🧠 AI Memory Optimizer
Drastically reduce RAG costs and latency while improving retrieval accuracy through advanced memory architecture.
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THE AGENSI STORE
4 skills found
Drastically reduce RAG costs and latency while improving retrieval accuracy through advanced memory architecture.
A retrieval architect that diagnoses why RAG returns confident-but-wrong answers, picks the right context architecture (RAG vs knowledge graph vs structured/temporal retrieval) instead of defaulting to vector search, and designs the institutional-memory schema embeddings throw away.
by Kaymue
Diagnose broken RAG systems. 8 failure categories: chunking, embeddings, retrieval, reranking, hallucination. Recall@k measurement.
Deploy a local, private RAG pipeline using Supabase, n8n, and Ollama in minutes.