Skip to main content
NexoraLaunch home

Build log live

Vectorize vs boxd

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

Vectorize compared with boxd
DetailVectorize logo Vectorizeboxd logo boxd
What it doesAgent memory that learns from experience Composable computers for devs and agents
StageStartup Not given
Founded2024 Not given
Based inUS NL
Pricing modelFreemium Not given
PricingSelf-hosted: Free, MIT licensed. Hindsight Cloud: Pay-as-you-go with free credits to start. Retain (store memories) $10.00 per million tokens, Recall (retrieve memories) $0.75 per million tokens, Reflect (synthesize patterns) $0.05 per call, Iris Extract (structured extraction) $7.50 per million tok 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
Key features
  • Per-user persistent memory with preferences, history and decisions kept separate
  • Cross-session persistence allows context to survive weeks between interactions
  • Fast parallel retrieval in under 100ms through four strategies running simultaneously
  • Works with any LLM without losing learned context when swapping models
  • Learns from mistakes and corrects behavior on repeated problems
  • Automatic pattern detection synthesizes individual facts into consolidated knowledge
  • Conflict detection preserves both old and new states with timestamps when facts change
  • Integrates with 20+ coding agents including Claude Code, Cursor, and Copilot
  • 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
What makes it different
  • 94.6% retrieval accuracy on LongMemEval-S, beating next-best system at 74.0%
  • MIT licensed open source with no usage limits, telemetry or restrictions
  • Reflection layer automatically builds judgment and mental models over time without manual tagging
  • Entity resolution handles hundreds of entities with 99.5% query reduction
  • 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
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)68 +1 (up) since last check44 no change since last check
Trust Flow (Majestic)188
Citation Flow (Majestic)4737
Referring domains (Majestic)1378151

5 details filled in for both companies.

More alternatives to Vectorize More alternatives to boxd

Ask a question