Neta, Engineering’s software platform dedicated to the Energy & Utilities sector, is featured in an Atlassian case study that highlights the evolution of its Application Management Services (AMS) model through Jira Service Management, Confluence, and Artificial Intelligence.

The case study describes how Neta transformed its approach to application service management by making corporate knowledge more accessible, accelerating ticket resolution, and improving operational efficiency through an integrated ecosystem of Service Management and AI.

Context

Neta supports Energy & Utilities companies across the entire Meter-to-Cash process through a modular platform covering CRM, Billing, Metering, ERP, and Workforce Management.

Supporting the platform is a team of approximately 700 professionals located across Italy, Spain, and Brazil, delivering Application Management Services while ensuring operational continuity, user support, and application governance.

As operational complexity increased and support requests continued to grow, Neta recognized the need to evolve its service management model by leveraging corporate knowledge and unlocking the full potential of Artificial Intelligence.

The Challenge

Before the transformation, the information required to resolve support tickets was scattered across multiple repositories and tools, making it difficult to find the right knowledge and increasing dependence on highly experienced specialists.

Many requests required escalation to second-level support, resulting in a growing number of escalations and a heavier workload for senior professionals.

The objective was to create a model in which every operator, regardless of experience, could quickly access the information needed to manage tickets independently, consistently, and efficiently.

The Transformation

The transformation began by centralizing corporate knowledge within Confluence, consolidating more than 7,000 documents into a shared knowledge base.

On this foundation, Neta built a new Service Management model powered by Jira Service Management and enhanced with AI agents designed to support specific operational processes.

The intelligent agents automatically analyze tickets, search existing documentation, identify similar resolved cases, and recommend potential solutions to operators. At the same time, the system automates ticket classification and assignment, routing requests directly to the most appropriate teams.

This approach transformed support management from a reactive model into a knowledge-driven system where people, processes, and Artificial Intelligence work together to improve service quality and operational efficiency.

Results

The results highlighted by Atlassian demonstrate the value of this transformation:

• 35% reduction in escalations from first-level to second-level support.
• Zero average ticket assignment time thanks to automation.
• More than 7,000 documents centralized in a shared knowledge base.
• Greater operational autonomy for AMS operators.
• Faster onboarding of new team members.
• Improved workload distribution across support teams.

According to the case study, 69% of team members actively use AI capabilities, while more than half of users report time savings ranging from 10% to 30% when managing support requests.

A Model for the Future of Enterprise Service Management

This initiative represents another important step in Neta’s innovation journey toward a smarter, more integrated Enterprise Service Management model focused on maximizing the value of data and organizational knowledge.

The goal is to progressively extend this approach to additional business processes, continuing to put Artificial Intelligence at the service of people to improve the quality, speed, and consistency of the services delivered.