Back to Solutions

Local Deep Researcher

A fully local web research assistant powered by Ollama or LMStudio-hosted LLMs that generates markdown reports with iterative search and summarization.

Overview

Local Deep Researcher is a fully local web research assistant that uses any LLM hosted by Ollama or LMStudio. It takes a topic and automatically generates a search query, retrieves web results, summarizes them, reflects on knowledge gaps, and refines the search over multiple cycles. The final result is a markdown report with citations, all generated locally and without requiring cloud-based LLM access.

Technologies

  • Fully local research workflow—no cloud dependency
  • Customizable via environment variables and LangGraph Studio
  • Supports Ollama and LMStudio-hosted models
  • Iterative search and summarization for deeper insights
  • Markdown report with source citations and knowledge tracking

Key Features

Local LLM Integration

Seamlessly integrates with local models hosted by Ollama or LMStudio, with configurable endpoints and model names.

Iterative Web Research

Performs a loop of search, summarization, reflection, and refined search to build a comprehensive understanding.

Search Tool Flexibility

Supports DuckDuckGo, SearXNG, Tavily, and Perplexity, with optional API key configuration.

Markdown Output with Citations

Generates a final report in markdown format with citations to all referenced sources.

LangGraph Studio UI

Includes a UI for configuring and visualizing the research flow, with environment variable and runtime controls.

Common Use Cases

Offline or Privacy-Sensitive Research

Ideal for users who require fully local processing due to privacy, confidentiality, or offline constraints.

Technical Documentation and Summarization

Automatically generates research summaries for complex topics with citations from trusted sources.

Academic and Scientific Exploration

Useful for exploring scholarly topics using DuckDuckGo or Perplexity, backed by customizable LLMs.

Developer Experimentation with LLM Workflows

Provides a hands-on example of orchestrating LLMs in a structured loop for iterative knowledge building.

Ready to transform your business?

Let's discuss how our local deep researcher solutions can help you overcome challenges and achieve your business objectives.