The client’s supply chain officer described their problem as "fighting ghosts." They knew disruptions were coming, but they never knew from where until it was too late. My challenge was to turn millions of scattered customs records into a coherent *map of the world*. We used **Neo4j** to build a knowledge graph where every node represented a physical entity—a factory, a port, a warehouse. But the real magic happened in the edges. We didn't just map "A connects to B"; we mapped "A relies on B for 30% of critical input X." When a major port strike hit in 2024, while competitors were scrambling to call suppliers, our client’s dashboard lit up red. The system traced the disruption through four layers of the supply chain instantly. They re-routed shipments *before* the bottleneck physically occurred. > "We stopped reacting to disasters and started predicting them. This graph is the nervous system of our operations."