| What it does | Structured AI decisions with probabilities for developers
| Put your business decisions on trial with competing AI agents
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| Stage | Not given
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| Founded | Not given
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| Based in | Not given
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| Pricing model | Paid
| Freemium
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| Pricing | Starter: $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: 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 | - 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
| - 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 | - 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
| - 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 |
| DR (Domain Rating by Ahrefs) | 13 ▲ +1 (up) since last check | 28 ● no change since last check |
| Trust Flow (Majestic) | 0 | 9 |
| Citation Flow (Majestic) | 23 | 32 |
| Referring domains (Majestic) | 59 | 180 |