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Free-first literature discovery tool that visually maps citation networks and related papers to speed up systematic reviews.
AI research workspace that drafts full academic papers with verified inline citations from up to 500 uploaded sources in a single prompt.
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
- ✦Citation and author network exploration from a seed paper
- ✦Interactive visualizations of how topics relate over time
- ✦Unlimited library organization and collection sharing
- ✦Zotero integration for syncing saved papers
- ✦Up to 300 seed articles supported on the paid tier
- ✦Alerts for new related research
- ✦Research on AI governance
- ✦Analysis of AI risks and opportunities
- ✦Annual reports and updates
- ✦Information on AI regulation
- ✦Event summaries and announcements
- ✦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
- ✦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
- →Building a systematic literature review efficiently
- →Discovering research gaps in an unfamiliar field
- →Tracking new publications related to saved papers
- →Visualizing how a body of research has evolved
- →Understanding public attitudes towards AI
- →Analyzing the impact of AI on great powers
- →Regulating downstream AI developers
- →Managing risks from AI-enabled biological tools
- →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
- →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