Connected Papers vs Elicit: pricing, features and which to choose

Connected Papers is a visual literature discovery service for researchers, students, and applied scientists who begin with a paper they already know. A user enters an origin paper and receives a map of related research, making the product useful for orientation before deeper reading. It publicly launched after beta in June 2020. Its About page links team profiles but does not state current headcount or funding. A 2022 announcement said the service was building more than 50 graphs per minute and had reached more than two million researchers in the prior year, which are historical company claims. The product remains active and focused on discovery rather than drafting. Its main tradeoff is convenience versus coverage, since a visual neighborhood can clarify a field without representing every relevant publication.

The workflow begins with a paper title or identifier, then Connected Papers analyzes a surrounding corpus and presents a force-directed graph of strongly related papers. Node size indicates citation influence, color indicates recency, and line strength indicates similarity. Prior Works highlights common ancestors, while Derivative Works surfaces later studies and reviews. Multi-origin graphs refine discovery around several seed papers, and saved papers plus history support repeated sessions. This workflow helps students understand intellectual structure, trace foundations, locate later extensions, and find review papers that may be missed by a single keyword query. It also shifts effort from query construction to result interpretation. Each promising item still requires independent reading, source checking, and confirmation that the apparent relationship is substantively relevant.

Connected Papers is a strong choice for orientation, citation chaining, and finding intellectual neighborhoods around a known paper. ResearchRabbit is broader for collections, author following, and ongoing monitoring, Litmaps emphasizes tracking and alerts, and Semantic Scholar provides conventional search; OpenAlex and Inciteful are additional alternatives. Connected Papers is not a complete search system because graph similarity is not keyword recall, corpus coverage is bounded, and the service cannot replace full-text access, screening, duplicate handling, or source verification. Pick it when a visual map is the fastest way to understand a field or extend a seed-paper search. For systematic reviews, use it alongside explicit database searches, inclusion criteria, screening records, and reference checking so visual prominence does not determine coverage alone.

Elicit is made by Elicit Research, PBC, an AI company that grew from Ought and focuses on scientific research and evidence-backed decisions. Its product searches academic literature, organizes papers into tables, extracts information, and guides systematic reviews. Elicit announced a $22 million Series A in February 2025 at a reported $100 million valuation, led by Spark Capital and Footwork. The company said it had more than 400,000 monthly researchers at that time, while its homepage later claimed more than five million researchers. Those figures use different dates and definitions. Elicit is active and has expanded from paper search into reports, routines, libraries, and organizational research workflows. This makes it useful for recurring work where teams need a consistent structure for reviewing literature and recording study details.

A normal Elicit workflow begins with a natural-language research question. Search returns relevant papers, after which the user can inspect titles, abstracts, full text, and extracted fields in a table. The user can add columns describing population, intervention, outcome, method, or another question, then export results. Research Reports automate search, screening, extraction, and report writing around a selected question and template. Systematic Reviews provide setup, paper gathering, title and abstract screening, optional full-text screening, data extraction, and a final report. Users can upload PDFs, import from Zotero, save papers in a library, chat with papers, and use a browser extension for institutional full-text access. In practice, the table format helps reviewers compare studies without moving repeatedly between separate documents or tools.

Elicit is strongest for researchers who need structured literature work rather than a general chatbot answer. It can reduce repetitive screening and extraction, but generated fields still need checking against papers, especially for nuanced methods, contradictory findings, and incomplete full text. Compared with Consensus, Elicit offers deeper table extraction and systematic-review workflows. Compared with SciSpace, it emphasizes structured review automation and research reports. Compared with NotebookLM, it searches a large paper corpus rather than relying mainly on user-uploaded sources. Choose Elicit for repeatable literature reviews, academic teams, and research operations; choose a general assistant for broad web research or creative writing. Its main tradeoff is that users gain review structure while accepting plan limits and the need for expert judgment.