Elicit
The AI research assistant built for evidence — search, screen, and extract at scale.
At a Glance
- Publisher
- Elicit (formerly Ought)
- Coverage
An AI workflow over 125M+ papers (via Semantic Scholar and OpenAlex) that searches, summarizes, screens, and extracts structured data into tables (verify current counts).
- Access
Freemium — a free tier with monthly limits; paid plans for higher volume and systematic-review features.
- Free alternative
- Consensus, Semantic Scholar, plain OpenAlex search.
- Regional
Global, following the open metadata it runs on.
Our Take
Elicit is the strongest of the AI literature tools for structured evidence work — it behaves like a systematic-review engine, pulling findings into extractable tables and screening at a scale humans can’t match, which is why review teams reach for it. Built on Semantic Scholar and OpenAlex, it inherits open metadata’s breadth and its gaps, and, like any LLM tool, it can misread a methods section, so its outputs are a first pass, not a citation. Use it to accelerate screening and data extraction; verify every extracted claim against the source paper before relying on it.
Power Tips
- Use the data-extraction columns to pull sample sizes, methods, and outcomes into a review table.
- Treat AI summaries as triage — open the methods on anything you’ll cite.
- Combine Elicit’s screening with a comprehensive database search for PRISMA-defensible coverage.
Alternatives & Complements
Consensus, Semantic Scholar, Scite, Research Rabbit
Figures last verified: June 15, 2026