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Edge Arena vs MiroFish

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

Edge Arena compared with MiroFish
DetailEdge Arena logo Edge Arena MiroFish
What it doesPut your business decisions on trial with competing AI agents A simple and universal swarm intelligence engine
StageNot given Not given
FoundedNot given Not given
Based inNot given Not given
Pricing modelFreemium Freemium
PricingFree: 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 Starter: $7.50/month (monthly) or $9/month (annual); Pro: $15.83/month (monthly) or $19/month (annual); Premium: $40.83/month (monthly) or $49/month (annual). Annual plans save 17%.
Key features
  • 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
  • Upload PDF, Markdown, and text documents to seed simulations
  • Convert source material into ontology and graph structure
  • Run parallel simulations with up to 1 million agents per run
  • Generate prediction reports with key risks and confidence signals
  • Deep interaction through ReportAgent or direct character interviews
  • Dual-surface simulation across Twitter and Reddit style channels
  • Follow-up questions in the same workspace for continued analysis
  • Build executable scenarios for public opinion, market, policy, and narrative use cases
What makes it different
  • 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
  • Inspectable AI forecasts treated as exploratory hypotheses before operational decisions
  • Review simulations before upload with the Forecast Explorer gallery
  • Graph-native simulation that exposes actor incentives, narrative spread, and reaction chains
  • Templates and guides for recurring scenario types like crises and product launches
  • Keeps judgment with humans on scenario boundaries and high-stakes operating calls
Community votes00
DR (Domain Rating by Ahrefs)28 no change since last check56 no change since last check
Trust Flow (Majestic)95
Citation Flow (Majestic)3230
Referring domains (Majestic)180160

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