Enterprise Production-Grade Knowledge Graph Case Studies

Presentation materials showcasing production-grade Knowledge Graph (KG) systems at companies, presented at the Knowledge Graph Conference (KGC), have been shared. These cases go beyond the simple proof-of-concept (PoC) stage, showing systems that meet complex compliance and data requirements in actual production environments.

Key company use cases are as follows:

• Bloomberg: Built a formal dependency model for ontology governance.
• AbbVie: Operates ARCH, an internal KG for drug and disease domain intelligence. This system is connected to a scoring engine, a researcher dashboard, and an LLM companion for natural language queries. Here, the KG serves as the trusted single source of truth, while the LLM is used as the user interface.
• Morgan Stanley: Automated SHACL drift detection for risk reporting data, building a system that sends weekly alerts when the semantic layer drifts from the governance framework.

The key point is that knowledge graphs are being used not as a mere auxiliary layer to vector search, but as core infrastructure that performs reasoning. This presents a practical alternative for solving complex data structures and logical reasoning problems that are difficult to address with vector DBs alone.