boxd vs RELAI

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

boxd compared with RELAI
Detail	boxd	RELAI
What it does	Composable computers for devs and agents	The continual learning engine for AI agents
Stage	Not given	Not given
Founded	Not given	Not given
Based in	NL	Not given
Pricing model	Not given	Freemium
Pricing	Credit-based pricing: €0.039 per vCPU-hour (active only), €0.012 per GiB-hour for RAM (memory in use), €0.00008 per GiB-hour for disk (written space only). New accounts receive €30 in free credits. A typical 2 vCPU / 8 GiB machine costs approximately €0.03 per hour while running (with 10% vCPU activ	RELAI Free: $0. RELAI Enterprise: Custom pricing.
Key features	Hardware-isolated Linux VMs with persistent state between sessions Snapshots and checkpoints for machine state management Automatic hibernation after 4 hours idle, paying for disk only Pre-installed tools: Claude Code, Docker, Node, Python, Go, git, Chrome, ffmpeg, nginx Public HTTPS URL per machine with custom domain support Egress allowlist for network security and isolation CLI, API, Python and TypeScript SDKs for automation Integration with GitHub, Linear and Slack across all machines	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	Hardware-isolated real VMs instead of containers, with full kernel isolation Persistent machines remember running processes and state between disconnects Pay only for active resources used, not provisioned size Free self-hosting up to 16 vCPUs on your own infrastructure	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 plan	Not given	Not given
Open source	Not given	Not given
Platforms	Not given	Not given
Public API	Not given	Not given
Community votes	0	0
DR (Domain Rating by Ahrefs)	44 no change since last check	23 no change since last check
Trust Flow (Majestic)	8	13
Citation Flow (Majestic)	37	25
Referring domains (Majestic)	151	79

4 details filled in for both companies.

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