How governed SQL, a medallion semantic layer, and three query engines make enterprise data actually queryable — without hallucinated column names.
Most Text-to-SQL demos look great until you try them on real enterprise data. You ask “what were our top 10 materials by revenue last quarter?” and the model confidently returns a query that joins ORDERS to PRODUCTS — tables that don’t exist in your SAP system. Or it invents a column called revenue when the real one is buried inside VBAK.NETWR, a field whose meaning you’d only know if you’d spent years as an SAP consultant.
That’s the problem we set out to solve with Onibex ASK — Agentic Semantic Knowledge, an open platform that turns natural language into governed SQL over SAP data. The word “governed” is doing a lot of work in that sentence, and it’s worth unpacking exactly what it means and why it changes everything.
The LLM Should Be a Compiler, Not an Inventor
Most Text-to-SQL systems give the LLM a database schema and ask it to “figure it out.” That works surprisingly well for simple schemas — a handful of tables with obvious names. But SAP HANA schemas are not simple. A real S/4HANA system might have thousands of tables, cryptic four-letter field names, and join conditions that were designed for performance, not readability.
