From Knowledge Islands to Marketing Brain: Knowledge Fusion & Graph Reasoning for Corporate Products
China Postal Savings Bank built a corporate product recommendation system using multi-source knowledge fusion, a dual-engine vector database and knowledge graph, and a four-layer agent architecture (intent recognition, vector matching, graph retrieval, LLM polishing), achieving 90% accuracy—a 30% improvement over pure RAG—and deploying across 11 business channels with 36,000+ recommendations generated.
