Ratify the Service Logic standard
Work with the data committee to validate the ontology and schema, standardize them for Service Logic, and establish a conforming model built for the FSM, AI and AI agents.
WHY THIS STAGE EXISTS
AI and AI agents need one trusted, machine-readable service model before they can reason across records and take useful action.WORK PERFORMED
- DeepGlow works with the Service Logic data committee to validate the proposed ontology, field definitions, relationships and controlled vocabularies.
- Reconcile business-unit terminology and required data elements into one versioned Service Logic standard, with open decisions documented for committee disposition.
- Identify the future FSM's required entities, fields and integration constraints, then build those needs into a conforming schema without making the canonical model vendor-specific.
- Design the schema so AI models and AI agents can reliably interpret service history, connect evidence and use new capabilities without inventing meaning or bypassing governance.
- Deliver the ratified schema, decision log, conformance rules and acceptance criteria that govern the Bronze and Silver implementation.
RESULT OF THIS LAYER
A committee-ratified, versioned ontology and conforming schema that standardizes Service Logic data and provides a governed foundation for the future FSM, AI models and AI agents.
Service Logic gains one agreed model that reduces rework and gives AI and AI agents reliable data, relationships and context for new capabilities.