Vector Databases and AI Memory
8 min read
AI memory systems depend on vector search. Facts are embedded, stored, and retrieved by nearest-neighbor similarity — usually cosine distance.
What matters
- Embedding quality sets the ceiling for recall.
- Metadata filters prevent irrelevant matches.
- Hygiene keeps noise out of future responses.
GreatChat uses embedding-backed search with user-scoped memory so results stay relevant. Manage yours from memory.
Comparable products worth reviewing: Mem0, Letta, Zep, and Pinecone.
For background theory, see Hugging Face NLP vector semantics.
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