Overview
Elicit is a specialized AI research assistant built by Ought to help researchers search, screen, and analyze academic literature more efficiently. It finds relevant papers, summarizes key findings, extracts structured data into tables, and generates customizable research reports inspired by systematic reviews.libguides.library.
Pricing
Basic / Free
- Free plan with unlimited search across 125–138+ million papers, unlimited summaries, unlimited chat with papers, and up to 2 automated reports per month.
- Includes basic table views with 2 custom columns, source viewing, and Zotero import; ideal for students and light users.
Plus
- Plus plan is about 10–12 USD per month (often listed as 10–12 USD monthly or ~120 USD/year).
- Adds more robust usage (e.g., higher PDF extraction limits, up to 5 table columns, more simultaneous summaries, and unlimited exports to CSV/BIB/RIS) for independent researchers.
Pro / Team / Custom
- Pro plan is around 42–49 USD per month per user, aimed at systematic reviews and professional research teams.
- Team and Custom tiers add volume discounts, data configuration, co-branding of notebooks, custom workflow development, and the ability to screen from ~1,000 papers at a time.
Key Features
- Semantic paper search – Uses embeddings to search across 125–138+ million papers from Semantic Scholar, PubMed, OpenAlex, and more, returning relevant studies for complex research questions.library.
- Systematic review automation – Automates screening, data extraction, and partial report generation for systematic reviews and meta-analyses, delivering up to ~80% time savings.answers.businesslibrary.uflib.
- Paper summarization & data extraction – Summarizes abstracts and full texts, extracts specified variables into tables, and lets users customize columns for structured evidence synthesis.
- Notebooks, tagging & organization – Provides research notebooks, tagging, and custom columns to organize notes, codes, and extracted findings across projects.
- Brainstorming & term suggestions – Helps generate research questions, find related concepts, and suggest new search terms and keywords.
Best Use Cases
- Academic literature reviews – Students and researchers conducting traditional or scoping literature reviews in any discipline.libguides.library.
- Systematic reviews & meta-analyses – Evidence-based fields like biomedicine, social sciences, and education that need rigorous, transparent review workflows.
- Policy, think-tank & NGO research – Analysts synthesizing evidence across large bodies of literature to support reports and policy recommendations.nbt.
- Industry research teams – R&D and market research teams needing fast evidence scans and structured data extraction from academic sources.
- Early-stage project exploration – Researchers exploring new topics, mapping concepts, and identifying gaps in existing literature.
Pros
- ✅ Designed for research, not chat – Optimized for literature review and evidence synthesis with verifiable sources, rather than generic conversation.
- ✅ Huge academic coverage – Searches across 125–138+ million papers and multiple major scholarly databases.
- ✅ Strong automation for systematic reviews – Can significantly reduce time spent on screening, summarizing, and data extraction.
- ✅ Accessible pricing with a solid free tier – Free plan plus low-cost Plus and Pro tiers provide good value for individuals and teams.
Cons
- ❌ Dependent on available metadata/full text – Quality of results can vary when PDFs or metadata are incomplete or behind paywalls.
- ❌ Not a full replacement for human judgment – Researchers still need to assess study quality, methods, and biases; Elicit mainly accelerates the mechanical parts.
- ❌ Focused on academic papers only – Less suited for gray literature, proprietary datasets, or non-academic sources.
Official Website
Elicit – Official AI research assistant: https://elicit.com
Release Date: Elicit was developed by Ought around 2021 as a tool to automate scientific literature review, and later spun out as a for‑profit public benefit corporation while keeping its mission of scaling up good reasoning for scientists.
Last Updated: December 2025