ML inferencing

Leverage streaming online predictions to drive insights to action

Overview

For cutting-edge stream-based use cases, the incorporation of machine learning models is integral for next best action processing.

Out-of-the-box, Joule offers the capability to seamlessly deploy JPMML models within a processing pipeline using a predictive processor.

Learn more about Joule's ML inferencing architecture here.

Joule provides the capability to perform near-real-time predictions to enable best next action use cases.

Use cases

• Online customer segmentation

• Predictive service maintenance

• Behaviour anomaly detection

• Best next action

• Customer conversation scoring

Available ML inferencing options

Online predictive analytics

JPMML prediction processor evaluates event feature vectors in near-real-time

Feature engineering

Decorate a feature vector with enriched features specific to the deployed model

Model audit

Monitor model predictions and performance metrics to support explainability, detect drift, and manage retraining

Model management

Deploy a retrained model directly in to a running Joule with zero down time