Generative BI and Natural Language Analytics
A natural language analytics interface allowing business users to ask portfolio questions in plain language and receive guided, contextual insights — reducing the analytics bottleneck in banking environments.
Business Problem
Business intelligence dashboards provide enormous analytical value — but only to users who know how to navigate them. Most business users understand the questions they need answered, not the filters, measures, and dimension structures. A small number of technical analysts serve a much larger population of data consumers, manually answering questions that a well-designed system should handle.
Solution Concept
A natural language analytics interface that sits above existing data infrastructure. Users ask business questions in free text. The system interprets the intent, identifies the relevant dimensions and measures, retrieves the appropriate data, and returns a structured, contextual answer — with guidance on related insights and drill-down options.
Architecture
Governance Considerations
Business Impact
Confidentiality Note: Due to employer obligations, code, raw data, proprietary models, and internal investigation details are not disclosed. This case study presents architecture, methodology, and business impact only.