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briq vs RELAI

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

briq compared with RELAI
Detailbriq logo briqRELAI logo RELAI
What it doesCloud sandboxes and services for builders and agents The continual learning engine for AI agents
StageNot given Not given
FoundedNot given Not given
Based inFR Not given
Pricing modelFreemium Freemium
PricingHobby (Free): 5 sandboxes & services at once, 16 GB of memory, pico/micro/nano/small/medium sizes, 10 GB disk. Pro (€20/month): €20 usage included monthly, 50 sandboxes & services, 80 GB memory, 5 members, all sizes, 250 GB disk, always-on briqs. Team (€100/month): €100 usage included monthly, 200 s RELAI Free: $0. RELAI Enterprise: Custom pricing.
Key features
  • Linux sandbox with shell, persistent files and development tools
  • Multiple services: Postgres, Redis, DuckDB, custom OCI images
  • MCP integration with Claude, Cursor, VS Code
  • Environment forking with data preservation
  • Idle workload sleep mode with compute billing pause
  • Private networks with public endpoint selection
  • Spend caps, size limits and concurrency controls per credential
  • Audit log for reviewing all actions
  • 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
  • Built specifically for AI agents with native MCP protocol support
  • Open-source runtime in public development with Rust and Firecracker
  • Integrated services ecosystem with private networking
  • 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)18 −1 (down) since last check23 no change since last check
Trust Flow (Majestic)013
Citation Flow (Majestic)2025
Referring domains (Majestic)2479

5 details filled in for both companies.

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