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Deep AI search over scientific literature with full-text analysis
Updated
Undermind is an AI co-researcher that helps scientists find academic papers they might otherwise miss. It was founded by MIT quantum physics PhDs and is backed by Y Combinator, and it analyzes full texts rather than only abstracts.
The workflow has four steps: describe your research and answer clarifying questions, let Undermind explore and evaluate hundreds of papers by following citations, build and refine reports while reading full texts, and keep up with notifications. A typical search takes a few minutes, and the vendor reports its v2 engine found 85% of the 20 most relevant papers in 10 minutes in its own benchmark.
Scientists and academic researchers doing literature discovery and reviews use it. Teams can share a Team plan with management features and priority support.
Free costs $0 with basic chats and standard rate limits. Pro is $16 a month billed annually with advanced models, full-text analysis and 10x higher limits. Team is $15 per person a month billed annually. Enterprise is custom with SSO and dedicated support.
Alternatives include Consensus for evidence summaries from papers, SciSpace for paper explanation, Scite for citation context, ResearchRabbit for visual literature mapping, and Scholarcy for article summaries.
Pricing Model
FREEMIUM
Starting Price
$16/mo
Free Options
Free version
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Other
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Compliance Standards
SOC 2 Type II
EnterpriseISO 27001
EnterpriseGDPR Compliant
GlobalHIPAA
HealthcarePCI DSS
FinanceCCPA
PrivacyFedRAMP
GovernmentCSA STAR
CloudDeployment & Data
Data Residency Options
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AI summaries of research papers as interactive flashcards
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