Nuvama (Leading Wealth Management Organization)

The organization's Relationship Managers struggled with siloed information spread across SharePoint and AWS, making it difficult to efficiently access client portfolio data. KPI computation (XIRR, Revenue, Asset Allocation) required high manual effort through spreadsheets. Document discovery relied on slow, exact-match search across large repositories, significantly hampering productivity.

Exponentia.ai built an end-to-end GenAI platform featuring RAG-based retrieval for conversational access to unstructured documents with citation-backed answers, and a Text-to-SQL engine converting natural language queries into SQL against structured portfolio datasets. The solution was integrated into Microsoft Teams and a Prism web application, with RBAC enforcement ensuring RMs only accessed their own client portfolios via a secure AWS backend.

Relationship Managers achieved significant reductions in manual spreadsheet effort and document searching time. KPIs and charts are now generated instantly over pre-computed datasets, enabling real-time analytics. The platform also established a scalable data governance foundation to support future GenAI expansion.

• Combining RAG pipelines with Text-to-SQL agents enables a unified conversational interface over both unstructured and structured enterprise data
• RBAC enforcement at the AI layer is essential for regulated industries where data scoping per user is a compliance requirement
• Integrating GenAI into existing tools (Microsoft Teams) accelerates adoption without requiring workflow changes