Wyze Labs

Zendesk AutoTagging AI

Wyze needed a way to improve the accuracy and consistency of Zendesk ticket tagging, which had been time consuming to do manually and often varied across agents and support partners. The project developed an AI-assisted classification capability that used ticket comments together with call or chat transcripts to propose the appropriate tags and dropdown field values in real time, with an option to automatically apply selections when confidence was high. Integrated with Zendesk, the system was intended to surface suggestions, confidence levels, and brief explanations within the ticket workflow while capturing overrides for review. It also included evaluation, monitoring, audit logging, and privacy safeguards such as PII redaction and controlled logging. This capability was designed to reduce agent effort, improve data quality for routing and analytics, and support more consistent taxonomy use across support channels.