Savyly 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.

Savyly compared with Edge Arena
Detail	Savyly	Edge Arena
What it does	Private AI assistant for Mac and Windows that floats over any app, reads your screen and answers in seconds	Put your business decisions on trial with competing AI agents
Stage	Startup	Not given
Founded	2026	Not given
Based in	IN	Not given
Pricing model	Free trial	Freemium
Pricing	Free trial: 15 minutes with all features including Deep. Until 8 November 2026 (Diwali offer): Spark ₹99 for 1 hour, Focus ₹199 for 3 hours, Sprint ₹499 for unlimited 7 days, Marathon ₹999 for unlimited 30 days. After 8 November: ₹199, ₹499, ₹999 and ₹2,999 respectively. All prices include taxes, pa	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	Interview practice with HR, technical, coding and system design modes Reads and answers questions from your screen Deep mode for expert-level thinking on complex problems Floats over any application without appearing on screen 11 ready-made modes or custom prompts Works with resume and job description for interview prep	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	Interview practice modes including DSA, technical, HR and system design with feedback	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)	1 +1 (up) since last check	28 no change since last check
Trust Flow (Majestic)	0	9
Citation Flow (Majestic)	14	32
Referring domains (Majestic)	1	180

5 details filled in for both companies.

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