Open Researcher's Core Technical Architecture
By combining Firecrawl's web crawling technology and advanced AI inference engine, Open Researcher realizes the whole process of automated processing from data acquisition to intelligent analysis. The real-time nature of the tool is reflected in two key dimensions: firstly, using Firecrawl to perform millisecond web page data crawling to ensure the acquisition of the latest information; secondly, real-time content parsing through the built-in AI model (supporting Anthropic/OpenAI, etc.). This dual real-time processing mechanism reduces the delay from information acquisition to analysis by more than 80% compared to traditional research tools.
Typical examples of technology implementation include: when users search for 'latest advances in quantum computing', the system can complete the whole process of target webpage crawling, content parsing, and key information extraction within 10 seconds, and automatically generate standardized references containing the source URL. The development team used Node.js to build a high-performance back-end service, combined with React to realize a dynamic split-screen interface, and this technology selection ensured the tool's smoothness in both data processing and user interaction.
This answer comes from the articleOpen Researcher: an AI research assistant that analyzes web content in real timeThe
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