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Well-adopted AI research assistant for finding papers, summarizing, and extracting data at scale.
AI research platform for literature reviews, paper Q&A and daily digests, built for academics wanting cited answers.
Knowledge-graph text analysis tool that surfaces topics and content gaps for research, SEO and market analysis.
Enterprise AI knowledge platform that unifies complex regulated-industry data into trusted, AI-ready intelligence for R&D and agents.
Widely used visual tool for exploring related academic papers.
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
- ✦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
- ✦Text network / knowledge graph visualization
- ✦Topic modeling and content-gap detection
- ✦AI insight and question generation
- ✦GraphRAG and MCP server for LLMs
- ✦Many import sources (PDF, CSV, YouTube, Google, web)
- ✦Obsidian plugin and browser extension
- ✦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
- ✦Visual graph generation of related academic papers
- ✦Discovery of prior and derivative works
- ✦Identification of important and relevant papers
- ✦Exploration of research field dynamics
- →Speeding up literature reviews
- →Automating systematic reviews and meta-analyses
- →Learning about new domains
- →Data extraction in rigorous systematic literature reviews
- →staying current with new research
- →generating cited literature reviews
- →reading and understanding papers
- →verifying academic claims
- →tracking topics and conferences
- →Research and idea generation
- →SEO content-gap analysis
- →Qualitative and market research
- →Grounding enterprise AI agents in trusted internal knowledge
- →Accelerating R&D literature and data analysis
- →Unifying siloed regulated data for AI applications
- →Getting a visual overview of a new academic field
- →Ensuring no key papers are missed in a field with a large volume of new publications
- →Creating a bibliography for a thesis
- →Discovering relevant prior and derivative works