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Jev Model vs Meetext

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

Jev Model compared with Meetext
DetailJev Model logo Jev ModelMeetext logo Meetext
What it doesStructured AI decisions with probabilities for developers AI-native forward deployed engineering software for enterprise customer deployments
StageNot given Startup
FoundedNot given 2025
Based inNot given Not given
Pricing modelPaid Freemium
PricingStarter: $9.9 with 100,000 credits, no expiry; Pro: $99 with 1,000,000 credits, no expiry; Enterprise: $999 with 11,000,000 credits. One-time plans do not auto-renew; credits remain available after purchase. Free during launch for all plans. Developer: $0/month (1 customer, 2 environments). Startup: $249/month or $2,988/year (10 customers, 25 environments). Growth: $849/month or $10,188/year (75 customers, 150 environments). Enterprise: Custom pricing. If using Meetext's AI model, charged on usage at ap
Key features
  • Typed decision output with Choice, Score, and Noul question types
  • Probability and confidence results on every answer
  • Online playground for testing with unlimited runs
  • REST API and SDK integration
  • Multiple concurrent requests
  • Team workspaces and collaboration
  • Up to 8 typed questions per request
  • Fast decision latency around 120ms
  • Agent Skill for coding agents and LLM workflows
  • Support for English and Simplified Chinese
  • Supports 14 enterprise destinations including Slack, Teams, ChatGPT, Claude, Salesforce, ServiceNow, HubSpot, Notion, Linear, Atlassian, Asana, Google Chat, Cursor and VS Code
  • Personal data masking and usage budgets with kill switch
  • Health checks, incident response and three-layer monitoring
  • Customer-written acceptance criteria that rerun on each publish
  • Hosted MCP endpoints and customer installation portals
  • Cross-customer gap detection and pull request generation
  • Permission-aware AI agent that requests confirmation before acting
What makes it different
  • Structured output with defined answer space
  • Probability-backed decisions code can use directly
  • Multiple questions from one state in parallel
  • Developer control over business logic and actions
  • Designed to integrate into existing systems without replacement
  • Automates the repeatable deployment work that scales linearly with customer count, avoiding the need to hire more forward deployed engineers
  • Priced per customer environment rather than by API traffic or usage volume
  • Verifies changes only when customer-written acceptance criteria pass, not just when code is deployed
  • Includes AI agent for common operational tasks but all changes require human confirmation
Community votes00
DR (Domain Rating by Ahrefs)13 +1 (up) since last check7 +4 (up) since last check
Trust Flow (Majestic)01
Citation Flow (Majestic)2320
Referring domains (Majestic)597

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