Deep Research FAQs

Question 1

What is Deep Research and how does it work?

Accepted Answer

Deep Research is an AI-powered multi-agent system that conducts comprehensive research. It uses a Planner to break down tasks and coordinate parallel Workers, integrating various LLMs and external tools to gather information and generate detailed reports.

Question 2

Which large language models (LLMs) are compatible with Deep Research?

Accepted Answer

Deep Research supports any LLM compatible with the OpenAI API, including models from OpenAI's GPT series and OpenRouter, without requiring models that have function call capabilities.

Question 3

Can I integrate custom or external tools with Deep Research?

Accepted Answer

Yes, Deep Research offers a universal MCP (Multi-Agent Communication Protocol) extension, allowing seamless integration of diverse external tools (stdio, streamable, or SSE) by configuring them in the `config.toml` file.

Question 4

What are the main benefits of using Deep Research?

Accepted Answer

Deep Research provides high-performance, asynchronous processing for complex tasks, enables comprehensive research through multi-agent orchestration, and offers flexible LLM and tool integration via simple HTTP and MCP interfaces.

Question 5

Is Deep Research suitable for in-depth data science and machine learning research?

Accepted Answer

Absolutely. Its multi-agent architecture and ability to integrate external data sources via MCP tools make it ideal for conducting thorough, data-driven research in data science, machine learning, and various other fields.

Deep Research

Deep Research

Key Features

Use Cases

Key Features

Use Cases