DataSquirrel

DataSquirrel is self-hosted file intelligence: it indexes the storage you point it at — local folders, NAS mounts and Google Drive — and then lets you find anything in it, without a single byte leaving your machine.

Point it at a folder and it crawls, hashes and catalogues every file it finds. From there, NutFinder searches by name and metadata and narrows results by folder, kind, file type, size or date; a duplicate report shows what you are storing more than once; a storage breakdown shows where the disk actually went. On request — never automatically — a local LLM reads and summarizes a file, a selection or a whole folder, and those summaries become searchable alongside filenames. A chat assistant in the sidebar answers questions about your files from those summaries, cites the files it used so you can click straight through to them, and can run a filtered search itself: ask for your largest videos from this year and it works out the filters. When a file changes, its summary is flagged as outdated rather than silently rewritten; when a file disappears, DataSquirrel tells you instead of handing you a dead path.

Everything runs in Docker on your own hardware: a FastAPI service and a Streamlit interface over PostgreSQL 16 with full-text search and pgvector, with Ollama serving the model. No cloud service, no account, no telemetry. One codebase runs as a four-container install on a laptop or, by configuration alone, adds GPU inference, scheduled scans and monitoring — topology is a deployment choice, never a separate code path.