Preference-based search is the problem of finding an item that matches best with a user's preferences. User studies show that example-based tools for preference-based search can achieve significantly higher accuracy when they are complemented with suggestions chosen to inform users about the available choices. We present {\tt FlatFinder}, an implementation of an example-based tool and discuss how such a tool as well as suggestions can be efficiently implemented even for large product databases.