Abstract: Systems and method are provided for implementing dynamic-action systems in real-time data streams. A computing device may generate a feature vector representing a portion of a real-time data stream. The computing device may execute a set of machine-learning models using the feature vector to generate a set of characteristics associated with the data stream. The computing device may determine that a condition of a trigger of a set of triggers is satisfied based on the set of characteristics. In response, execute a function associated with the trigger that is configured modify data that is to be transmitted over the data stream. The computing device may use another machine-learning model to monitor activation triggers and dynamically modify triggers to adjust the set of characteristics.