Dragoneye
Turn videos into structured data with zero-shot vision models
Dragoneye is a computer vision platform that turns video into structured data through zero-shot models, removing the need for data labeling or model training. A model is defined by a schema describing what to detect and which attributes to extract, then run on video to return tracked objects with details such as first and last seen time, on-screen duration, and custom attributes.
Models are created through a coding agent using the Dragoneye MCP server with Claude Code or Codex, or through the built-in Playground. Schemas can be revised to add new attributes and rebuilt without retraining. Models run on video via Python and Node SDKs, and results can feed into alerts, reports, and workflows. Pretrained models cover use cases including airport operations, traffic surveys, sponsor exposure, and roadside inventory.
Dragoneye is aimed at developers and teams building video analysis into their products. Pricing is usage-based, with free credits on signup and per-minute video and per-image rates, plus a volume tier with custom terms, discounts, priority support, and beta bespoke model finetuning.
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