Undermind vs Elicit: pricing, features and which to choose

Undermind is an AI research agent for scientific literature, founded in 2023 by quantum physics PhDs Joshua Ramette and Tom Hartke. The company joined Y Combinator’s Summer 2024 batch and is based in San Francisco. Its target users include research scientists, doctors, and R&D teams facing narrow questions that keyword search can miss. Undermind says scientists from thousands of research institutions use the service, and its enterprise page identifies more than 1,000 GSK scientists as users. The founders describe the product as a search engine rebuilt around adaptive exploration, with large language models directing searches through scientific literature instead of matching terms alone. The company does not publish a funding total.

A typical search begins with a natural language research goal. Undermind asks follow-up questions, then reads and evaluates papers, follows citation trails, and continues exploring related authors and work. Users can iterate on reports, inspect full texts, extract details, generate custom tables, and trace statements through inline citations to source papers. Workspaces support shared research, paper libraries, and saved files. The service also offers alerts for new findings in selected areas. The company says a production deep search stops after about 2.9 minutes on average. That delay is deliberate: Undermind is designed for difficult discovery and evidence gathering, not for instant answers to routine questions.

Undermind fits researchers who value broad discovery and citation trails over speed. Elicit is a stronger choice for structured extraction and paper comparison, Consensus is better for concise evidence summaries, and SciSpace is better suited to explaining individual PDFs. Undermind is also a poor fit for general web research or teams seeking a self-serve public API, because API access is presented as an enterprise feature. Individual terms restrict use of the site and functionality to personal, noncommercial use, although insights may be used in commercial or professional research. Enterprise terms address proprietary data, model training, provider retention, and deletion. Choose Undermind for complex scientific discovery, then verify important findings against the cited papers. Its pricing separates academic subscriptions from commercial research subscriptions.

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.