This work presents an approach to using artificial intelligence for sealing technologies: Cognitive Sealing. Cognitive Sealing applies artificial intelligence to sensor and actuator signals captured within the sealing system’s environment as opposed to directly embedded sensors within the seal. The feasibility of the approach has been proven for a rod sealing system in a hydraulic application based on different seal failure scenarios. To achieve this, a machine learning model for the detection of behavior scenarios was developed. The model infers possible anomalies without influencing the sealing system. Such a model could be the basis of a product-related service that allows the monitoring of a sealing system in a hydraulic application.