Elicit: AI for scientific research

What

Elicit is an AI research platform for scientific and evidence-heavy work. It helps researchers search academic literature, generate structured research reports with citations, organize sources, monitor new publications, and support systematic review workflows.

The product appears positioned for professional researchers and research-driven teams in academia, pharmaceuticals, medtech, policy, consumer goods, industrials, software, and related fields. Its core workflow is to turn a research question into a faster evidence review by searching large research datasets, extracting information, and presenting findings in reports, tables, and review workflows.

Features

• Semantic search across large research datasets: Elicit searches over 138 million academic papers and 545,000 clinical trials, helping users find relevant evidence even when they do not know the exact keywords.
• AI-generated research reports: The platform produces structured research briefs with sentence-level citations, which helps users review evidence quickly while tracing claims back to source text.
• Customizable report generation: Users can adjust which papers and what information are included, making reports more adaptable than a fixed one-size-fits-all summary.
• Systematic review support: Elicit automates screening and data extraction and partially supports search and report generation, which is useful for teams running more formal evidence synthesis projects.
• Library for source organization: Researchers can store and organize papers they find, making it easier to reuse sources across future projects.
• Alerts for new research: Elicit Alerts surfaces relevant new research so users can stay current without relying only on traditional email alert streams.

Helpful Tips

• Check fit by workflow depth: Elicit supports both quick evidence lookups and longer review projects, so buyers should decide whether they mainly need search, report generation, or systematic review automation.
• Validate source coverage for your field: The site cites academic papers and ClinicalTrials.gov content, but teams in niche domains should confirm whether the available sources match their evidence requirements.
• Use citations as a verification layer: Sentence-level citations are valuable, but research teams should still review underlying papers before using outputs in regulated, clinical, or policy decisions.
• Assess customization needs early: If your team has fixed evidence templates, inclusion criteria, or extraction fields, evaluate how well Elicit’s report and review workflows map to those standards.
• Separate confirmed capability from future direction: The page mentions an API and research agents in release notes, so those may expand automation options, but implementation details are not fully described on this page.

OpenClaw Skills

Elicit could likely work well inside an OpenClaw environment as the evidence retrieval and synthesis layer for research-intensive workflows. Likely use cases include an agent that turns a natural-language research question into a literature scan, a report-building workflow that drafts evidence summaries with linked citations, or a monitoring agent that watches for new studies and routes notable findings to teams by topic.

For target users such as R&D teams, medical affairs, policy analysts, or academic research groups, this combination could shift work from manual paper gathering toward more structured evidence operations. If connected through the announced API rather than a confirmed native integration, OpenClaw skills could likely orchestrate recurring review pipelines, compare evidence across projects, populate internal knowledge bases, and hand off cited outputs to downstream writing, decision-support, or portfolio-planning agents.