Case Study

Maximising help desk efficiency with Generative AI

Discover how a multinational energy company has automated its help desk system, providing fast and timely support to users' needs.

# Ticketing automation
# RAG methodology

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The challenge

To automate the ticket management process for an immediate response to requests for assistance on applications and systems used by internal users.

scenario

The limitations of the traditional help desk model

In many large companies, managing technical support tickets represents a complex challenge that must balance effectiveness and speed of response. A multinational company in the energy sector, which operates globally, must manage a large volume of requests from internal users every day. A flow that often numerically exceeds the operators' available resources, generating response times that extend up to several days.
These requests have so far been managed through traditional ticketing platforms, using various applications and services. Every ticket is often reviewed and assigned manually to operators. Consequently, due to the complexity of specific issues or the need to gather further details from users, the procedures often lengthen, causing potential inefficiencies.

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THE SOLUTION

Artificial intelligence and RAG methodology

To face these types of challenges, the RAG (Retrieval Augmented Generation) methodology today represents an ideal approach for optimising processes. Data Reply chose it and used it to implement an ad hoc solution for the customer. Using the power of LLMs, the developed solution is able to analyse and understand the type of request contained in the ticket, identify the most relevant technical documentation and generate the appropriate response for solving the problem. This automated process allows you to generate timely and accurate responses, and to update the status of tickets in real time. In addition, it ensures responses are always up to date thanks to constant and automated monitoring of new technical documentation. The solution offers great flexibility, supports different languages (Italian, English and Spanish) and is applicable in various areas.

How did we do it

Automation and optimisation of responses

Integration into the existing platform

The solution has been integrated into the customer's ticket management platform, using a microservice architecture, which helps to ensure constant monitoring of system components and documentation.

Automated ticket management

LLM models read and understand tickets, consult documentation, and provide automated responses. If necessary, they request additional information from users or redirect tickets to the specific support group.

Monitoring and control

A control service constantly verifies the state of the platform, identifying any problems, thus guaranteeing a double level of verification, before the intervention of generative AI.

The results

Fast and accurate support

The integration of Generative AI has transformed the way in which support tickets are managed, bringing efficiency and innovation to the customer's help desk. With this solution, the energy company can now guarantee a fast, precise and highly personalized technical support service, effectively responding to user needs. The immediate benefits were:

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Rapidity


The tickets are now resolved rapidly thanks to the answers generated promptly by the AI

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Efficiency


Reduction in the number of tickets redirected to the second level (more technical department) and immediate resolution of many problems, immediately after being reported

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Ongoing support


Constant monitoring and automatic updating of technical documentation

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Improved user experience


Users receive faster and more accurate answers, improving their overall satisfaction

Data Reply, as part of the Reply Group, supports customers in becoming data-driven. Data Reply is active in various industries and business areas and works intensively with customers so that they can achieve meaningful results through the effective use of data. To this end, Data Reply focuses on the development of data analytics platforms, machine learning solutions and streaming applications - automated, efficient and scalable - without compromising on IT security.