Worldwide demand of translation services has dramatically accelerated in the last decade, as an effect of the market globalization and the growth of the Information Society. Computer Assisted Translation (CAT) tools are currently the dominant technology in the translation and localization market. These include spell checkers, terminology managers, electronic dictionaries, full-text search tools, concordancers, bitexts, translation memory (TM) managers, and machine translation (MT) engines. Recent achievements by the so- called statistical MT approach have raised new expectations in the translation industry. So far, statistical MT has focused on providing ready-to-use translations, rather than outputs that minimize the effort of a human translator. The MateCat project aims at pushing what can be considered the new frontier of CAT technology: how to effectively integrate statistical MT within the translation workflow. Pursuing this objective is definitely relevant to improve the European competitive position in the multilingual digital market as well as its scientific and technological leadership in this area.Europe's flagship of statistical MT is currently represented by Moses, an open source toolkit\tnow widely adopted by research labs and SMEs around the world. MateCat will build on this asset by joining the forces of three research labs, including the developers of Moses, and a Web-based language service provider, owner of MyMemory, the largest TM in the world. MateCat will pursue its ambitious goals by: (i) establishing new operating conditions for MT in the CAT scenario; (ii) making MT aware of its use, self-tuning to the task, learning from the user feedback, and more informative; (iii) developing and field testing a new CAT tool integrating novel MT functionalities. To foster rapid exploitation, MateCat will release its main outcomes in open source and set-up a User Group, including end-users, service providers, and technology developers.