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Stories of our customer success
Discover our repository of case studies that showcase real-world examples of how we are modernizing data for customers.
Optimizing Incident Management: 30% Faster Response, 25% Reduced Handling Time
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Highlights
AI-driven text and image-based classification improved categorization quality and consistency.
Real-time category recommendations automated routing, reducing manual overhead.
Enhanced customer satisfaction (CSAT) with faster, more accurate incident handling.
Overview
An organization in the government IT services sector faced significant challenges with inefficient incident categorization for citizen inquiries and IT Service Desk submissions. Manual errors and delays were causing slow routing and resolution times. We implemented an AI-driven categorization model on Azure to help the organization automate classification, improve accuracy, and accelerate service delivery across its Oracle Service Cloud (OSvC) platform.
Client
A major North American municipal IT services provider
Geography
CA, USA
Industry
IT Services / Government
Offering
Azure Data Factory, Azure Blob Storage, Azure Machine Learning, Azure App Service
The Challenges
- Inefficient and incorrect incident categorization led to frequent manual interventions.
- Delayed routing and longer resolution times impacted service levels.
- Inconsistent categorization reduced first contact resolution (FCR).
- Manual processing increased operational costs and lowered customer satisfaction.