Why it matters
- In-paper Q&A with Copilot eliminates the need to struggle through dense academic language — ask a question, get a plain-English answer.
- 10M+ users demonstrates strong product-market fit for AI-assisted paper reading.
- Equation and figure explanation capabilities address a specific gap — scientific papers often include math or charts that are difficult to interpret without domain expertise.
- Literature Review feature combines paper discovery with AI synthesis in a single workflow.
Key capabilities
- Copilot (in-paper chat): Ask questions about any paper; get contextual AI answers citing specific sections.
- Equation explanation: Highlight mathematical formulas; get plain-English explanations of what they mean.
- Figure/table interpretation: Ask about charts and tables in papers; AI explains the data.
- PDF upload: Upload any PDF (not just papers in their database) for Copilot analysis.
- Literature review: Search for papers on a topic; AI synthesizes findings across multiple papers.
- Citation generator: Generate citations in APA, MLA, Chicago, and other formats from paper metadata.
- Paper summarization: Get structured summaries of papers with key contributions and limitations.
- Related papers: Discover relevant papers connected to what you're currently reading.
Technical notes
- Paper database: 200M+ papers (open access + metadata)
- PDF chat: Any PDF can be uploaded for Copilot
- AI: GPT-4 powered Copilot responses
- Citation formats: APA, MLA, Chicago, Vancouver, and 9,000+ journal styles
- Mobile app: iOS and Android apps available
- Pricing: Free (limited Copilot questions/day); Premium ~$20/mo
- Company: SciSpace (formerly Typeset.io); Bangalore, India; founded 2015; 10M+ users
Ideal for
- Students and researchers who struggle with dense academic papers and need help understanding specific sections.
- Anyone reading papers with complex mathematics, statistics, or domain-specific jargon they need explained.
- Researchers doing literature review who want AI synthesis without manually reading every abstract.
Not ideal for
- Systematic reviews requiring structured data extraction across many papers — Elicit's table-based extraction is superior.
- Finding papers by claim/consensus — Consensus's Consensus Meter is better for that.
- Academic writing and manuscript preparation (SciSpace's original use case is now secondary to research AI).
See also
- Elicit — Better for systematic literature review and structured data extraction across papers.
- Consensus — Better for quick consensus checking on research claims.
- Perplexity — General AI search with citations; broader than scientific papers only.