Elasticsearch's inference pipeline aggregation allows users to apply new machine learning models to already indexed data, offering flexibility and real-time predictions without needing to reindex. This feature enhances the capabilities of the ingest pipeline by enabling inference at the search stage, allowing businesses to leverage existing data for predictive analytics, such as identifying customer churn. The process involves a trained model, such as one predicting telecom customer churn, applied using a composite terms aggregation on customer call data. The predictions can be visualized using Kibana's Vega plugin, transforming complex data into intuitive dashboards. This approach facilitates better business decisions by enabling quick and efficient use of historical data, with users encouraged to experiment through a free trial of Elastic Cloud or local machine learning installations.