Boost.space 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.

Boost.space compared with Edge Arena
Detail	Boost.space	Edge Arena
What it does	AI agents for product catalog revenue and business automation	Put your business decisions on trial with competing AI agents
Stage	Not given	Not given
Founded	2022	Not given
Based in	CZ	Not given
Pricing model	Paid	Freemium
Pricing	Bob Agent Launch: $2,500 one-time (excluding VAT), includes up to 8 hours of expert work and first month of Agent OS. Custom Agent Launch: $5,000 one-time (excluding VAT), includes up to 16 hours of expert work and first month of Agent OS. Agent OS plans: Standard at $300 per month when paid annuall	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
Key features	Access to 9B+ commerce records for product research	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
What makes it different	One-time agent purchase with no subscription lock-in for the delivered agent Prove ROI in 4 weeks before committing to ongoing services Delivered agent remains yours with its training, memory and custom skills Reuse agent context and skills across multiple roles without starting from zero Transparent pricing with confirmed costs before purchase	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
Community votes	0	0
DR (Domain Rating by Ahrefs)	62 +1 (up) since last check	28 no change since last check
Trust Flow (Majestic)	18	9
Citation Flow (Majestic)	40	32
Referring domains (Majestic)	647	180

5 details filled in for both companies.

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