Elicit

About Elicit

Elicit is an AI research assistant designed to speed up literature reviews. Instead of opening dozens of papers one by one, you ask a research question in plain language and Elicit searches the academic literature, surfaces relevant papers, and extracts key details into a structured table. For researchers facing a new topic, a systematic review or a grant background section, that shift from reading everything to screening efficiently is the whole point of the tool.

The workflow is deliberately table-first. Each paper becomes a row, and columns capture the information you care about, such as the study population, intervention, outcomes or methods. Elicit can summarise abstracts and full texts, answer questions about a set of papers, and export the results for further analysis. It cites sources for its claims, which matters: in research, an answer without a traceable source is a liability, not a shortcut.

What Elicit does

Elicit searches a large index of academic papers and returns results ranked by relevance to your question, not just by keyword match. You can filter, screen and shortlist papers, then ask Elicit to extract specific fields into columns. This is where it saves the most time in a systematic or scoping review: instead of copying sample sizes, settings and findings by hand from each PDF, you define the columns once and let the tool populate them, then verify the entries that matter most.

It also supports follow-up analysis across papers: summarising what a group of studies collectively says, identifying where studies agree or disagree, and drafting research reports from the screened set. Newer workflows add guided systematic review tools, screening at larger scale, and bibliography exports. The quality of the output depends heavily on the question you ask and the papers you include, so a vague question returns a vague table, and a well-scoped question returns something genuinely useful.

Pricing (checked 31 October 2026)

Elicit offers a free Basic plan for searching and limited extraction, with paid Plus and Pro plans for heavier use. Third-party pricing checks on 31 October 2026 report Plus from about $11 per user per month billed annually, and Pro from about $39 per user per month billed annually, with higher Scale plans for teams; some older listings show Plus at $12 and Pro at $49, so confirm the current ladder on elicit.com/pricing before subscribing. Sources: elicit.com pricing via thetoolsverse.com and aitoolranked.com, checked 31 October 2026.

Use cases

• Running a first-pass literature search on a new research question and screening papers quickly.
• Building a data-extraction table for a systematic or scoping review, with defined columns per paper.
• Summarising a set of papers on one topic to write a background or related-work section.
• Checking what evidence exists for a claim before citing it in a paper or proposal.
• Exporting extracted data to CSV, BIB or RIS for reference managers and further analysis.

Who it suits, and where it falls short

Elicit accelerates screening, but it does not replace judgement. Extracted values can be wrong, especially for nuanced methods or subgroup results, and a table that looks complete can hide a misread paper. That is why verification matters: check the extracted fields for the papers your conclusions actually rest on, and read full texts for key studies rather than trusting summaries alone. The free plan’s extraction limits also run out fast on a real review.

Coverage is another limit. Elicit is strong on published, indexed papers, but it will not find everything in a niche field, grey literature or very recent preprints with the same reliability, so a rigorous review still needs complementary searches. Paid plans are priced per user, which adds up for a team, and the more advanced systematic review features sit on the higher tiers. Used as a screening and extraction assistant with human verification, it is powerful; used as an automatic answer machine, it is risky.

How to get the most from it

Start by writing your research question as precisely as you would for a database search, including population, intervention and outcome where relevant. Define extraction columns before you run a large batch, and test them on five to ten papers first. Export early and keep a copy of your screening decisions, so the review stays auditable. Finally, spot-check extracted numbers against the original PDFs for every paper you plan to cite, because that is where an error costs the most.

Alternatives to consider

For evidence synthesis with an agreement view, Consensus answers questions from peer-reviewed research and shows how studies align. For citation checking, Scite classifies how papers support or contrast a claim, while SciSpace lets you chat with PDFs and explore related papers. For a visual map of a field, Litmaps is a strong complement.

Looking for more options? Browse our full AI writing tools directory, or compare Elicit with the alternatives linked above.

Key features

• Literature search and screening
• Auto-extracted data tables
• Summarization with citations
• Concept mapping
• Free tier