RAG and GenAI for Customer 360 Architecture

Traditional batch-based Customer 360 architectures are inadequate for GenAI applications because they rely on stale data. A modern AI-driven Customer 360 combines real-time event streaming (Kafka), stateful stream processing (Flink), RAG-based context retrieval, and guardrailed GenAI generation. The architecture continuously updates customer profiles from live events, retrieves relevant enterprise knowledge at query time, and enforces compliance controls including PII filtering, role-based retrieval, tokenization, and immutable audit logs. This is especially relevant for financial services use cases like agent copilots, fraud detection, personalized banking, and compliance-aware communication. Key design principles include event immutability, exactly-once processing, horizontal scalability, and multi-region support.