Recall
Find any file on your machine with a sentence — no tags, no indexing
Expert verdict
Ship
3-1The Panel's Take
Recall is a local-first multimodal semantic search tool that lets you find any file on your computer using natural language — images, PDFs, audio, video, and text — without any manual tagging, folder organization, or metadata. Ask "that invoice from the dentist last spring" or "photo of the whiteboard with the Q3 roadmap" and it surfaces the right file. Under the hood, Recall uses Google's Gemini Embedding 2 to generate semantic embeddings for all your files and stores them in ChromaDB, a local vector database that runs entirely on your machine. Nothing leaves your device. The Raycast extension adds a visual grid UI so you can search from anywhere on macOS without opening a terminal. First-run indexing can take 20-30 minutes for large libraries, but subsequent queries are near-instant. The project is MIT-licensed and built by a solo developer. It's a clear response to the frustration that Spotlight, Find, and Windows Search still rely heavily on filename and metadata matching even in 2026. As Gemini Embedding 2 is free within generous limits, the operating cost is essentially zero for personal use.
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Recall verdict: SHIP 🚀 3 ships · 1 skip from the expert panel Full review: shiporskip.io/tool/recall-local-multimodal-semantic-search-gemini-chromadb
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<a href="https://shiporskip.io/api/badge-click/recall-local-multimodal-semantic-search-gemini-chromadb" target="_blank" rel="noopener"><img src="https://shiporskip.io/api/badge/recall-local-multimodal-semantic-search-gemini-chromadb" alt="Recall Ship verdict on ShipOrSkip" width="360" height="90" /></a>[](https://shiporskip.io/api/badge-click/recall-local-multimodal-semantic-search-gemini-chromadb)<iframe src="https://shiporskip.io/embed/recall-local-multimodal-semantic-search-gemini-chromadb" title="Recall ShipOrSkip verdict" width="360" height="260" style="border:0;border-radius:16px;max-width:100%;" loading="lazy"></iframe>The reviews
“ChromaDB + Gemini Embedding 2 on local files is a setup I'd have spent a week configuring from scratch. Recall packages this cleanly with a Raycast extension that makes it actually usable day-to-day. The MIT license and zero vendor lock-in seal the deal for me.”
“Re-indexing after file changes, cold-start latency on large libraries, and the dependency on Gemini Embedding 2 (which isn't truly offline) are real friction points. Apple Intelligence already does some of this natively on-device. Wait for broader platform support before switching your file workflow.”
“Semantic search for personal files is the foundation for personal AI agents. If your agent can find any piece of information you've ever touched, you unlock genuine memory at human-years scale. Recall is primitive but points at something important.”
“I have 80,000 photos, hundreds of PDFs, and years of Figma exports I can never find. The idea of describing an image or document and having it surface immediately is worth every minute of setup time. This is the dream of local AI finally shipping.”