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

1. Online customer segmentation

2. Predictive service maintenance

3. Behaviour anomaly detection

4. Best next action

5. 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