Machine learning and case processing

As you triage email content in interaction cases, your application intelligently learns from your actions by using text analysis and the natural language processing (NLP) model saved in a text analyzer rule.

It makes an informed guess about the following items:

• Entities extracted from the email content
• A category representing the email content
• The sentiment (positive, neutral, negative) of the email content
• How to automatically route an interaction case in the future

For example, if you marked several similar interaction cases to be spun off as a regular case of a case type, the system will suggest the same case to be spun off in the future interaction cases that contain similar content.