Despite the impressive amount of recent studies devoted to improving the state of the art of Machine Translation (MT), Computer Assisted Translation (CAT) tools remain the preferred solution of human translators when publication quality is of concern. In this talk we present our works on improving the commercial bilingual concordancer TransSearch, a Web-based service whose core technology mainly relies on sentence-level alignment. We report on experiments which show that it can greatly benefit from statistical word-level alignment.