Abstract: Systems for providing a contact center system detect patterns in the behavior of service agent users and customers having a customer service issue. The system records activity data describing interactions of the users with a virtualized contact center and with each other; the activity data is aggregated and then analyzed (e.g., using a machine learning engine) to measure one or more metrics that define a behavior pattern. The analysis identifies an intent expressed by customers having a common issue, and further identifies attributes of the intent as well as the actions taken by the service agents in response to the intent. The system uses the analysis to generate a workflow of potential interactions that resolve the issue. The system automates the workflow by generating and deploying a computerized service agent configured to interact with customers of a contact center and execute the workflow.