Microsoft Foundry-based architecture addresses RAG's limitation of lacking accumulated understanding. Classic RAG retrieves documents but discards insights after each query, requiring redundant processing. The proposed solution introduces a persistent knowledge layer with three parts: a vendor-neutral design pattern, an Azure-native implementation using Azure AI Search, Cosmos DB, and FastAPI, and a synthetic property-insurance demo called Ostermere Mutual.

The design adds layers for knowledge accumulation, query routing, and governance. Unlike semantic caching, which only stores answers, this system maintains connections between concepts, decisions, and contradictions. The Ostermere Mutual demo demonstrates handling complex queries about policy exceptions, depreciation thresholds, and regulatory changes without retreating to zero-state reasoning.

Part II details Azure service mappings, while Part III shows how the system resolves contradictions and tracks historical decisions. The approach emphasizes that retrieval alone cannot build domain-specific memory, requiring architectural shifts to store relationships and reasoning. The GitHub repository provides a full implementation under the MIT license.