Firesearch – An AI-powered deep research tool developed by Mendable AI

What is Firesearch？

Firesearch is an AI-powered deep research tool developed by the Mendable AI team. It combines Firecrawl’s multi-source web content extraction technology with OpenAI GPT-4o’s capabilities in search planning and content generation. Firesearch breaks down complex queries into multiple sub-questions, conducts targeted searches, and extracts relevant content for each. It supports real-time progress tracking, answer validation (confidence level ≥ 0.7), automatic retries, full citations, and context memory—enabling users to efficiently obtain accurate and comprehensive research results. Built with Next.js 15, it offers a modern React development experience, ideal for users conducting in-depth web research.

Key Features of Firesearch

• Intelligent Search: Breaks down complex queries into sub-questions and performs targeted searches for each.

• Answer Validation: Verifies whether retrieved results truly address the query, only accepting responses with a confidence score of 0.7 or higher.

• Automatic Retry: Automatically retries unanswered queries using alternative search terms, up to two attempts.

• Real-Time Progress Tracking: Updates search progress in real time so users can monitor the current status.

• Complete Citations: Every fact is linked to its original source to ensure traceability.

• Context Memory: Maintains conversational context for follow-up questions, supporting coherent dialogue and deeper research.

• Content Synthesis: Combines all retrieved results into a comprehensive answer and generates potential follow-up questions.

Technical Principles of Firesearch

• Firecrawl: A multi-source web content extraction tool that gathers information from a variety of websites.

• OpenAI GPT-4o: Powers search planning, content generation, and content synthesis, ensuring accurate and coherent answers.

• Next.js 15: A modern React framework with App Router support, providing an efficient frontend development experience.

• Configuration & Optimization: Users can adjust search behavior via the lib/config.ts file—for example, setting the max number of search queries, sources, or minimum content length. Firesearch supports multiple search strategies, such as expanding keywords, narrowing scope, using synonyms, or rephrasing queries to improve search effectiveness.

Project Links

• Official Website: https://tools.firecrawl.dev/firesearch

• GitHub Repository: https://github.com/mendableai/firesearch

Application Scenarios of Firesearch

• Academic Research: Quickly collect literature, organize data, and support academic investigations.

• Market Analysis: Efficiently gather competitor information, analyze trends, and support strategic planning.

• News Reporting: Rapidly collect materials to produce in-depth news coverage.

• Technical Development: Track technological progress and solve engineering problems to support development work.

• Education and Learning: Assist teachers in designing courses and help students complete research and data collection.