Helpdesk Ticket Classification and Answering
Implementation Time:
9 months
Solution Provider: AI Singapore
Daimler is one of the biggest producers of premium cars and the world’s biggest manufacturer of commercial vehicles with a global reach. They provide financing, leasing, fleet management,
insurance and innovative mobility services
- Over 12,000 helpdesk tickets are created globally at Daimler
- Todav helpdesk staff answer every ticket manuallv, although 70% of incidents have a known or standard solution
- As Daimler expands and more IT svstems are used, the number of tickets generated is outpacing the helpdesk’s team to answer them
How Daimler use machine learning techniques to build a model that can classify different free-text requests, and match them to a standard solution if it exists, in order to shorten the time it takes to resolve an incident?
A deep learning system was built to classify helpdesk tickets and provide instant answers:
- Models are trained on large set of past tickets and answers to past tickets
- AISG team developed an AI system that is able to classify ticket types, and route them to the correct helpdesk team or provide answers from a database if there is a good match
- Algorithms parse free-response text entered by the user into the helpdesk system
- The algorithm then predicts the type of helpdesk support being requested and retrieves the correct solution or escalates it to a human operator
OutcomesÂ
The system can automatically answer ~40% of incoming helpdesk requests
PDF Document
This is the last content of this tab. If you do not see any resources above, it means the solution provider have not provided any resources. Feel free to contact Solution Provider for more information.
Implementation Time
9 months
Use Case Brochure
