Implemented an Azure-native AI platform to automate large-scale document analysis and case processing, significantly reducing processing time and improving regulatory efficiency.
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The challenge
The organisation faced a massive backlog of hundreds of thousands of cases, representing hundreds of millions of pages requiring manual review. Traditional processes required full reading of case files, manual identification of key elements, and individual drafting of opinions and referrals. This approach was highly time- and resource-intensive, creating operational bottlenecks and making it impractical to process the backlog within a reasonable timeframe.
The approach
Designed and implemented a cloud-native solution leveraging Microsoft Azure, including Azure OpenAI, Azure AI Search, and Azure Document Intelligence. The platform utilised large language models, vector search, and computer vision to automate the analysis of complex documents, including technical reports and structured data. Azure Functions orchestrated workflows to process documents, interpret content, apply regulatory logic, and generate structured outputs such as referrals and recommendations. A governed Azure Landing Zone ensured scalability, security, and compliance.
The outcome
Delivered a highly efficient AI-driven platform that processed large volumes of cases with high accuracy, significantly reducing processing time from years to months. The solution improved operational efficiency, reduced bottlenecks, and enabled faster regulatory decision-making. It also increased internal satisfaction by reducing manual workload, while establishing a scalable and governed foundation for future AI-driven public sector innovation.
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