ResearchRabbit helps researchers find papers they would not discover through keyword search. You add a few papers to a collection, and the tool suggests related earlier work, later work that cites them, and papers by connected authors, showing the connections in visual graphs. As you add more papers, recommendations get more specific, which makes it behave like a recommendation engine for research.
Collections keep projects organized, and alerts notify you when new papers match your interests. You can see networks of authors, explore how a field evolved, and export references to managers like Zotero. It is popular with students and academics who are starting a literature review or entering a new topic, and who want something more exploratory than a search box.
ResearchRabbit has been free to use, which made it popular, though plans and features can change, so check the current site. It depends on the quality and coverage of bibliographic databases, and it recommends rather than summarizes, so you still need to read the papers. Litmaps, Connected Papers, and Inciteful offer comparable visual exploration, Semantic Scholar and Google Scholar provide search, and Elicit, Consensus, and SciSpace add AI answers. It suits early-stage exploration.