IBM's Technical Support Services division runs remote support centers, where agents provide phone support for client problems related to IBM and non-IBM hardware and software products. Support center personnel use numerous pieces of information - including many searches, log files, and records of historical support tickets, from disparate data sources - to recommend solutions for customer technical problems. We have built an advanced search system to assist support agents who are resolving customer service requests and improving our client experience. The system has been deployed and used globally by thousands of support center personnel. In this paper, we describe the system's architecture, the technical challenges, and the innovative solution we have built. In addition, we discuss the novel ideas to address the unique requirements and challenges of the support services domain. These ideas include using system logs and domain knowledge to automatically expand agent queries, incorporating implicit agent feedback, and selecting features to extract useful information from highly unstructured and noisy ticket data. Results on the effectiveness of the system are presented. We also discuss future work on enhancing the system's capability to automatically diagnose customer hardware and software problems and remediate them.