Elicit
Semantic search across 138M+ academic papers with custom extraction fields that auto-populate across a paper set, with sentence-level source citations on every claim.
What it does
Elicit lets you search across more than 138 million academic papers and 545,000 clinical trials using natural language — not just keyword matching. Its core differentiator is structured data extraction: you define custom fields (sample size, methodology, effect size, population) and Elicit automatically populates those fields across your entire paper set. Every extracted data point is linked back to the specific sentence in the source paper it came from.
Best for
Systematic reviews, meta-analyses, and any project requiring structured comparison across many papers. Particularly strong in healthcare, psychology, and social science research where PRISMA-style extraction is standard. The sentence-level citation linking makes it auditable in a way that general-purpose AI tools are not.
Pricing
Freemium. A limited free tier exists for exploration. The full structured extraction workflow requires the Pro tier at ~$49/month.
Pricing history note: Elicit previously offered a Plus tier at $12/month. That plan is no longer available. If you’ve seen older pricing references, this is the reason. Factor the current Pro rate into your project budget, especially for multi-month reviews.
Strengths
- Sentence-level source links on every extracted claim — unusually auditable for an AI tool
- Custom extraction fields you define match your specific research question, not generic categories
- Handles large paper sets (hundreds to ~1,000 papers) systematically
- Covers clinical trials database in addition to academic papers
Limitations
- Structured extraction works best for papers that state values explicitly; it can misattribute results in papers with multiple reported outcomes (e.g., grabbing an unadjusted effect size when you needed the adjusted one)
- Spot-check at least 10–15% of extractions against the original PDF before reporting any numbers
- The $49/mo Pro price point makes it significant for individual researchers vs. funded labs
- Does not replace methodological rigor — if your review requires PRISMA or Cochrane compliance, Elicit speeds the mechanics but doesn’t validate that you followed the standard correctly
How it compares
| vs. | Key difference |
|---|---|
| Semantic Scholar | Semantic Scholar is better for broad initial discovery; Elicit is better for structured extraction once you have a candidate pool |
| Consensus | Consensus is faster for a single-claim spot-check; Elicit is built for multi-paper systematic extraction |
| NotebookLM | NotebookLM synthesizes documents you’ve already chosen; Elicit helps you search, screen, and extract from a much larger set |
→ See full comparison: AI Tools for Literature Review
Related tutorial
Running a Systematic Literature Review with AI — covers the full workflow using Elicit in context with Semantic Scholar, NotebookLM, and Zotero.