<!-- Full-page Markdown export (rendered HTML → GFM). Source: https://neotoma.io/hi/retrieval-memory Generated: 2026-04-26T19:10:28.723Z --> # Retrieval memory Retrieval memory reconstructs context at query time (RAG/vector search). It excels at relevance search, but does not guarantee deterministic or complete state reconstruction. Similarity ranking is sensitive to embeddings, chunking, and index updates. The same intent can return different top-k items over time. Query A: "How should I schedule with Ana?" -> top-k returns preference "morning meetings" Query B: "Summarize Ana's profile" -> top-k may omit that same preference This model can satisfy semantic search needs but not core state-integrity guarantees. See [platform memory](/platform-memory), [deterministic memory](/deterministic-memory), [conflicting facts risk](/conflicting-facts-risk), and [memory model comparison](/memory-vendors).