The Semantic Foundation — Why Your Data Agent Needs More Than RAG

The promise of “ask your data anything” has been around for years. The reality? Most implementations hallucinate metrics, confuse business terms, and break the moment questions get domain-specific. The difference between a demo and a production-grade data agent isn’t the model — it’s the data infrastructure and context underneath. In this episode, we unpack the building blocks that make talk-to-your-data agents actually work: ontologies that define what business terms mean, knowledge graphs that capture how concepts relate, metrics layers that encode executable business truth, and the data platform that ties it all together. We clarify what each layer does, where the hype exceeds reality, and what you actually need for your use case. Then we bring it to life with AutoScout24's Omnio — a specialist AI assistant covering 13 data domains, 153 benchmarks, and 9 purpose-built skills. AutoScout24 shares how they went from didn’t work to a production system and where every release is gated by automated evaluation against real business questions.