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Local Deep Research
Local Deep Research is an open-source AI research assistant that performs deep agentic research with multiple LLMs and search engines.
Local Deep Research is an AI-powered research assistant that performs automated, agentic research using multiple language models and search engines. Users ask complex questions, and the assistant searches across the web, academic papers, and private documents, synthesizing everything into a detailed report with proper citations. It supports quick pipeline modes for fast facts as well as autonomous agentic research strategies. Designed for privacy, it runs locally on hardware like an RTX 3090, keeping data encrypted in a personal SQLCipher database secured with AES-256. Users can build searchable knowledge bases from downloaded academic papers and web pages to compound their research over time.
Local Deep Research at a glance
Key features
- Perform automated agentic research
- Search across web, academic papers, and private documents
- Synthesize research into reports with citations
- Build an encrypted searchable knowledge base
- Run fully local on local hardware
- Control egress scope and privacy settings
Use it for
- Conduct deep academic and complex analysis research
- Search private documents alongside the live web
- Extract and index academic papers from ArXiv and PubMed
- Generate cited research reports automatically
Alternatives to Local Deep Research
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- DeepSearcher — Performs evaluation and reasoning based on private enterprise data using various models.
- DeepAnalyze — Automates the entire data science pipeline including analysis and visualization.
- AutoResearch — It provides a stateful, reproducible workflow for automated AI research.
- GPT Researcher — Ranked #1 on Carnegie Mellon's DeepResearchGym benchmark for academic research.
- HyperResearch — Generates verified reports with citations checked against full source texts and a persistent vault.
- Lune — Accesses trusted knowledge from top conference papers for AI agents.
- put·here — It maps every canvas to a real Finder folder, keeping saved files local and accessible.
- LLM Wiki Research — Compiles parallel agent research into source-backed markdown knowledge bases.
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