Jev vs Edge Arena
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Jev compared with Edge Arena
| Detail | 
Jev | 
Edge Arena |
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| What it does | API access without the waitlist: one key, two endpoints
| Put your business decisions on trial with competing AI agents
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| Stage | Not given
| Not given
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| Founded | Not given
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| Based in | Not given
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| Pricing model | Freemium
| Freemium
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| Pricing | Not given
| Free: 2 free runs included with signup. Paid plans: Pro $12/month (1,344 credits, ~4 balanced runs/month), Power $29/month (3,360 credits, ~10 balanced runs/month), Studio $99/month (12,000 credits, ~35 balanced runs/month). One-time credit packs: Starter $9 (720 credits), Velocity $19 (1,680 credit
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| Key features | - Custom criteria: POST state with choice options and score rubrics
- Eight pre-measured rulesets: support-ticket-triage, llm-model-routing, agent-tool-selection, content-moderation, phishing-detection, rag-reranking, agent-output-guardrails, lead-scoring
- Probability distributions over all choices and scores
- Parallel question evaluation within one call
- Key rotation and deletion
- TypeSafe key support for direct billing
| - Multiple competing AI agents explore different strategic approaches simultaneously
- Adversarial critique phase eliminates weak plans before output
- Scoring rubric ranks finalist plans on consistent criteria
- Execution packs with structured next steps and implementation guidance
- Public or private run options with control over data sharing
- Prompts and results never used to train AI models
- View runner-up results and elimination reasoning
- Live real-time competition observation dashboard
- External developer agent deployment with rewards
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| What makes it different | - No waitlist: get a key immediately with email or Google sign-in
- Measured pricing: real calls cost ~20× less than vendor-circulated figures
- Input-only pricing with no output tokens
- Eight rulesets with published exact calls and measured output
- Transparent cost reporting with versioned model IDs in responses
| - Multi-agent competition vs single AI answer reduces blind spots through structured debate between opposing perspectives
- Adversarial critique phase pressure-tests assumptions and eliminates fragile plans before presentation
- Execution-ready structured output designed for immediate action vs theoretical analysis
- Data privacy protection with no model training on user prompts or results
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 26 ▼ −1 (down) since last check | 28 ● no change since last check |
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| Trust Flow (Majestic) | 18 | 9 |
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| Citation Flow (Majestic) | 24 | 32 |
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| Referring domains (Majestic) | 80 | 180 |
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4 details filled in for both companies.
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