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Consensus

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Description

A semantics-based AI tool that uses AI models to analyze abstracts of papers and find papers using plain text queries for literature reviews

Market positioning

AI-powered semantic literature search tool

Target audience

PhD students, researchers, and academics conducting literature reviews

Use cases

Academic literature review and research paper discovery using natural language queries

Company information

Company size

Small startup (estimated 10-50 employees)

Revenue

$1-10M ARR (estimated)

Scale

Early-stage growth

Number of users

10,000+ researchers (estimated)

Features

Abstract analysis using AI models, AI-powered semantic search, Full-text analysis (sometimes), Plain text query capability

Pricing

Pricing modelFreemium with premium subscriptions
Starting priceFree tier available, premium plans starting at $9/month
Billing periodMonthly/Annual

Rating

4.2/5

No Trustpilot link available

Pros and cons

Based on: (AI summary)

Pros

  • Uses advanced AI for semantic search
  • Useful for early research stages
  • Can answer scientific questions quickly

Cons

  • Less reliable than citation-based tools
  • May provide less accurate results than human-curated citations

Feature Comparison

Top features across 11 competitors (most common first)

Feature Anara (form…LitmapsResearchRab…Semantic Sc…Connected P…IncitefulConsensusElicitPhD Literat…SciSpaceScite
Citation-based paper discovery
AI-powered semantic search
Visual graph representation of paper connections
Abstract analysis using AI models
Plain text query capability
Automated citation and study tools
Built-in collaboration with shared workspaces
Multimedia research support (PDFs
videos
web pages
notes)
Multi-source research from PubMed
arXiv
JSTOR
Persistent research memory
Source control flexibility
Source verification with exact passage linking
Systematic workflow automation
Access to 270+ million papers
Automated alerts for new publications