At Across, we have experienced this paradigm shift at first hand in recent years, and we have also seen it play out among our customers. According to customer interviews, our customers see clear trends in their companies: the orders are getting bigger, efficiency and cost pressures are increasing, translations are being made into more and more languages, and so on. The majority of the customers we interviewed are also certain that MT is the future. However, many still say that they do not use MT in their translation processes.
We asked ourselves: What is the problem? The answers we received were clear: companies have too little time to deal with the topic, the topic is too complex, it is hard to get an overview, and support is needed to move forward.
Across conducted intensive research to identify potential areas of opportunity for bringing about the perfect interplay of human and machine. We have seen that the potential is definitely there, but in order to take full advantage of it, it is necessary to develop new features for machine translation that MT vendors have not yet brought to the marketplace. One thing is clear: In the future, a translation management system or a CAT tool will only be successful if it is extensively linked to an MT system. However, without our own MT or a close partnership with a specific provider, we will not be able to achieve our goals.
We weighed all the options and alternatives, but it was clear to us at the end of our research process: We must and will develop our own MT system—AcrossMT. Why? We want to bring the data in-house, we don't want a black box or dependencies, and we want to have an impact on data quality and connect the MT to our own systems. This approach will accelerate our processes and ensure better translation quality for our customers.
However, our system is not meant to be just another one of many that you connect to the translation management system (TMS) via an application programming interface (API). No, we are developing a completely new product with the MT system at its core. However, by the time this product is launched, we will already be able to offer features that will set us apart: For example, data will be regularly exchanged between AcrossMT and the Across Language Server. Based on these data, the engines are constantly retrained. This makes sure that all available data are used and the engines progressively get better.