Overview
Elicit is an AI-powered research assistant built specifically for scientific literature review, developed by the nonprofit organization Ought and launched in 2021. It is used by over 2 million researchers in academia, clinical research, and industry. The core value proposition is automating the most tedious parts of a systematic review: finding relevant papers, extracting structured data from PDFs, and synthesizing evidence across dozens or hundreds of sources.
The platform indexes more than 138 million scientific papers and over 545,000 clinical trials, with semantic search that surfaces relevant work even when the user doesn't know the precise terminology. Elicit's extraction tables — where users define column headers and the model populates values across a corpus of papers — are its most distinctive feature and the main driver of the reported 80% time savings on systematic reviews.
Underlying the product are large language models (LLMs) from major frontier providers. Ought has also launched an API so Elicit can be called from within Claude or ChatGPT workflows. The free tier is meaningfully functional, which has driven broad adoption, though serious systematic review work quickly exhausts the PDF extraction limits and pushes users to Pro or Team tiers.
Elicit is strongest in empirical biomedical, public health, and social science research. It is a poor fit for humanities disciplines where literature resists structured extraction schemas.
Key Benefits
- Scale: Semantic search across 138M+ papers surfaces relevant literature that keyword searches miss, reducing selection bias in evidence gathering.
- Structured extraction: Automated table-filling from PDFs compresses days of manual extraction into hours, with user-defined columns.
- Workflow guidance: Systematic review templates walk researchers through screening, extraction, and synthesis in a reproducible sequence.
- Accessible free tier: Unlimited search and basic chat with papers requires no payment, lowering the barrier for students and independent researchers.
- API integration: Callable from Claude and other LLM workflows, enabling Elicit's citation retrieval to augment general-purpose agents.
Use Cases
- Systematic literature reviews — Research teams use Elicit to screen hundreds of papers, extract PICO-structured data, and generate PRISMA-compatible summaries, cutting the typical timeline from weeks to days.
- Evidence synthesis for grant writing — Researchers quickly establish the state of evidence on a topic, identify gaps, and pull supporting citations for funding applications.
- Clinical trial landscape analysis — The dedicated clinical trials database lets medical researchers survey what has been tested for a condition, with structured extraction of endpoints and outcomes.
- Academic paper triage — Graduate students and analysts use the chat and summary features to rapidly assess whether a paper is relevant before reading in depth.