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Rool® vs RELAI

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

Rool® compared with RELAI
DetailRool® logo Rool®RELAI logo RELAI
What it doesYour private AI machine in the cloud The continual learning engine for AI agents
StageNot given Not given
FoundedNot given Not given
Based inIE Not given
Pricing modelFreemium Freemium
PricingStandard: Free forever. Plus: €9/month. Pro: €25/month. Team plan: No subscription, pay per machine and per AI use from prepaid balance in US dollars. Machine sizes: R0 $5/month, R1 $10/month, R2 $30/month. AI pricing per million tokens: Rool® 1 input $0.35, cached input $0.07, output $0.70. Rool® 1 RELAI Free: $0. RELAI Enterprise: Custom pricing.
Key features
  • Persistent memory that builds knowledge graphs over time
  • File storage and management with version control
  • Collaboration with shared access and permissions
  • Multiple Rool Machines per account
  • Built-in connectors and custom MCP servers
  • Full data export and API access
  • Progressive Web App and mobile apps
  • Hourly credit refills with daily limits
  • Rool 1 and Rool 1.5 AI models
  • EU infrastructure with self-hosted models
  • Capture signals from code, requirements, and production traces
  • Build and maintain EvalsWiki as versioned behavioral knowledge
  • Find missing eval coverage and unclear expectations
  • Generate complete evals with scenarios, environments, and evaluators
  • Optimize harness across prompts, tools, workflows, and code
  • Multi-objective optimization for quality, cost, latency, and KPIs
  • Model selection, migration, and routing with evaluation
  • Regression-controlled improvement with evaluation evidence
  • Versioned storage in repository with pull requests
What makes it different
  • Private machine isolated at VM level, not just by access rules
  • Hosted entirely in the EU with self-hosted AI models
  • Never trains AI models on your data
  • Free forever plan with no credit card required
  • Turns failures into replayable learning environments
  • Prevents regressions by keeping previous evals in the loop
  • Integrates with existing observability stacks and traces
  • Preserves business intelligence versioned in repository
  • Adapts harness to model changes without redefining use cases
Free planNot given Not given
Open sourceNot given Not given
PlatformsNot given Not given
Public APINot given Not given
Community votes00
DR (Domain Rating by Ahrefs)16 no change since last check23 no change since last check
Trust Flow (Majestic)613
Citation Flow (Majestic)2925
Referring domains (Majestic)5679

5 details filled in for both companies.

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