Translate business intent into governed schemas more efficiently by placing AI at the forefront of your modeling workflow. Feed user stories, sample reports, and a controlled glossary; the assistant proposes candidate domains, dimensions, facts, and relationships, plus draft DDL with keys, constraints, and naming conventions. It flags conflicts in terminology, maps metrics to calculation logic, and sketches lineage from source systems to curated tables. Analysts validate assumptions, tighten grain and surrogate keys, and choose slowly changing dimension strategies. Next, auto-check proposed models against sample data for nulls, cardinality issues, and referential integrity; generate tests to ensure changes remain safe. Version models as code, review via pull requests, and publish to a semantic layer so BI, APIs, and notebooks share consistent KPIs. You retain the final say—AI accelerates the draft, allowing humans to focus on correctness and adoption.