They pay because the search only matters if the whole team gets it. A local index that only lives on the editor's machine solves the editor's problem and nobody else's, and the person who most needs to find the clip is usually the one furthest from the storage. Shade sells the index plus the delivery of what the index found, and the second half is the expensive one.
REPLACEMENT BRIEF
audio & video
Can AI replace Shade?
EDITORIAL ANSWERKINDACurated prompt
Walk my drives, pull keyframes and transcripts, embed both with CLIP and whisper into a local vector index, then search the whole library in plain English.
Build the personal version →AT A GLANCE
- price
- $35/mo
- listed annual price
- $420/yr
- replaceable scope
- Walk my drives, pull keyframes and transcripts, embed both with CLIP and whisper into a local vector index, then search the whole library in plain English.
- build time
- multi-day
what AI can build
Walk my drives, pull keyframes and transcripts, embed both with CLIP and whisper into a local vector index, then search the whole library in plain English.
The search half is real and rebuildable. Extract keyframes with ffmpeg, embed them with CLIP, transcribe the audio with whisper, put the vectors in SQLite, and 'the drone shot over the bridge at golden hour' finds the clip on your own drives. The open-source stack for that is mature and the result is genuinely good. What does not survive the port is what Shade has grown into: cloud streaming so an editor opens full-res without waiting on a download, per-link permissions and guest access, review and approval, and a model pipeline that keeps improving without you retraining anything. Solo, on local storage, the DIY version wins outright. On a team, you are rebuilding a platform and calling it a script.
The prompt was editor-reviewed; no completed build is recorded.
The honest tradeoff
why people still pay
what you lose
xcloud streaming of full-res files without downloading them first
xguest links with per-link permissions and roles
xbuilt-in review, approval, and commenting
xface recognition and shot-type tagging that improves without your involvement
xteam sync, so everyone searches the same index
xthe NLE plugins and Slack integration
Start with existing software
prior art · use these instead of building, if you'd rather
EVIDENCE LEDGER
What this page can prove
The verdict judges replaceability. The evidence level records what DeepFeather actually checked.
evidence level
Curated promptThe prompt was editor-reviewed; no completed build is recorded.
Growth · monthly per seat
known limits · cloud streaming of full-res files without downloading them first; guest links with per-link permissions and roles
Build promptreviewed prompt · not run
the prompt
Curated promptBuild me a semantic search engine for my own footage to replace Shade. Requirements: - A Python CLI plus a small FastAPI web UI on localhost. SQLite with sqlite-vec for the vectors and the metadata, one file at ~/FootageIndex/index.db. - `index <folder>` walks the tree, and for every video ffmpeg pulls a keyframe every 5 seconds plus one at each scene cut detected by the ffmpeg scene filter. - Each keyframe is embedded with open_clip (ViT-B/32) and stored with its timestamp. Stills and photos get the same treatment as a single frame. - Audio goes through whisper.cpp for a transcript with word timestamps, chunked into 30-second windows and embedded with sentence-transformers for text search. - The search box takes a plain sentence and searches image and transcript vectors together, returning ranked results as thumbnail, filename, and timecode. Clicking one opens the clip at that exact frame in a player. - Indexing is incremental and resumable, keyed on file path plus mtime plus size, and prints a running count so an overnight run is checkable in the morning. - Everything runs on my machine, models included · no accounts, no cloud, no telemetry, no API keys. Files are read only, never moved or renamed. - Out of scope: face recognition, sharing links, review and comments, and team sync. Do not build auth or a server deployment, this is a single-user local tool. - README: installing ffmpeg and whisper.cpp, first-run model downloads, an honest estimate of indexing hours per TB on CPU versus GPU, and how to reset the index.
Copy or open in an agent
The prompt stays readable first. Choose a launch option when you are ready.
$ open in your agent (prompt prefilled, you press enter) or copy it raw
BUILD FEEDBACK
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questions
Can AI replace Shade?
Possibly for a narrower core workflow, but this catalog judgment is not a verified build. Expected gaps include: cloud streaming of full-res files without downloading them first, guest links with per-link permissions and roles. Validate the prompt against your own acceptance criteria before committing.
How much does Shade cost?
Shade is listed at about $35/month (Growth, checked 2026-07-30), or $420 per year. This is a pricing reference, not evidence of a completed replacement or realized savings.
What do I lose by replacing Shade?
Honestly: cloud streaming of full-res files without downloading them first; guest links with per-link permissions and roles; built-in review, approval, and commenting; face recognition and shot-type tagging that improves without your involvement; team sync, so everyone searches the same index; the NLE plugins and Slack integration. If any of those are load-bearing for you, keep paying.
Is there an open-source alternative to Shade?
Yes — Immich (Self-hosted photo and video library with CLIP semantic search and face recognition already built in. The closest working proof the search half is solved.), PhotoPrism (Self-hosted AI-tagged media library with local indexing and search. Photo-first, but the same pattern.). Using prior art is also a valid exit; the prompt is for when you want it exactly your way.