Enterprises rely on Standard Operating Procedures (SOPs) to govern critical operational decisions, yet these procedures are often maintained as static documents that require manual interpretation by employees. In practice, a human agent reads an SOP, identifies the relevant business concepts, retrieves data from fragmented systems such as CRM, billing, payment platforms, case management tools, data warehouses, and BigQuery, and then applies the required policy or process rule. This tutorial introduces an Enterprise Semantic Layer approach for transforming SOPs into agent-ready semantic assets. Participants will learn how to extract operational business rules from SOP documents, normalize them into reusable rule statements, tag them with Business Objects, and connect those Business Objects to source systems, datasets, tables, and data products. The tutorial will demonstrate how these semantic connections provide the grounding needed for multi-agent systems to retrieve the right enterprise data, explain their reasoning, identify missing Business Objects, and trigger ontology modeling tasks. Using a realistic billing/refund SOP scenario, the tutorial will walk through the full workflow: SOP ingestion, business rule extraction, Business Object identification, RDF materialization, source-system mapping, and agentic retrieval through a semantic layer. The session is intended for practitioners and researchers interested in knowledge graphs, semantic governance, enterprise AI, ontology engineering, and trustworthy multi-agent automation.
Enterprise Semantic Layer for SOP Automation and Agentic AI