Legal Tech
Wolters Kluwer
Self-service analytics in natural language
A Q&A platform where business users query controlled datasets in natural language — backed by a semantic layer linking business concepts to data structures.
Results achieved
Faster decision making
Explainable results
Analysts freed for depth
The challenge
Operational questions about product groups, market segments and campaigns required analytics support every time — slowing decisions and burning analyst time on repetitive ad-hoc requests.
Our approach
- 1.Semantic layer linking business concepts to data structures
- 2.Natural language to SQL with controlled execution
- 3.Open architecture inside the client's existing cloud environment
- 4.Validated pilot with business users
The solution
A self-service Q&A platform where business users query controlled datasets in natural language. The semantic layer — not the LLM alone — keeps results consistent, explainable and reliable.
AzureLLMSQLSemantic layer