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Vectorize vs WBX Sandbox

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 WBX Sandbox
DetailVectorize logo Vectorize WBX Sandbox
What it doesAgent memory that learns from experience Secure execution for AI agents in isolated Firecracker microVMs or WebAssembly
StageStartup Not given
Founded2024 Not given
Based inUS CZ
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 Free plan: no card required, 5 concurrent sandboxes, up to 1 hour per sandbox, one-time welcome credit. Pro: $49.00/month (excl. VAT) with $25.00 usage credit, 25 concurrent sandboxes, up to 24 hours per sandbox, 100 vCPU/100 GB RAM total. Team: $119.00/month (excl. VAT) with $50.00 usage credit, 10
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
  • Isolated Firecracker microVMs with own kernel and filesystem
  • Background jobs that survive disconnects
  • Batch execution with up to 1,000 jobs and dependency passing
  • WebAssembly jobs starting in milliseconds without VM boot
  • Budget Guard with cost reserves and limits
  • Execution receipts with runtime, isolation, resources and file hashes
  • Native MCP server integration for ChatGPT and Claude
  • Compact log digests instead of full 5,000-line logs
  • Server-side job waiting with signed webhooks
  • Verified package cache for PyPI, npm, Go and Rust
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
  • Two runtimes with honest isolation labeling
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 check2 no change since last check
Trust Flow (Majestic)180
Citation Flow (Majestic)470
Referring domains (Majestic)13780

5 details filled in for both companies.

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