Originally published on AI Tech Connect.
What you need to know Text search is a solved problem; video search is not. The moment a product manager asks "let users search our video library by what happens in it" or "let staff ask questions about this footage", most teams reach for the nearest tool they know — caption every frame with a vision-language model, embed the captions, and search those. It demos well and then quietly disappoints, because a frame caption describes what is on the screen and says nothing about what is being spoken, and because it loses the one axis that makes video different from every other document type: time. A video is not a page. It is several streams running in parallel — the visual frames, the speech and audio, the text burnt onto the screen, the metadata around it — all indexed against a clock.…
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