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Well-adopted AI research assistant for finding papers, summarizing, and extracting data at scale.
AI-assisted systematic literature review platform for research teams handling screening, deduplication, extraction, and PRISMA reporting.
AI research platform for literature reviews, paper Q&A and daily digests, built for academics wanting cited answers.
Enterprise AI knowledge platform that unifies complex regulated-industry data into trusted, AI-ready intelligence for R&D and agents.
Free nonprofit tool that visualizes scientific literature as topic maps, clustering papers to speed research discovery.
No public pricing
No public pricing
No public pricing
- ✦AI-enabled systematic reviews
- ✦Research reports
- ✦Upload your own PDFs
- ✦Quick summaries
- ✦Source quotes
- ✦Question answering
- ✦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
- ✦literature review generator with per-sentence citations
- ✦AI reader for PDFs
- ✦AI writer with citations
- ✦academic claim verification
- ✦question answering over literature
- ✦daily, conference and best-paper digests
- ✦cross-source search of papers, patents and grants
- ✦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
- ✦AI-generated visual maps of research topics
- ✦Clusters papers into themes
- ✦Open-access resource discovery
- ✦Open-source and nonprofit
- ✦Custom integrations/embedding for organizations
- →Speeding up literature reviews
- →Automating systematic reviews and meta-analyses
- →Learning about new domains
- →Data extraction in rigorous systematic literature reviews
- →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
- →staying current with new research
- →generating cited literature reviews
- →reading and understanding papers
- →verifying academic claims
- →tracking topics and conferences
- →Grounding enterprise AI agents in trusted internal knowledge
- →Accelerating R&D literature and data analysis
- →Unifying siloed regulated data for AI applications
- →Get an overview of a research field
- →Find relevant papers faster
- →Identify key concepts in the literature
- →Embed discovery tools in library systems