What problem does it solve? Conducting a rigorous literature review requires searching multiple academic databases, deduplicating results, verifying every citation, and formatting output to publication standards—a slow, error-prone manual process. ## Core Features & Use Cases - Multi-Database Search: Query PubMed, bioRxiv, arXiv, Semantic Scholar, and specialized biomedical databases, then aggregate, deduplicate, and rank results by citation count. - Citation Verification: Automatically validate every DOI against CrossRef and generate correctly formatted references in APA, Nature, Vancouver, Chicago, or IEEE styles. - Professional Document Generation: Produce structured markdown reviews from a PRISMA-compliant template and convert them to PDFs via pandoc with table of contents and section numbering. - Use Case: A researcher writing a systematic review on CRISPR therapies for sickle cell disease searches three databases, screens 217 papers down to 52, synthesizes findings thematically, verifies all DOIs, and exports a publication-ready PDF. ## Quick Start Ask the AI to conduct a systematic literature review on your research topic, searching PubMed and bioRxiv, and generate a verified PDF report.
