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FOXMEMORY™In Development

# Memory that works like _memory_.

Not RAG. Not a vector database bolted to a chatbot. A system where experience is consolidated, weighted, and maintained - and the system knows when it needs to sleep.

THE PROBLEM

## RAG is not memory

Retrieval-augmented generation is not memory. It's search with extra steps. There's no consolidation - every memory is equally fresh. There's no weighting - a passing remark and a life-changing conversation are stored the same way. There's no maintenance - the index grows forever without reorganization. And there's no sleep. Real memory requires offline processing to integrate new experience with old.

ARCHITECTURE

## A hybrid that learns from itself

🔍

### Vector Layer

Forked from mem0\. Embedding-based similarity retrieval for the fast path - what is this most like?

🕸️

### Graph Layer

Neo4j knowledge graph. Structural relationships, causal chains, temporal sequences - the things vectors cannot capture.

🔄

### Bidirectional Coherence

The novel part. Graph changes back-propagate into the vector store. When a new relationship recontextualizes an old memory, the embedding is re-computed. Meaning is relational.

WHY IT MATTERS

## A mind needs to grow

A mind without real memory is a parlor trick. It can be impressive in the moment, but it can't grow, can't consolidate experience into wisdom, can't know itself over time.

[Follow development on the blog](/blog)

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