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Elicit searches and summarizes over 125 million academic papers, extracting findings into structured tables so you can review the literature on a research question faster.

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Elicit is a Research Assistants tool. Elicit searches and summarizes over 125 million academic papers, extracting findings into structured tables so you can review the literature on a research question faster. Key features include Semantic paper search, Data extraction into tables, and Sourced summaries and systematic review workflow. Best for graduate students, researchers and academics.

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About

About Elicit

Elicit is an AI research assistant built by Ought that lets you search across more than 125 million academic papers, summarize them, and extract data into structured tables. It is aimed at students, researchers, and anyone doing literature reviews, with every claim linked back to the source paper.

Capabilities

Key Features

Semantic paper search.

Elicit searches over 125 million papers using meaning-based matching rather than keywords, so you can find relevant studies even when you don't know the exact terminology.

Data extraction into tables.

Its AI pulls specific details from papers, such as sample size, methods, and outcomes, into structured columns so you can compare many studies side by side instead of reading each one in full.

Sourced summaries and systematic review workflow.

Every AI summary and table cell links to the source paper with supporting quotes, and the systematic review tools follow PRISMA 2020 guidelines for traceable, reproducible reviews.

FAQ

Frequently Asked Questions

Elicit has a free Basic plan that includes unlimited paper search, summaries, and chat with papers. Paid tiers (Plus around $12/month, Pro around $49/month, and Team around $79/month, billed per user) add automated reports, bulk data extraction, and the full systematic review workflow. Annual billing offers a discount.

Elicit is a legitimate study and research aid: it links every summary and extracted finding to the original paper so you can verify and cite the source yourself. It speeds up reading and screening, but you should still read key papers directly and write your own analysis. Submitting AI-generated text as your own work, or skipping the cited primary sources, can violate your institution's academic-integrity rules.

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