Istella Process Automation integrates state of the art Natural Language Processing and Machine Learning algorithms with the aim of maximizing the efficiency of the business processes.
Istella Ticket Intelligence
Istella Ticket Intelligence learns from existing enterprise knowledge bases (data repositories, trouble tickets history, wiki, manuals, etc.) to automatically classify and route customers’ support requests.
The efficient management and routing of trouble tickets to the appropriate support team is of paramount importance to save time, guarantee user satisfaction and optimize allocation of team resources. In most of the Issue Tracking Systems, the assignment of the trouble tickets to the appropriate support group is still performed manually through a time consuming and error-prone procedure.
Istella Ticket Intelligence leverages on NLP and Machine Learning technologies in order to optimize the workflow of the trouble ticketing systems.
Istella Ticket Intelligence can streamline Help Desk workflow through:
Istella Ticket Intelligence uses patented machine learning techniques for auto-routing trouble tickets to the relevant person or support unit. Istella machine learning technology analyzes the archive of previously managed tickets and identifies patterns in how those tickets have been classified, routed and solved. When a new request arrives from a user (for instance via email), Istella analyzes the content of the request, predicts the ticket attributes and automatically routes it to the most appropriate support team. The system is able to automatically classify tickets according to their issue type, severity and skills required for the final resolution, speeding up the time-consuming manual procedures and improving accuracy.
As new trouble tickets are closed, Istella captures related information, learns and adapts its models for future predictions.
Automatic suggestions for trouble tickets resolution
Istella Ticket Intelligence leverages on the enterprise knowledge base (history of already managed trouble tickets, internal data resources, wikis, etc.) to provide support team members with suggestions on how to deal with specific users’ requests. Recommendations can be provided in term of previously managed tickets where a similar issue has already been solved or detailed documentation related to the issue.