Local Deep Research
AI deep research tool with multi-source search, PDF extraction, and local storage
Overview
Local Deep Research is a self-hosted research assistant that orchestrates multi-source searches across the web, arXiv, PubMed, Wikipedia, and local documents to produce comprehensive, cited research reports. It uses local LLMs via Ollama or remote APIs for synthesis, extracts text from PDFs, and stores all data in encrypted local storage to preserve privacy. It runs as a Docker container or Python package.
Where it falls short of ChatGPT
- Project is relatively new with limited community testing and potentially rough edges
- No real-time collaboration or sharing of research reports
- Search quality depends heavily on the LLM and API keys configured
- No web UI beyond the basic interface; limited customization options
We list the gaps honestly so you can decide if the trade-off is worth owning your data.
Tags
Claim this listing to keep it accurate, add a deploy template, or feature it on relevant pages.
Embed the Local Deep Research difficulty badge in your README — it links back here.
[](https://openreplace.com/local-deep-research)Similar open-source projects
Other self-hostable tools in the same space worth comparing.
Run large language models locally with a simple CLI and REST API
Feature-rich self-hosted chat UI for Ollama and OpenAI-compatible APIs
Modern AI chat framework with multi-provider support and MCP marketplace
All-in-one local AI app with RAG, agents, and no-code agent builder