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Mnemoverse 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.

Mnemoverse compared with WBX Sandbox
DetailMnemoverse logo Mnemoverse WBX Sandbox
What it doesOne memory, every AI tool. Write once, recall anywhere. Secure execution for AI agents in isolated Firecracker microVMs or WebAssembly
StageNot given Not given
FoundedNot given Not given
Based inNot given CZ
Pricing modelFreemium Not given
PricingFree: $0 with 1,000 queries/day, 10,000 atoms, 60 req/min. Pro: $29/mo with 50,000 queries/day, 500,000 atoms, 600 req/min. Team: $149/mo with 500,000 queries/day, 5,000,000 atoms, 3,000 req/min. Enterprise: Custom limits and pricing. 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
  • Persistent cross-tool memory API working with Claude, Cursor, VS Code, ChatGPT, Python, and any HTTP client
  • Hebbian associations that strengthen links between concepts recalled together
  • Outcome feedback that re-ranks recall based on usefulness
  • Automatic query expansion along learned associations
  • Python SDK with typed errors for write, read, feedback, and stats
  • REST API for any HTTP client
  • Per-tenant org isolation and SHA-256 hashed API keys
  • 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
  • Learns from outcomes and improves over time, unlike vector databases that only perform similarity search
  • Works across every AI tool with a single API key, not locked to one platform
  • Complementary to RAG: remembers outcomes and lessons, not just document similarity
  • Free tier with full API access and MCP server, no credit card required
  • 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)40 −1 (down) since last check2 no change since last check
Trust Flow (Majestic)70
Citation Flow (Majestic)370
Referring domains (Majestic)2000

4 details filled in for both companies.

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