Elicit

Developed by Ought, a nonprofit focused on AI alignment and safe AI development, Elicit operates with a strong commitment to factual accuracy it only surfaces claims it can trace to specific papers, and explicitly flags uncertainty rather than hallucinating confident-sounding answers.

The platform's core workflow begins with a research question: Elicit searches its database of 200 million academic papers, ranks the most relevant results, and then automatically extracts key data from each study design, sample size, intervention, outcomes, and limitations presenting everything in a structured table that normally requires hours of manual screening to produce.

This makes it particularly valuable for systematic reviews, meta-analyses, and evidence-based decision-making.

Elicit's Concept Search goes beyond keyword matching to understand the semantic intent of a research question, returning papers that are conceptually relevant even when they don't share exact terminology. This is critical in academic research where related work often uses different vocabulary across subfields a limitation that trips up even PubMed and Google Scholar.

The platform supports PDF upload and analysis for papers outside its index, allowing researchers to build a private library of documents that Elicit can query alongside its public database.

For competitive intelligence and market research applications, teams upload internal reports, white papers, and industry studies alongside published research to synthesize insights from both public and proprietary sources.

Elicit's free tier provides a meaningful number of monthly searches suitable for individual researchers, while paid plans unlock higher paper limits, PDF uploads, and advanced extraction columns.