Snoolink Lens is a desktop media search app for creators and teams. Index your libraries once, then search photos and videos with natural language.
From unorganized media to searchable assets in three clear steps.
Select your media folders and kick off local indexing to make your library searchable.
Use prompts like "sunset drone shot over water" instead of filenames or folder paths.
Open exact moments quickly and move faster in your curation, editing, and publishing workflow.
Designed to reduce search time, recover hidden assets, and speed up publishing.
Search by intent, context, and meaning instead of filenames and manual tags.
Find visually similar media and uncover assets you forgot existed.
Search videos semantically and pinpoint useful moments without timeline scrubbing fatigue.
Keep your media on your machine with local indexing and local search by default.
Set expectations clearly before install to reduce setup friction.
A practical comparison for creators and social teams.
| Capability | Manual Folders | Traditional DAM | Snoolink Lens |
|---|---|---|---|
| Search by meaning | Limited | Partial | Yes |
| Setup effort | High | Medium | Low |
| Local-first privacy | Yes | Varies | Yes |
| Scene-level video retrieval | No | Limited | Yes |
| Large library usability | Poor | Medium | High |
Show users the operational impact, not only feature lists.
Choose your installer and get started in minutes.
Installer: .exe
Installer: Apple Silicon .dmg
SEO-friendly answers about Snoolink Lens desktop app, local indexing, and AI media search.
Snoolink Lens is an AI desktop app for Windows and macOS that scans media folders, indexes image and video metadata, and lets you search with natural language using semantic ranking and practical filters.
Lens is local-first. Local indexing and local search run on your machine with no mandatory cloud upload. Optional cloud indexing can be enabled for richer metadata such as descriptions and OCR text.
Yes. Snoolink Lens supports natural language search across images and videos. Results are ranked using semantic, lexical, and fuzzy signals, and video workflows support scene-level retrieval.
You can tune indexing concurrency with SNOOLINK_INDEX_CONCURRENCY. Lower values can reduce memory pressure, while higher values can improve throughput if your system has enough CPU and RAM headroom.
The current release includes a Windows installer (.exe) and a macOS Apple Silicon build (.dmg). You can always check the releases page for the latest build availability.
Broaden your query, reduce strict filters, and let indexing continue because row-level failures are isolated. If needed, verify dependencies and update to the latest release notes for recent indexing and search fixes.
Install Lens and turn buried footage into reusable content in minutes.