predictive-intelligence

Predictive Intelligence automates ServiceNow incident routing and categorization by applying machine learning classification models to historical records, generating real-time predictions for proactive triage and assignment.

Anomaly detection for ServiceNow records uses machine learning clustering algorithms to identify statistical outliers and unusual patterns in numeric data, flagging incidents or changes that deviate from normal operational behavior.

Yes, machine learning similarity and clustering algorithms group related ServiceNow records by matching text and numeric features, enabling faster triage by surfacing similar incidents, problems, and changes for consolidated resolution.

Train regression machine learning models on historical ServiceNow data to predict numeric outcomes and suggest next actions, enabling the platform to recommend proactive steps to agents during triage.

To train an ML solution and test classification accuracy, define the ml_solution and related ML tables, train the model on historical incident data, then use the provided tooling to validate predictions and monitor model accuracy.

Prerequisites for Predictive Intelligence include defining the ml_solution and related ML tables, gathering sufficient historical incident or change records for training, and configuring the tooling to test predictions and monitor accuracy.