Self-driving cars and warehouse robots rarely fail on everyday scenes. They fail on rare moments like a pedestrian stepping out from behind a van or a worker beside a moving forklift, and those moments are buried in hours of unwatched video. Longtail is a video agent that finds them. You describe a corner case in plain English, and the agent:
- expands it into several searches
- searches the indexed footage three ways: VAST's hybrid search, our own Cosmos-Embed index, and YOLO object detections
- has NVIDIA Cosmos3-Reason watch the best candidates and keep only real matches
Results are ranked by danger (Cosmos's rating) and rarity (embedding distance within each camera pack). Each clip comes with a structured scenario label, "find similar" turns one example into a set, and a coverage map shows which situations are missing and lets the agent fill those gaps. Every run exports a training-ready JSON with clip IDs and start/end times, or a versioned Weights & Biases dataset. It works across real dashcam, highway and street cameras and synthetic warehouse footage.
