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Well-adopted AI research assistant for finding papers, summarizing, and extracting data at scale.
AI research workspace that drafts full academic papers with verified inline citations from up to 500 uploaded sources in a single prompt.
Free nonprofit tool that visualizes scientific literature as topic maps, clustering papers to speed research discovery.
AI-assisted systematic literature review platform for research teams handling screening, deduplication, extraction, and PRISMA reporting.
Enterprise AI knowledge platform that unifies complex regulated-industry data into trusted, AI-ready intelligence for R&D and agents.
No public pricing
No public pricing
- ✦AI-enabled systematic reviews
- ✦Research reports
- ✦Upload your own PDFs
- ✦Quick summaries
- ✦Source quotes
- ✦Question answering
- ✦Full document drafting from one prompt
- ✦Automated literature search via Semantic Scholar
- ✦Import and cite up to 500 uploaded papers
- ✦Inline citation verification
- ✦Export to PDF, Word, LaTeX, and BibTeX
- ✦Overleaf integration for manual editing
- ✦Zotero and Mendeley library import
- ✦AI-generated visual maps of research topics
- ✦Clusters papers into themes
- ✦Open-access resource discovery
- ✦Open-source and nonprofit
- ✦Custom integrations/embedding for organizations
- ✦Reference import, organization, and deduplication across large libraries
- ✦AI-powered relevance predictions to prioritize screening
- ✦Collaborative title/abstract and full-text screening workflows
- ✦Structured data extraction and PICO framework support
- ✦Risk of bias assessment tools
- ✦Auto-generated PRISMA flow diagrams and audit trails
- ✦Mobile app for screening on the go
- ✦Axion for turning data chaos into AI-ready intelligence
- ✦Neuralith for converting enterprise knowledge into an AI engine
- ✦RSpace for precision intelligence in complex R&D
- ✦Data unification across fragmented enterprise sources
- ✦Built for regulated, compliance-driven industries
- →Speeding up literature reviews
- →Automating systematic reviews and meta-analyses
- →Learning about new domains
- →Data extraction in rigorous systematic literature reviews
- →Researchers producing a literature review quickly
- →Students drafting long papers with verified citations
- →Academics writing in a non-native language
- →Exporting AI-drafted content into LaTeX workflows
- →Get an overview of a research field
- →Find relevant papers faster
- →Identify key concepts in the literature
- →Embed discovery tools in library systems
- →Running systematic literature reviews as a research team
- →Speeding up deduplication and abstract screening for large reference sets
- →Producing PRISMA-compliant documentation for publication
- →Coordinating divided screening workloads across reviewers
- →Grounding enterprise AI agents in trusted internal knowledge
- →Accelerating R&D literature and data analysis
- →Unifying siloed regulated data for AI applications