Research Navigator is an AI-driven tool that automates literature review tasks for researchers, students, and professionals. Leveraging advanced NLP and knowledge graph technologies, it retrieves and filters relevant scientific articles based on user-defined queries. It extracts salient points, methodologies, and results to generate concise summaries, highlights differences across studies, and provides side-by-side comparisons. The platform supports citation export in multiple formats and integrates with existing documentation workflows via API or CLI. With customizable search parameters, users can focus on specific domains, publication years, or keywords. The agent also maintains session-based memory, enabling follow-up queries and incremental refinement of research topics.

Deep Research AI Agent is an open-source Python framework designed for conducting comprehensive research tasks. It leverages integrated web search, PDF ingestion, and NLP pipelines to discover relevant sources, parse technical documents, and extract structured insights. The agent chains requests through LangChain and OpenAI, enabling context-aware question answering, automated citation formatting, and multi-document summarization. Researchers can adjust search scopes, filter by publication date or domain, and output reports in markdown or JSON. This tool minimizes manual literature review time and ensures consistent, high-quality summaries across diverse research domains.

The FactSet Internal Research Notes Extension is designed to integrate with your web browsing, enabling efficient note-taking and entity recognition while you explore content. Users can save important information directly to their Internal Research Notes application, making it easy to gather and organize insights relevant to their work or studies. This tool provides a user-friendly interface that supports seamless integration with FactSet’s powerful data services, effectively streamlining your research workflow.