Paperguide — AI Research Platform for Scientific Research Workflows - Showcase Project

Paperguide is an AI Research Platform for Scientific Research Workflows. Built for research labs, principal investigators, and research teams, it brings the entire research lifecycle into one collaborative AI-native workspace. Research teams use Paperguide to find, organize, screen, extract, and synthesize scientific literature for literature reviews, systematic reviews, evidence synthesis workflows, and other evidence-based research projects. The platform replaces the fragmented four to six tool research stack with one connected workspace, where every claim, extraction, and citation traces back to a real, peer-reviewed source paper. Features: Research Agent: Runs the full research process end-to-end in a single connected session, from discovery, screening, and comparison to extraction, drafting, and citation handling. AI Academic Search: Hybrid semantic and keyword search across 200M+ peer-reviewed papers from PubMed, arXiv, OpenAlex, and Semantic Scholar with cited evidence-backed answers. AI Literature Review (Agent): Structured five-step Plan, Search, Screen, Extract, Synthesize workflow. Extended mode screens up to 200 papers. Deep Research Report: Researcher-controlled deep research with confirmation at every stage. Full-fledged AI-native Reference Manager: Replaces Zotero, Mendeley, and EndNote. 1,000+ citation styles, Chrome extension, shared libraries. Citation-Grounded AI Paper Writer: Drafts research papers and review sections with references pulled from your library. No fabricated citations. Structured Data Extraction: Pull custom-column evidence tables from multiple papers, with each cell linked to its source passage. CSV/Excel export. PDF Intelligence (Chat with PDF): Query any uploaded paper conversationally with page-level rationale. Evidence Synthesis Workflows and Systematic Reviews: Run protocol-driven syntheses with structured screening and citation-grounded synthesis writing.