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Scifocus vs MailDignity

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Scifocus compared with MailDignity
DetailScifocus logo ScifocusMailDignity logo MailDignity
What it doesAI-powered research assistant for academic writing and scientific discovery Fix your AI outbound and save your reputation
StageStartup Startup
FoundedNot given 2026
Based inNot given Not given
Pricing modelFreemium Paid
PricingFree tier with 800 words. Paid plans: Basic $6.99/month (10,000 words/month for Daily Academic Toolkit, 5,000 for Research Assistant Pro); Pro $10.99/month (50,000 words/month for Toolkit, 7,500 for Pro); Ultimate $35.99/month (unlimited Toolkit access, 15,000 words/month for Research Assistant Pro Not given
Key features
  • Literature review tools to find and organize relevant research
  • Note-taking and mind-mapping features for organizing research insights
  • Essay and academic writing assistance
  • Support for responding to reviewer comments and revisions
  • Grammar checker and citation format conversion
  • Paraphrasing tools for original content creation
  • Over 50 modules in Daily Academic Toolkit for essay and research support
  • Research Highlights Extractor and Content Fusion tools
  • Multiple AI model integration with seamless switching
  • End-to-end encryption and advanced security measures
  • PASS, REVIEW or FAIL verdicts on emails
  • Detects unsolicited diagnoses and privacy intrusion
  • Catches generic flattery and fake familiarity
  • Identifies asymmetric asks and excessive homework
  • API integration for automated checking
  • MCP support for AI agents
  • Gmail and Outlook browser extensions
  • ChatGPT app integration
  • Structured JSON verdicts via API
What makes it different
  • Grounded in scientific expertise with content trained on scholarly articles and STM knowledge
  • Comprehensive all-in-one platform covering entire research lifecycle from idea to publication
  • User data ownership and privacy protection without using inputs to train base models
  • Model-agnostic flexibility allowing seamless switching across different LLMs
  • Journal-standard output optimization for publication-ready academic content
  • Uses deterministic filters with fixed rules before applying AI analysis
  • Judges message form rather than facts it cannot verify
  • Scales across workflows and no-code platforms
  • Integrated with Zapier, Make, n8n, Clay and other tools
Community votes00
DR (Domain Rating by Ahrefs)6 no change since last check10 +3 (up) since last check
Trust Flow (Majestic)74
Citation Flow (Majestic)2722
Referring domains (Majestic)639

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