AI is accelerating a data deluge. Everyone’s expected to make sense of it, but not everyone is a SQL or Python expert. Conversational BI and natural language querying promise to democratise insight, yet opinions swing from “silver bullet” to “demo-ware”. The missing piece? One size doesn’t fit all, the engine under the bonnet matters.

Beneath every “chat with your data” demo is one of four engine modes: strict semantic parsing, ontology/graph reasoning, direct LLM-to-SQL, or a hybrid that grounds LLMs on a governed semantic/metrics layer. In this vendor-neutral session, you’ll learn how to identify which engine your use case needs, how to spot what vendors are running under the bonnet, and when building the engine yourself is the right call. You’ll leave with an engine archetype map, a buyer’s checklist to pressure-test vendor claims, and a pragmatic pilot plan you can run on your stack, without over-spending or over-promising.