DeepResearch leverages advanced natural language processing to crawl multiple academic sources, extract key findings, and produce structured summaries. It creates interactive knowledge graphs, highlights relevant citations, and generates insights on demand. Users can tag, organize, and export results to citation managers or collaborative platforms. The AI continuously learns user preferences to improve relevance and depth over time, making literature reviews faster and more comprehensive.

Deep Research Agent leverages OpenAI's GPT models to perform advanced document retrieval and analysis. Users configure data sources (e.g., PubMed, arXiv), define queries, and receive digestible summaries highlighting methods, results, and key arguments. It supports multi-document comparison, citation extraction, and interactive Q&A sessions. Modular architecture allows integration of custom connectors, NLP pipelines, and export formats like markdown or JSON. With built-in scheduling, it can periodically update literature reviews, detect new research trends, and generate reports. Ideal for research teams, academics, and industry analysts seeking to reduce manual reading time and improve insight discovery in vast scientific corpora.