A literature-discovery tool that uses seed papers, recommendations and visual citation networks to help researchers explore related work and organize collections, with an ongoing free tier.
ResearchRabbit helps you explore scientific literature through relationships between papers, authors and references. Instead of treating every search as a disconnected list, it uses selected seed articles to guide discovery and visualize connections. It is particularly useful after you have found a few strong papers and want to understand the surrounding research landscape.
Its role is discovery and organization. A citation network can show a path to relevant work, but it does not establish that every connected study is high quality or supports the same conclusion. Read the papers and record why they matter before moving from a map of relationships to a claim about the state of a field.
Map an unfamiliar field
Trace the development of an idea
Expand a thesis reading list
Share a seminar collection
Official product image. Click to inspect the details.
Choose representative seeds
Explore one direction
Organize decisions
Combine with other searches
Example prompt or task: Start from three papers on a defined research topic. Find related work, inspect earlier and later studies, and build separate collections for core evidence, background and papers still needing review.
This is an editorial task outline rather than a conversational prompt that the product is guaranteed to execute automatically.
The official free plan includes ongoing searches and collections.
ResearchRabbit publishes an ongoing Free tier that includes searches, library collections and collection sharing. The pricing page also sets a limit on the number of seed articles used in a search. That makes the free route useful for focused discovery without implying every scale or control is included.
RR+ adds larger seed sets, advanced search controls and additional organization or research-integrity features. Prices and country-based discounts can differ. Do not interpret a paid discovery plan as access to every publisher’s full-text content.
Yes, an ongoing free offering covers core discovery and collection work. RR+ provides additional capabilities.
Its discovery process is built around seed articles. You can start by locating a relevant paper or bringing in an existing library.
No. A relationship can reflect citation or related subject matter, not agreement or equivalent evidence quality.
Official guides include author exploration. Verify names and relevance before assuming all results belong to one research program.
The official guidance presents it as complementary to library resources. Use other search methods when a comprehensive review is required.
The guide includes a Zotero importer. Check the current import process and the resulting records.
Its strength is finding and organizing literature. The interpretation, argument and final writing still require your own reviewed synthesis.
Explore platforms, inputs and outputs, licensing, and access requirements.
ResearchRabbit is an online literature-discovery service. Its official guides describe search, author exploration, citations, references and library workflows. It works best with a clear research question and a maintained reading record, rather than an ever-growing collection without selection criteria.
Database coverage and recommendation methods influence what appears. New, sparsely cited or differently indexed research may be less visible in a citation network. Complement graph exploration with direct searches when coverage matters, and keep any gaps explicit in your final description of the research process.
Collections can reveal research interests or unpublished project directions. Review sharing controls and keep confidential notes within the audience authorized to see them.
Use the current terms for uploaded references and any associated files. Preserve an independent copy of your accepted bibliography and decisions so your research record does not depend solely on a hosted account.
Reviewed October 3, 2026. Product facts come from the official sources below. Suggested projects, prompts and review methods are FindGoodAI editorial guidance, not measured performance results.
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