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Oswin Data vs MailDignity

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

Oswin Data compared with MailDignity
Detail Oswin DataMailDignity logo MailDignity
What it doesDatasets for RAG, fine-tuning and training built from public sources Fix your AI outbound and save your reputation
StageNot given Startup
FoundedNot given 2026
Based inNot given Not given
Pricing modelPaid Paid
PricingWeb Corpus: starter sets from $49 (250,000-500,000 documents); shelf corpora from $99-$199 per shelf (one-time license); Everything (full crawl) $3,000 one-time; Whole Library (all builds for one year) $5,000 per year. Reference Collections: Encyclopedia $1,200 commercial or $349 research (one-time) Not given
Key features
  • Web corpus with 100.7M documents and 105B tokens from Common Crawl
  • Documents scored with Bear Rank and shelved by subject
  • 15 million encyclopedia entries with sources and model attribution
  • 200 million synthetic Q&A records with metadata
  • Delivered as JSONL and Parquet formats
  • Free samples available on Hugging Face
  • Command-line client with resumable downloads and SHA-256 verification
  • Statistics collection with 7,000 topics and 140,000 figures
  • Glossaries for 10,000 topics with one million definitions
  • Book Q&A dataset with 8,000 titles for reading comprehension
  • 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
  • All datasets built only from public sources with full provenance tracking
  • Every record includes source attribution and licensing information
  • Eight curated subject shelves for targeted corpus selection
  • Flexible purchasing: buy individual shelves, slices, or entire library
  • Over 4 TB of clean, deduplicated text ready for machine learning
  • 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)Not checked yet no change since last check10 +3 (up) since last check
Trust Flow (Majestic)54
Citation Flow (Majestic)2822
Referring domains (Majestic)699

4 details filled in for both companies.

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