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In a traditional customer service support environment, service engineers typically provide a worldwide customer base support through the use of telephone calls. Such a mode of support is inefficient, ineffective and generally results in high costs, long service cycles, and poor quality of service. The rapid growth of the World Wide Web and Intelligent Agent technology, with its widespread acceptance and accessibility, have resulted in the emergence of Web-based and AI Agent-based systems. Depending on the functionality provided by such systems, most of the associated disadvantages of the traditional customer service support environment can be eliminated. This paper describes a framework for Web-based and AI Agent-based online customer service support system, and discusses the method to use Rough Set Theory and Neural Network Theory to support intelligent fault diagnosis by customers or service engineers.