This work examines how Deep Learning(DL) are integrated with a specific web application. It is performed by creating various artifacts that examine the integration of a specific web application with DL. This is done with regards to future expansion of functionality and the value it offers to the stakeholders. The insights that arise during the work are communicated to the stakeholders through weekly meetings throughout the process. The paper ends with a conclusion that is based on the insight’s that are gained during the work. The conclusion is that the best method is the combination of two of the artifacts. A REST service developed in the Python language that can determine if an image contains animals or not. This REST service I used in an external program that works towards the same object storage that the system does. The program reads images from the storage and tests whether they are empty or not with through the REST-service. Pictures that are classified as empty will be removed from the systems object storage.