Elastic (@elastic) “You've got 10k slides, scans, and screenshots to search. Your first instinct is” — TopicDigg
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You've got 10k slides, scans, and screenshots to search.
Your first instinct is to throw a VLM at it. But a VLM reads one image at a time. Running it across your whole corpus on every query doesn’t scale.
Split the pipeline instead. jina-clip embeds every image into a vector once. At query time, the same model embeds your question and does a similarity lookup.
Jina-VLM only touches the matched slides: a handful of images, not thousands.
Build the index once, then retrieval is instant. The VLM only reasons where it matters.
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