Jockey by TwelveLabs - Your entire video library: organized, searchable, understood
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Jockey is the first AI that understands your entire media library across photos and video. It analyzes thousands of hours of footage so you can find and connect people, moments and context across videos. Use it in Claude or ChatGPT, or build with the API/SDK. Ingest YouTube, TikTok and Instagram Reels links; assemble content into MP4s; and create and share video-driven artifacts with playable clips. Every TwelveLabs model upgrade makes Jockey better, without re-integration.
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Congrats for amazing product launch. I want to know your hidden limits and retention policy of data.
Keeping timestamped clips and JSON in the output gives developers something they can actually build on. The ability to revoke shared results is a thoughtful detail too, especially when the footage isn't meant to stay public.
exactly - that's video understanding, as an API. Developers would love it. See docs: docs.twelvelabs.io
Great that Jockey understands my whole photo and video library, so I can describe a clip in plain words and actually find the right footage.
@karimbenkeroum exactly! try for free here: playground.twelvelabs.io/get-started
Congrats @aiden_lee7 and team. Eight launches and still shipping from user feedback is the part I respect most. The social ingestion from YouTube and Reels links is a smart addition; no upload step is exactly the kind of friction people quit on.
Congrats Aiden and the TwelveLabs team on taking Jockey to GA. Pairing your own library with a social corpus of trending Reels and TikToks is the part I want to try, since most video search tools only see what you uploaded. When Jockey explains why a hook works, is that grounded in performance data from the corpus or in Pegasus reasoning about the clip itself, and can a user tell which one an answer came from?
handling thousands of hours of video across chat interfaces is impressive, but does the MCP setup ever run into context window bottlenecks when a query spans too many disparate clips in a massive library??
@sumonmatrix great question. The library itself never goes into the chat's context window. Jockey searches your videos and reasons over the matching clips on our side, and ChatGPT or Claude only gets back the result.
What comes back depends on which of our two answer tools the assistant calls:
jockey_query -- returns a written answer with citations to the clips it used. That answer does go into the chat's context, but its length depends on what you asked for, not on how many hours of video were searched.
jockey_render_response -- shows the answer as an interactive visual inside the chat. The assistant only receives a short status line, so the answer itself adds almost nothing to its context.
Follow-up questions continue the same Jockey session, so the assistant doesn't need to pass earlier results back in.