An organization set out to transform how it resolves IT incidents - moving towards automation, and preventative resolution. To lay the foundation, we implemented a Generative AI solution that reclassified historical incidents and continues to classify new ones in real time. This enabled the organization to understand true incident patterns, improve routing accuracy, and prioritize automation efforts based on clean, structured data.

The client’s ITSM platform held years of incident data - but inconsistent classification by support teams made it difficult to identify which issues were recurring, automatable, or high-impact. Many tickets were broadly tagged or misclassified, undermining root cause analysis and automation planning. Furthermore, inaccurate classification led to inefficient routing, manual handoffs, and longer resolution times for end users.

We applied clustering techniques on historical incident descriptions to identify natural groupings of issues. Working closely with domain experts from both our team and the client’s IT operations, we validated and refined these clusters into meaningful categories. These categories were then configured within the ITSM platform to standardize classification going forward. On top of this foundation, we implemented a Gen AI-based auto-classification solution to classify new incidents in real time based on their descriptions — improving routing accuracy and enabling better analytics. This approach delivered clean, structured data without the need for prior labeled training data.