Elicit is an AI research assistant built for academic literature work. Ask a question in plain language and it searches more than 138 million papers, ranks them by semantic relevance, then pulls findings into a structured table you can edit and export. Every extraction shows supporting quotes from the original PDF, so you can check what the AI claims. Researchers in biomedicine, life sciences, environmental science, and social science use it for screening, data extraction, and systematic reviews.

• Semantic Paper Search: Ask your research question in normal language instead of guessing keywords. Elicit ranks results from a corpus of 138+ million papers by conceptual relevance, so you find studies that keyword search misses.
• Evidence Tables with Data Extraction: Elicit reads full papers and fills columns you define, such as population, intervention, outcome, sample size, or study design. What used to take days of manual note-taking becomes a sortable table.
• Source-Grounded Outputs: Every extracted value comes with the supporting quote and an explanation of where it came from. You can audit any number Elicit reports rather than trusting a black box.
• AI-Assisted Screening: Generate screening criteria from your research question, then let Elicit sort papers by how likely they are to meet those criteria. You review and override its inclusion decisions.
• Systematic Review Workflow: Paid plans support PRISMA 2020 guidelines with reproducible, traceable steps and screening at scale, up to thousands of papers on higher tiers.
• Research Agent: On Pro and above, the agent assembles overviews of broad topics and searches past journal articles into clinical trial data and regulatory documents.
• Chat with Your Own PDFs: Upload papers you already have and ask questions against the full text, with answers tied to specific passages.
• Exports, Alerts, and API: Push tables to CSV or BIB for your reference manager, set alerts for new relevant studies, and connect Elicit to your own workflows through the API and MCP server.

• Large Research Database: Search more than 138 million academic papers and 545,000 clinical trials from a single workspace.
• Strong Source Traceability: AI-generated claims include sentence-level citations that point back to the supporting source.
• Flexible Research Workflows: Customize research reports, screening criteria, extraction columns, and review workflows around your project.
• Saves Manual Research Time: Elicit automates parts of paper screening and data extraction, with researchers reporting up to 80% time savings for systematic reviews.
• Useful Free Plan: The basic plan includes unlimited paper search, summaries, paper chat, source viewing, and Zotero import.

• Advanced Features Require a Paid Plan: Research agents, reports, systematic review usage, alerts, and other advanced features are subject to plan-based limits.
• Best Suited to Research-Heavy Work: Elicit is built around scientific literature and evidence-based research rather than everyday web searches.
• Usage Limits Vary by Plan: Higher-volume research workflows and larger systematic reviews require higher-tier plans.

• Scoping a New Research Area: You are entering an unfamiliar field and need to know what has already been studied. Ask your question, scan the top papers with extracted methods and outcomes side by side, and build a working map of the literature in an afternoon instead of a month.
• Data Extraction as a Second Reviewer: Systematic review teams run Elicit in parallel with one human extractor to simulate dual extraction at lower cost. Where both agree, the data is reliable. Where they disagree, a human checks it, which is where the published research says Elicit fits best.
• Screening Papers at Scale: Give Elicit your inclusion criteria and let it rank papers by their likelihood of meeting those criteria. Reviewers can inspect the reasoning, supporting evidence, and override individual decisions.
• Reading Papers Outside Your Specialty: Clinicians and policy analysts upload PDFs they need to understand quickly and ask targeted questions against the full text, getting answers anchored to specific passages rather than a generic summary.
• Keeping a Review Alive: Set alerts on your topic so new studies surface as they publish, then update an existing table instead of redoing the search from scratch.