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Datenschaftler
DE

Case Study

Enterprise AI Assistant for Banking

How we designed and deployed a grounded AI assistant for a major banking institution, enabling secure access to internal knowledge and streamlined customer service workflows.

The challenge

  • Knowledge scattered across SharePoint, shared drives, and internal wikis
  • Slow manual search processes costing staff hours per day
  • Inconsistent answers across teams and departments
  • Strict regulatory compliance requirements for all AI systems

Our approach

We designed and deployed an enterprise AI assistant powered by Azure AI Search and Azure OpenAI, with semantic and hybrid retrieval, source grounding, and role-based access control. The system provides accurate, traceable answers with full source attribution, operating entirely within the bank's Azure tenant.

Architecture

The solution uses Azure AI Search for hybrid retrieval combining vector similarity with keyword matching, Azure OpenAI for generation, a custom indexing pipeline for document processing, Azure AD for authentication and access control, and Application Insights for monitoring and evaluation.

Architecture diagram

Results

60%

60% Reduction in average query resolution time

85%+

85%+ Answer accuracy with source grounding

Full

Full Audit trail for regulatory compliance

Secure

Secure Deployment within banking cloud infrastructure

Technologies used

Azure AI SearchAzure OpenAISemantic KernelAzure ADApplication InsightsAzure Blob Storage

Compliance and governance

The system was designed with banking-grade compliance from day one: role-based access control per department, full audit logging of all AI interactions, data boundary controls ensuring no information leaves the banking tenant, content safety filters, and human escalation paths for sensitive inquiries.

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