Inspiration

AI agents are becoming better at reasoning, tool use, and long-running workflows, but their memory is still fragile.

Most agent-memory implementations focus on storing more information. In practice, an enterprise agent also needs to decide:

  • What is worth remembering?
  • Which facts are still current?
  • What should happen when new information contradicts old information?
  • How can a user inspect why a memory was retained, replaced, or forgotten?
  • How can memory behaviour be tested rather than treated as a black box?

This motivated Mnemo, a self-auditing memory layer for AI agents. The goal is not simply to create a larger vector store, but to create a memory system that is selective, correctable, explainable, and testable.

What Mnemo does

Mnemo observes conversations or agent events and extracts candidate memories such as:

  • User preferences
  • Operational facts
  • Decisions
  • Procedures
  • Entity relationships
  • Time-sensitive updates

Each candidate is assessed before storage. Mnemo records attributes such as memory type, importance, confidence, entities, provenance, and verification status.

When new information arrives, Mnemo can:

  1. Detect that it relates to an existing memory.
  2. Identify possible contradictions.
  3. Decide whether the new information should coexist with, supersede, or invalidate the older memory.
  4. Preserve an audit trail of the decision.
  5. Return the most relevant and current memory during recall.

The system also supports explicit forgetting. A memory can be removed from active recall while the reason and related audit event remain available for inspection.

How I built it

Mnemo is implemented as a modular Python application with a FastAPI service layer.

The main workflow is:

Conversation or event
        ↓
Candidate-memory extraction
        ↓
Memory assessment
        ↓
Duplicate and contradiction detection
        ↓
Store, update, supersede, or reject
        ↓
Semantic recall with provenance
        ↓
Auditable forgetting and replay

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