xOpat is a powerful digital pathology viewer. It's flexibility outperforms other available solutions. However, the viewer deployment requires skilled administrator with xOpat API knowledge. For now, the viewer is suitable mostly for infrastructure-level deployment, and it is hard to install for common users, including pathologists. The goal of this thesis is to bring this viewer closer to general public by implementing a desktop application able to simply browse pathology slides, and view them. The application should provide intuitive installation wizard for Windows and Linux, at least. The viewer runtime should hide any consoles windows (except for Linux) to improve user experience. Another goal is to integrate the viewer with Jupyter notebooks to bring simple interface to researchers who need to visualize their data. The notebook integration requires simple installation through python package installer, and ability to open notebook-local data with arbitrary viewer session configuration. The deployment routine should be automated to ease releases of new versions. The xOpat viewer and the work surrounding it is licenced under MIT.