Speech technology (ST) is a growing industry, with an estimated annual compound growth of 16-19% in the next five years. The majority of ST development is targeted towards high-resource languages, such as English. Danish, as a low-resource language, risks falling behind technologically and missing revenue from this technology. Modern ST is based on ML algorithms, which require large amounts of data. Lack of Danish data is causing Danish ST to fall behind. The CoRal project will remedy this, by creating the first large-scale high-quality dataset consisting of 1,500 hours of transcribed Danish speech, both conversational and read-aloud, comparable in size to English state-of-the-art speech datasets, with eight models, incl. speech recognition and text-to-speech models. The dataset and models will be publicly available and enable use cases which were previously impossible even for some of the largest Danish companies e.g., ATP. Publicly available materials will be developed which will help companies implement the technology and allow SMEs to enter the area with minimal risk, as they can use models and data with almost no prior expertise. In addition, the project will ensure that the dataset represents all variants of spoken Danish, across regiolects, ethnolects, etc. This will allow authorities to provide speech services to all citizens, even marginalized demographics. The scale and diversity of the dataset will push Danish ST up to the highest standard commercially.