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JevModel vs Referee.chat

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

JevModel compared with Referee.chat
DetailJevModel logo JevModelReferee.chat logo Referee.chat
What it doesStructured AI decisions via API and playground An AI panel debates your goal; a referee rules on re-checkable evidence
StageNot given Not given
FoundedNot given Not given
Based inNot given Not given
Pricing modelNot given Freemium
PricingFree: 5 successful runs per UTC day after email verification. Starter: $9.90/month for 30M tokens/month. Builder: $19.90/month for 80M tokens/month. Pro: $39.90/month for 200M tokens/month. Scale: $79.90/month for 500M tokens/month. Tokens refresh monthly and do not roll over. One-time token packs a Free: $1.00 starting credit once. Credit plans from $10 top-up with no expiration. Your own key: 5% infrastructure fee after the first $5.00 of usage.
Key features
  • Choice decision type: select from supplied options
  • Score decision type: assign level on defined scale
  • Noul decision type: yes/no judgment against criterion
  • Decision flows: chain questions on canvas with branching
  • Batch processing for CSV, TXT, JSONL files up to 1,000 rows
  • Shared account balance across console, batch and API
  • Export results as CSV or JSONL
  • Failed requests are refunded
  • Probabilities included with all answers
  • Panel of up to six AI models from different vendors
  • Referee rules on re-checkable evidence only
  • Searches academic databases: arXiv, OpenAlex, Crossref, Europe PMC
  • Executes Python code to verify claims
  • Customizable acceptance standards
  • Matches pause and resume without losing work
  • Shared ledger prevents re-derivation
  • Spending limit per match
What makes it different
  • One API and console for playground, flows, batch and API access
  • Only questions on the executed path in flows are billed
  • Built on TypeSafe AI's Jev structured decision model
  • Test and measure decisions on your own data before production
  • Custom decision criteria defined by your own labels and rules
  • Referee decides on evidence, not argument quality
  • Panel from different vendors fails in different directions
  • Stuck is a targeted question, not model thrashing
  • Cost grows with ledger, not round count
  • Published matches become research record
Community votes00
DR (Domain Rating by Ahrefs)30 +2 (up) since last check2 no change since last check
Trust Flow (Majestic)90
Citation Flow (Majestic)2713
Referring domains (Majestic)7931

4 details filled in for both companies.

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