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Vectorize vs Apollo-1

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 Apollo-1
DetailVectorize logo VectorizeApollo-1 logo Apollo-1
What it doesAgent memory that learns from experience Neuro-symbolic AI for enterprise agents that combine language understanding with symbolic logic in one integrated runtime
StageStartup Established
Founded2024 2017
Based inUS US
Pricing modelFreemium Contact for pricing
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 Not given
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
  • One integrated runtime combining neural and symbolic systems
  • Deterministic policy enforcement before action
  • Complete execution trace for every turn
  • Natural language program authoring with code generation
  • Consistent decisions from identical inputs
  • CPU-based logic execution with lightweight language models
  • Managed service and custom enterprise deployment options
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
  • Symbolic logic governs decisions instead of neural weights
  • Lower operational costs through CPU-based logic and lightweight models
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 check20 no change since last check
Trust Flow (Majestic)1811
Citation Flow (Majestic)4733
Referring domains (Majestic)1378155

7 details filled in for both companies.

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