No specific roles are required to build or maintain the knowledge graph—it's generated and updated automatically (controlled by the customer’s policy). The system's Entity Management and Knowledge Fabric components create and update the knowledge graph based on the law domain ontology and ingested documents. As new cases, documents, and legal materials are processed through the DDU service, entities and their relationships are automatically extracted and added to the graph. The system handles entity resolution, relationship identification, and graph updates without manual intervention. Your existing legal and operations teams simply use the system; no dedicated graph database specialists or ontologists are needed.

The system adapts through continuous learning at the infrastructure level as new documents and data sources are ingested into the Knowledge Fabric, with automatic schema detection, lineage discovery, and metadata synchronization improving over time. The DDU service refines its fact extraction patterns based on document processing outcomes, learning to identify legal concepts more accurately as it processes more jurisdiction-specific materials. Audit capability is built into every layer - the Knowledge Fabric maintains complete lineage tracking showing data flow and transformations, Document Management preserves immutable version history with source references, and all fact extractions include confidence scores and provenance trails. Contradictory information across documents is automatically flagged, low-confidence extractions trigger human review queues, and the system cross-references new documents against existing knowledge to detect inconsistencies. The fabric's metadata versioning and automatic schema monitoring ensure that as source systems evolve, data quality and lineage accuracy are continuously validated without manual intervention, creating a self-improving infrastructure foundation.