Projects

STAR-AI: Support Ticket Analysis and Resolution with AI

A Tool for Automating and Categorising Customer Technical Support Tickets

Funding: IFAB call for members

Enabling technology: Artificial Intelligence, LLM, Machine Learning

Sustainable Development Goals

The STAR AI project is transforming the way retail companies manage customer support requests. By leveraging advanced artificial intelligence and machine learning technologies, STAR AI automatically analyses thousands of support tickets and extracts valuable information to improve products and services. This innovative approach not only increases operational efficiency but also significantly enhances the customer experience by enabling faster and more personalised responses. STAR AI represents a major step forward in understanding consumer needs and opens up new opportunities for innovation in the retail sector.

Objectives

The project’s main objectives include developing an advanced analytics solution based on machine learning and generative AI, automating the classification of tickets into predefined categories, and analysing the sentiment of customer interactions with the support of large language models. The project also aims to extract key information from tickets using natural language processing techniques; benchmark different algorithmic solutions for interpreting consumer interactions; improve operational efficiency; provide strategic insights to optimise products and services.

Initial Challenge

The project addresses the need to manage an increasing volume of customer support tickets originating from multiple channels. To achieve this, it is necessary to overcome the limitations of manual ticket management, including inconsistent service quality for end customers, low operational efficiency, limited insights derived from ticket data, and poor scalability of existing systems.

Solution

To address these challenges, the project includes an analysis of existing processes and a mapping of available data sources, followed by the development of a machine learning model for the automatic classification of support tickets. Generative AI algorithms are also used for sentiment analysis and ticket interpretation, while Named Entity Recognition techniques are applied to extract key information from ticket content. The solution also includes the development of an integrated platform designed to improve service quality, operational efficiency and system scalability.

Benefits

The STAR AI project is expected to improve the quality of customer service by enabling the development of better products and services based on deeper consumer insights. It will also help strengthen brand trust and transparency while providing a more comprehensive understanding of customer behaviour. In addition, the solution will significantly reduce response times and increase operational efficiency, enabling large volumes of support tickets to be managed in a scalable way.

IFAB’s Role

IFAB participated in the project as a funding organisation, selecting it as part of its investment programmes in research, innovation and technology transfer. IFAB’s contribution consisted of recognising the project’s scientific and practical value and providing financial support, thereby enabling the technical partners to carry out the planned research and development activities. This involvement further confirms IFAB’s mission as an accelerator of high-impact initiatives for the local area and the wider production ecosystem.