We have developed GAMMI, an approach to the inference of cis-regulatory modules that employs an evolutionary search to identify modules conserved across a set of DNA sequences from different species. This paper describes the motivation and system design for GAMMI, and presents the results of initial tests of the system using artificial sequences with implanted artificial modules. Based on these preliminary tests, GAMMI appears to be a promising approach to the module inference problem.