AI video tagging
ShotMind creates searchable video metadata from the shot clips you choose, helping creators find local footage by what is visible and keep manual tags for the details they want to curate.
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Manual tags capture the details a team chooses to curate. AI-generated descriptions extend that context across footage from many projects, cameras, exports, and generation tests.
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ShotMind analyzes the shot clips you choose and saves descriptions, thumbnails, and a local searchable index in your library. Each selected clip gains richer context for visual search.
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Your files stay where they are while ShotMind adds a searchable layer above the folder structure you already use.
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Recognition quality varies with the shot and its context. Human review keeps client, rights, product, and final creative decisions connected to the original footage.
"symmetrical wide shot, centered subject, cool blue background"
Find detailed visual structure through natural-language search.
"slow push-in on product detail with shallow depth of field"
Search by motion, framing, and visible subjects together.
"tense low-light dialogue shot, over-the-shoulder framing"
Find mood and staging cues across different files.
You import local videos, split them into shots, and choose the clips worth analyzing. ShotMind turns those selected clips into searchable material.
AI descriptions provide broad visual context for faster search, while manual tags hold the project, client, rights, and creative details your team chooses to curate.
ShotMind can describe visible subjects, actions, scenes, composition, lighting, mood, style, and camera movement, then save descriptions and thumbnails in a local searchable index.