Identify all streaming data sources. Ask: Which events hold predictive value? Prioritize high-velocity, high-volume streams (clickstreams, telemetry, logs).
A feature store (e.g., Feast, Tecton) is critical for Smart ESP. It allows historical and streaming features to be served to models consistently. Without a feature store, your predictions will suffer from training-serving skew. smart esp
Smart ESP offers a path to anticipatory systems—machines that see around corners, processes that self-heal, and decisions that are both lightning-fast and deeply contextual. By moving from static rules to dynamic intelligence, you transform your data streams from a record of what happened into a forecast of what will happen next. Identify all streaming data sources
Within five years, we will see , where multiple edge-based ESPs share model updates without sharing raw data—preserving privacy while boosting collective intelligence. Conclusion: Is Your Organization Ready for Smart ESP? The question is no longer if your organization needs event stream processing, but how smart that processing needs to be. In a world where markets move in milliseconds, supply chains are global, and customer expectations are instant, reacting to the past is a recipe for obsolescence. A feature store (e