Use Case

Intelligent Application Maintenance Services

ABSTRACT
Application Maintenance is evolving toward an intelligent, data-driven model that combines automation and AI to improve request management efficiency and unlock the value of enterprise knowledge.

Where: Italy
Mission
Transform Application Maintenance into a more efficient, scalable, and intelligent service model that accelerates request handling and resolution, leverages organizational knowledge, and empowers operators to focus on higher-value activities. The goal is to evolve from traditional operations to a proactive, continuously improving model.
Solution

The model is embedded into existing operational processes without disrupting the tools already in use. Each request is automatically analyzed using historical data and application context to recommend proven resolution paths based on established knowledge.

Information from multiple systems is correlated to improve the quality of the analysis, while every resolved request enriches the knowledge base, creating a continuous learning cycle.

A human-in-the-loop approach ensures that operators retain decision-making control, guaranteeing service quality, reliability, and governance.

Digital Ecosystem
Actions
Digital Ecosystem
An integrated AI ecosystem supports the entire request management lifecycle by combining advanced ticket analysis, historical case matching, application context awareness, a dynamic knowledge base, and intelligent automation. Correlating information across these capabilities enables faster incident diagnosis, recommends resolution actions, and assists operators in their daily activities, driving a more efficient, proactive, and continuously improving Application Maintenance service.
Expected results

 

 

 

 

Shared and continuously updated knowledge

 

 

Improved service quality through faster and more consistent responses

 

 

Over 50% reduction in average ticket resolution time within 12 months

Markets
Ecosystems

Impacts

Technologies

To know more
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