotation (running proprietary, open-weight or custom models as analyzers with versioned indexes and human QC), episode retrieval (plain-language deep search returning clips and frames, with agents usable from MCP clients or the Python and Node SDKs), and realtime ingestion for live cameras and streams. It reads MCAP, LeRobot, RLDS, RTSP and files in S3, GCS or Azure, and writes Parquet manifests, PyTorch loader adapters and MCAP shards.
Products run as managed packages on VideoDB's cloud or the customer's own infrastructure, and recordings remain in place as the source of truth. The platform is intended for teams processing large volumes of video, including robot labs and camera fleets. An API key and documentation are available for self-directed building, while other inquiries go through direct contact; no free plan, trial or pricing tiers are stated.
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