Mobile OS often exhibit defects due to their complexity and frequent updates, adversely affecting user experience. To resolve these defects, OS providers enlist beta users to test the OS. During testing, any defects encountered are recorded in tickets and reported back to the providers. However, the sheer volume of these tickets significantly challenges the efficiency of the ticket handling system, especially during the triage phase, where engineers assign tickets to appropriate development teams for resolution. Enhancing triage efficiency is possible by aggregating duplicate tickets related to the same defect, allowing simultaneous assignment of multiple tickets. Nonetheless, current ticket aggregation methods demand substantial labeled data for training, imposing a labor cost that hinders their practical implementation in production environments. To reduce this labor cost, we propose TixFusion, an LLM-augmented ticket aggregation framework. TixFusion employs unsupervised clustering to aggregate tickets, minimizing the need for labeled data, and integrates an LLM to extract discriminative information from tickets, improving aggregation accuracy. Extensive experiments using a dataset collected from the production environment of a top-tier global mobile OS provider H demonstrate that TixFusion outperforms existing methods while maintaining a low labor cost. Additionally, TixFusion has been deployed in H for over three months, processing more than 200,000 tickets, and has increased the processing speed of triage engineers by 3.78 times.