Local Deep Research
AI-powered deep research tool with multi-source search (arXiv, PubMed, web), PDF text extraction, and encrypted local storage.
High commit volume, frequent releases and growing activity.
Commit activity more than 96% of tracked projects; popularity more than 77%. How this is calculated.
Commits, last 11 months
| Stars | 9.1k |
|---|---|
| Latest release | v1.10.7 · 28 Aug 2026 |
| Repo updated | 27 Sept 2026 |
| Licence | MIT |
| Built with | Docker, Python |
Is Local Deep Research actively maintained?
Local Deep Research is under active development: 4500 commits landed over the last 11 months, averaging roughly 317 commits a month in the most recent quarter.
The most recent tagged release, v1.10.7, shipped within the last month — a current, installable version exists today.
Local Deep Research ranks #9 of 14 tracked generative artificial intelligence (genai) projects. Several better-maintained options exist in the same category — they are listed below.
What Local Deep Research actually does
Local Deep Research is a self-hosted artificial intelligence tool designed to perform investigations using multiple sources such as academic databases and the web. It extracts text from PDF documents and keeps your data secure using encrypted local storage. The application is packaged for containerised environments and is released under the MIT licence.
Best fit: Researchers and privacy-conscious professionals who need an automated tool to query literature and web sources while keeping their data strictly on local hardware.
Worth knowing: Running local AI models and multi-source search pipelines requires significant local compute resources and hardware acceleration.
Deployment notes
As a containerised Python application, you will typically need to configure persistent volumes for the encrypted storage and set up a reverse proxy to handle TLS termination.
Links
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