Deep Research AI Agent is an open-source framework designed to automate every stage of the research process. By chaining web scraping modules, language model-based summarizers, and insight extraction pipelines, it gathers data from online articles, academic journals, and custom sources. It supports GPT-3.5, GPT-4, and other OpenAI models, allowing users to tailor question prompts and memory settings to their needs. After extracting key points and citations, it organizes information into comprehensive markdown or PDF reports. Researchers can extend its capabilities with plugins for database integration, API-based data retrieval, and custom analysis functions. This agent streamlines literature reviews, market research, and technical due diligence, reducing manual effort and ensuring consistent, high-quality outputs.

The AI Researcher agent acts as a virtual research assistant that automates key phases of scientific inquiry. It begins by accepting a user-defined topic and performing automated literature searches across online databases via integrated web search. It then extracts and summarizes the most relevant papers, highlights core findings, and identifies research gaps. Using these insights, the agent generates novel research questions and proposes experimental design outlines. The framework supports customizable task pipelines, allowing users to adjust search parameters, summarization depth, and idea generation strategies. All interactions occur through a simple command-line interface, leveraging Python scripts and OpenAI APIs. Researchers can review, refine, and export results to accelerate literature reviews and early-stage planning.