Semantic MDM (Semantic Master Data Management) applies the disciplines of enterprise MDM — golden records, entity survivorship, schema stewardship, and change governance — to the outward-facing semantic layer of a website or digital platform. Where traditional MDM governs master data inside the enterprise (customers, products, suppliers, employees), Semantic MDM governs the machine-readable entity definitions that AI agents, search engines, and agentic commerce systems encounter at the AI-facing boundary. The process runs in three stages. First, Audit: accessible entity definitions across the agreed domain scope are crawled, validated against Schema.org, and assessed for duplicate @id references, conflicting definitions, orphaned nodes, and semantic misalignment between declared meaning and operational intent. This is the Semantic Entity Assessment, the diagnostic equivalent of a data quality assessment before MDM implementation, with results in minutes. Second, Enrich: entity conflicts are resolved, canonical @id references are established, and survivorship rules are applied to produce a single authoritative definition per entity — the Golden Entity Record. Third, Publish: the validated entity layer is compiled into a Semantic MDM Data Catalog — a machine-readable, AI-traversable index of all golden entity records, maintained through agreed updates and governance; where configured, change data capture supports alignment with operational sources. In VISEON, Semantic MDM for the website is delivered by VISEON for Web, which serves the golden entity records to people through VISEON Ask and to AI agents through its own MCP server. VISEON for Enterprise applies the same discipline inside the organisation: one canonical identifier and definition per entity, linked to every system's version of it. For Qlik Cloud estates, VISEON for Qlik (vCat) governs the meaning of master measures and dimensions, and VISEON Data Assurance tests the master data itself, row by row. The parallel to traditional MDM is direct: just as MDM eliminated duplicate customer records across ERP and CRM systems, Semantic MDM eliminates duplicate entity definitions across the knowledge graph, giving connected AI agents a shared authoritative source of entity definitions and evidence.
