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AI USE CASE

Internal text-to-SQL data Q&A

Let business users ask data questions in plain English and get accurate answers.

Typical budget
€15K–€60K
Time to value
10 weeks
Effort
6–14 weeks
Monthly ongoing
€500–€3K
Minimum data maturity
intermediate
Technical prerequisite
data engineer
Industries
SaaS, Finance, Retail & E-commerce, Professional Services
AI type
rag search

What it is

A text-to-SQL agent grounded on your data warehouse semantic layer translates business questions into validated SQL, runs them and explains the result with caveats. Reduces ad-hoc analyst load 50–70% and democratises data access safely.

Data you need

Curated semantic layer / dbt models in a data warehouse.

Required systems

  • data warehouse

Why it works

  • Strong semantic layer is the prerequisite
  • Always show generated SQL alongside the answer

How this goes wrong

  • Confidently wrong answers on ambiguous schemas
  • Users trust output without checking definitions

When NOT to do this

Don't deploy on a raw warehouse without a curated semantic layer — answers will be unreliable.

Vendors to consider

This use case is part of a larger Data & AI catalog built from 50+ enterprise transformation programs. Take the free diagnostic to see how it ranks against your specific context.