Edge Arena vs Agentboxd

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 Agentboxd
Detail	Edge Arena	Agentboxd
What it does	Put your business decisions on trial with competing AI agents	Real email inboxes for AI agents with API, webhooks, and AI triage
Stage	Not given	MVP
Founded	Not given	Not given
Based in	Not given	GB
Pricing model	Freemium	Free
Pricing	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	Free during public beta. Planned after beta: Builder $15/month, Team $60/month, Scale custom. Builder includes 25,000 emails/month, 100 inboxes, 25,000 AI triage calls/month. Team includes 150,000 emails/month, 1,000 inboxes, 150,000 AI triage calls/month. Overage pricing: $1 per 1,000 emails, $0.50
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	AI triage on every email with category, phishing, injection, and urgency scoring Inboxes with one API call on shared or custom domains Drafts with human approval before sending DKIM-signed sending with threaded replies Webhooks with HMAC-SHA256 signature verification Full-text search and long-poll wait endpoints Text extraction from attachments including OCR Sign in with Agentboxd for AI agent authentication
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	AI processing is optional with privacy switch
Community votes	0	0
DR (Domain Rating by Ahrefs)	28 no change since last check	21 +4 (up) since last check
Trust Flow (Majestic)	9	5
Citation Flow (Majestic)	32	31
Referring domains (Majestic)	180	55

5 details filled in for both companies.

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