AI-Powered IT Ticket Analysis Framework Using Machine

Abstract

As organizations expand their IT systems, the number of support requests from users keeps growing. Manually sorting and prioritizing these requests is slow and prone to mistakes, which can really hurt service quality. This study presents an AI-powered IT ticket analysis system to tackle those issues.It uses a machine learning approach to automatically sort and prioritize tickets and to provide useful analytics too. Specifically, the system classifies tickets using TF-IDF and Logistic Regression. It looks at aspects like term frequency and inverse document frequency to slot tickets into categories, such as system, network, hardware, or software problems.Besides sorting, the system determines how urgent each ticket is, helping speed up problem resolution. Built on a Flask REST API, it integrates machine learning predictions, feature engineering, an SQLite database, and Power BI for easy-to-read dashboards.