boxd vs Exabase

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 Exabase
Detail	boxd	Exabase
What it does	Composable computers for devs and agents	Context infrastructure for AI agents
Stage	Not given	Startup
Founded	Not given	Not given
Based in	NL	GB
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	Not given
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	Memory system with self-managing advanced memory Isolated per-tenant instances with version rollback Portable context server with files, notes and links Sub-document multi-modal hybrid search Structured data extraction from PDFs, websites and images Autonomous agents for knowledge base automation 99.9% uptime SLA AES-256 encryption at rest and SSL in transit TypeScript SDK and REST API Model-agnostic and framework-agnostic
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	Cut token spend by up to 81% through persistent agent memory instead of full context window stuffing State-of-the-art on two leading AI memory benchmarks Full-stack data layer eliminating need for multiple services Production-tested at scale powering Fabric platform Self-improving memory that tracks relationships and resolves contradictions
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	29 no change since last check
Trust Flow (Majestic)	8	11
Citation Flow (Majestic)	37	32
Referring domains (Majestic)	151	122

4 details filled in for both companies.

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