The Runtime component is built on top of the open-source Apache Kafka stream processing platform. The predictor components of the pipeline are the predictive models from Nirdizati Training. The topic components are network-accessible queues of JSON messages with publisher/subscriber support. This allows the computationally intense work of the predictors to be distributed across a cluster of networked computers, providing scalability and fault-tolerance. The collator component accumulates the sequence of events-to-date for each case, such that the prediction is a stateless function of the trained predictive model and of the case history. This statelessness is what allows the predictors to be freely duplicated and distributed. The joiner component composes the original events with the various predictions, ready for display on the dashboard.