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Mnemoverse vs Perseus Computing

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 Perseus Computing
DetailMnemoverse logo MnemoversePerseus Computing logo Perseus Computing
What it doesOne memory, every AI tool. Write once, recall anywhere. High-assurance infrastructure for AI agents
StageNot given Not given
FoundedNot given Not given
Based inNot given US
Pricing modelFreemium Open source
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. Not given
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
  • Harpe: chooses what an AI agent reads under a token budget with consistent results
  • Kibisis: keeps agent memory on your hardware with AES-256-GCM encryption
  • Argus: append-only record that detects edits with cryptographic verification
  • No network code by default for local and disconnected use
  • MIT License with published code, benchmarks and raw results
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
  • Measured empirical validation across 6,111 questions outperforming full-context models
  • Zero plaintext on disk with encrypted vaults matching plaintext accuracy
  • 78.3% fewer tokens sent to the model with a 1,200-token budget per turn
  • Preserves conversational chronology and relational qualifiers under token budgets
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 check42 +1 (up) since last check
Trust Flow (Majestic)73
Citation Flow (Majestic)3724
Referring domains (Majestic)20062

4 details filled in for both companies.

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