ResearchRabbit is a generative AI platform designed to help researchers explore academic literature, discover related works, and map connections between studies. It combines machine learning with network-based visualization to assist in literature discovery, citation analysis, and topic exploration.

Primarily aimed at academic researchers, graduate students, and R&D teams, ResearchRabbit supports fields ranging from life sciences and medicine to social sciences and engineering. It integrates with citation managers like Zotero and enables a more exploratory and non-linear approach to research navigation.

Key features include AI-powered paper recommendations, dynamic citation mapping, collaboration tools, and timeline tracking. ResearchRabbit sets itself apart by emphasizing visual exploration and serendipitous discovery, rather than traditional search interfaces.

What are the main features of ResearchRabbit?

AI-powered literature recommendations

ResearchRabbit analyzes papers in your library to suggest related and relevant research.

• Learns from your added publications and updates recommendations as your library grows.

• Suggests papers based on citation patterns, topic similarity, and co-authorship networks.

• Allows browsing by connections rather than static keyword search.

This enables discovery of foundational or emerging research you might not have encountered otherwise.

Dynamic citation and co-authorship maps

One of ResearchRabbit’s core features is its interactive visualization of research networks.

• Generates maps showing how papers cite or are cited by others.

• Visualizes co-authorship networks and academic influence over time.

• Supports expanding nodes to explore related papers interactively.

These maps help users understand the structure and evolution of a research field.

Custom collections and tracking

Users can create and organize collections of papers, with AI continuously monitoring them for updates.

• Track newly published papers connected to your saved collections.

• Automatically receive suggestions for new relevant articles.

• Organize papers by theme, project, or timeline.

This supports ongoing literature review workflows and reduces missed developments.

Collaboration and shared research spaces

ResearchRabbit allows for collaborative research exploration among colleagues and teams.

• Share collections and maps with collaborators.

• View and build on each other’s research paths.

• Useful for labs, academic advisors, and multi-author research projects.

This feature encourages transparency and knowledge sharing across institutions or teams.

Integration with reference managers

The platform integrates with tools like Zotero to streamline citation management.

• Sync your Zotero library to import or export papers.

• Use ResearchRabbit to explore beyond your existing reference lists.

• No need to manage documents manually across platforms.

Simplifies reference tracking without disrupting your existing workflow.

Why choose ResearchRabbit?

• Visual-first approach to discovery: Unlike linear search engines, ResearchRabbit encourages non-linear, visual exploration of research networks.

• Personalized AI suggestions: Recommendations adapt to your interests, projects, and evolving research focus.

• Enhanced literature mapping: Understand how ideas, papers, and authors are connected over time.

• Designed for collaboration: Makes it easy for teams, labs, and advisors to explore and share academic resources.

• Integrates with existing tools: Works alongside Zotero, making it practical for day-to-day academic workflows.