Design a RAG-based AI insights system for purchase orders

Design a retrieval-augmented generation (RAG) system that provides real-time insights on purchase orders for 1 million users with 100 million purchase records, where 10% of customers generate 90% of orders. Discuss the end-to-end architecture including retrieval, generation, and time-based caching strategies with various caching algorithms for optimal performance under skewed load.