Designed and delivered an Azure AI solution for an internal AI agent that accelerates and standardises responses to complex domain-specific RFIs, establishing a secure and scalable foundation for AI-assisted knowledge workflows.
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The challenge
The organisation faced increasing volumes and complexity of RFIs, requiring subject-matter experts to manually search distributed documentation and repeatedly re-author similar responses. This led to long turnaround times, inconsistent answers, and limited reuse of validated knowledge, while operating under strict governance and regulatory constraints.
The approach
Conducted a structured assessment of the existing data and knowledge landscape, then implemented an Azure-native RFI Management Agent using Microsoft Foundry, Azure OpenAI, and Azure AI Search. The solution enabled automated ingestion of RFI documents, AI-assisted answer suggestions using retrieval-augmented generation, and a human-in-the-loop workflow for review, collaboration, approval, and export - all deployed within the customer’s Azure tenant and aligned to Microsoft’s Well-Architected Framework.
The outcome
Successfully demonstrated measurable productivity and quality improvements in RFI response workflows. Validated the technical feasibility, security, and scalability of Azure AI for regulated environments, and provided a clear architectural and operational roadmap to support future AI-enabled use cases.
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