Abstract. We present a corpus-based approach for the automatic analysis and synthesis of email responses to help-desk requests. This approach can be used to automatically deal with repetitive requests of low technical content, thus enabling help-desk operators to focus their effort on more difficult requests. We propose a method for extracting high-precision sentences for inclusion in a response, and a measure for predicting the completeness of a planned response. The idea is that complete, high-precision responses may be sent directly to users, while incomplete responses should be passed to operators. Our results show that a small but significant proportion (14%) of our automatically generated responses have a high degree of precision and completeness, and that our measure can reliably predict the completeness of a response.