Turn old footage into a searchable reference library before prompting, storyboarding, or editing. Search for the shot you need by describing what is visible, then use it for prompts, boards, or edits.
AI video prompts, storyboards, and shot lists work better when you can point to concrete visual evidence. The hard part is that useful references are often buried inside old exports, product shoots, or test generations.
Find a remembered visual without scrubbing through long videos.
Collect product details, mood shots, camera moves, and composition references before prompting.
Use your own footage as a practical reference source instead of starting from memory.
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Why folders and editors are slow for this job
Folders help you remember a project. Editors help you cut a timeline. Neither one is designed to search every visual moment inside a long video by what appears on screen.
A filename rarely says which shots contain hands, products, lighting, motion, or mood.
Manual tags become inconsistent once the library grows.
Opening every candidate file in an editor is too slow when you only need references.
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Turn old footage into searchable shots
ShotMind splits local videos into shot-level moments, analyzes selected shot clips, and lets you search those moments by natural language.
Import local footage you own or manage.
Split long videos into individual shots.
Choose the shot clips worth analyzing.
Search by visible subject, action, scene, lighting, composition, movement, or mood.
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Turn references into prompts and boards
After you find a useful reference, translate what is visible into production notes instead of copying the whole clip into a prompt.
Separate subject, action, scene, lighting, camera movement, and mood.
Use the reference shot to brief collaborators, compare generations, or build a storyboard beat.
Keep the surrounding video context available for timing, product details, or client discussions.
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Where it fits with AI video tools
Use ShotMind before Runway, Kling, Luma, Seedance, editing, or pitching. It helps you find the reference; your generation or editing tool still handles production.
Prepare prompts with real visual examples from past material.
Compare generated shots against references from your own library.
Build a lightweight local reference habit without turning every clip into a manual tagging task.
Privacy boundary
Full source videos stay local on your computer.
Only selected shot clips are temporarily sent to cloud AI for analysis.
Temporary cloud copies are removed from active cloud storage after analysis succeeds.
Analysis results and necessary metadata are kept for search and management.
Fit and boundaries
ShotMind is not a replacement for your editing app.
It is not a public stock-footage marketplace.
It is not an enterprise DAM or MAM permission system.
FAQ
Can I use this before Runway, Kling, Luma, Seedance, or similar generation tools?
Yes. ShotMind sits before the generation step. Use it to find reference shots, visual details, motion ideas, or mood examples, then bring those ideas into your AI video workflow.
Does ShotMind generate the video for me?
No. ShotMind helps you find and organize visual references from footage you already have. Your AI video tool or editor still does the generation, editing, color, audio, and delivery work.
Will it upload my full source videos?
No. Full source videos stay local. Only selected shot clips are temporarily sent to cloud AI for analysis, temporary copies are removed from active cloud storage after successful analysis, and analysis results plus necessary metadata are kept for search and management.
Do I have to tag every reference manually?
No. ShotMind reduces manual tagging by generating searchable descriptions for selected shots.
What kinds of references work best?
Visible references work best: product close-ups, actions, locations, lighting, texture, camera movement, mood, composition, and reusable B-roll moments.