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AI · June 27, 2025

I built an AI-Powered semantic search for Mac

After getting frustrated with macOS's Spotlight search, e.g., typing "driver license" doesn't give me anything unless the file name matches exactly, I thought, why not index my entire Documents folder? This way, I can find that one PDF or image buried deep in subfolders using natural language queries. So I built SmartSearch; it uses SentenceTransformers for embeddings and FAISS for fast similarity search. Best of all, it runs locally on your computer. Github: https://github.com/neberej/smart-search/ Demo:…

I built an AI-Powered semantic search for Mac launched on June 27, 2025 with 6 votes and more than 75% of that year's launches. The site was still online in September 2026, 1 year on.

In plain words

SmartSearch is an AI-powered semantic search tool for Mac that indexes local files and finds documents using natural language queries rather than exact filename matching. It uses SentenceTransformers and FAISS to search through Documents folders and nested files, with results for PDFs, images, and other content. The application runs entirely locally on the user's computer, accessed via a keyboard shortcut, and is available as open-source software on GitHub.

written from the facts on this page · September 2026

From the sources

AI-powered semantic search for Mac. Contribute to neberej/smart-search development by creating an account on GitHub.

There are two portions - backend which does heavy lifting creating embeddings and frontend which communicates using rest APIs. ./install.sh Run ./start-frontend.sh ./start-backend.sh Build (for prod/usage) The following build process creates a .dmg file that can be installed. And then, Ctrl + Space or Cmd + Space shows/hides thefrom github.com

In the maker’s words, at launch

After getting frustrated with macOS's Spotlight search, e.g., typing "driver license" doesn't give me anything unless the file name matches exactly, I thought, why not index my entire Documents folder? This way, I can find that one PDF or image buried deep in subfolders using natural language queries. So I built…

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