[{"data":1,"prerenderedAt":4},["ShallowReactive",2],{"raw-en-use-cases\u002Fai-governance":3},"---\ntitle: Model Governance\ndescription: How IQ:NS supports model governance by placing AI models, controls, and policies into a shared semantic framework.\nlang: en\nnavigation:\n  section: use-cases\n  label: Model Governance\n  order: 10\n---\n\n# IQ:NS for Model Governance\n\nModel governance needs more than model inventories. It needs semantic links between AI capabilities, controls, risk profiles, and organisational policies.\n\n## The challenge\n\nGovernance teams often struggle to connect models with the obligations they must satisfy. Models are identified in registries, while requirements live in documents and spreadsheets.\n\n## What the ontologies provide\n\n- **Model context** — represent model types, capabilities, use cases, and associated risks\n- **Policy linkage** — map models to the controls, obligations, and standards that apply\n- **Governance evidence** — query the knowledge graph for governance coverage and model-risk relationships\n- **Cross-team alignment** — ensure the same model semantics are used by engineering, risk, and audit teams\n\n## How it fits\n\nIQ:NS complements model registries with structured semantics. It does not replace your governance process, but it gives that process a shared vocabulary to work from.\n\n[Explore the ontologies](https:\u002F\u002Fgithub.com\u002Fiqns-org\u002Fontologies) · [Learn how it works](\u002Fhow-it-works)\n",1776235631603]