Elicit is an AI-powered research assistant built specifically for systematic literature reviews and evidence synthesis. Researchers and scientists use it to automate the most time-consuming parts of academic research: finding relevant papers, reading them, and extracting structured data. Elicit searches across 200 million papers from Semantic Scholar and other academic databases, ranks results by semantic relevance (not just keyword matching), and presents the top papers with AI-generated summaries of their key findings, methodologies, and conclusions. The Data Extraction feature is where Elicit truly shines. Users define custom extraction columns — population studied, intervention used, outcome measured, sample size, effect size, study design — and Elicit reads every paper and fills in the table automatically. What might take a research team weeks to extract manually, Elicit handles in minutes. Elicit also performs concept mapping across a body of literature, identifying themes, contradictions, and research gaps. Papers can be organized into collections, annotated, and exported to CSV or BibTeX. Built by Ought, an AI safety nonprofit, Elicit is designed to make evidence-based decision-making faster and more rigorous — whether for academic research, systematic reviews, policy analysis, or clinical evidence synthesis.