New research project will translate algorithms and artificial intelligence into state-of-the-art customer support
AI, Artificial Intelligence
During the next two years, research scientists in algorithms, information search and machine learning, in collaboration with Danish companies and with the Innovation Fund as the grantor, will explore new methods for optimizing customer service systems.
Illustration: By Soniachat8
Improved customer service systems can be achieved using chatbots and artificial intelligence
Who hasn't experienced a telephone or web-based customer service where something went wrong, where the process became unnecessarily complicated, or the response from the system was useless? A new innovative collaboration between a group of researchers from the Department of Computer Science at the University of Copenhagen, as well as a number of public institutions and private companies express great ambitions to apply the latest research in algorithmic, artificial intelligence and information retrieval with the aim of reaching new solutions and unprecedented performance in customer service systems.
The key element of the project is to combine artificial intelligence with traditional customer service disciplines such as expert finding, ticket routing as well as answering questions and finding solutions. At the same time, efficient algorithms will be developed to support the entire system.
University researchers and companies join forces to solve the task
The people behind AMAOS are some of the University's leading researchers, hand picked for the assignment. Professor of Algorithm Stephen Alstrup, who will develop the algorithms, explains:
"With the help of artificial intelligence and machine learning, we can create algorithms that make customer service platforms reach new levels of unseen speeds and results. Our goal is - modestly expressed - to create world-class customer service."
Other prominent project members are Professor Anders Søgaard, researcher in NLP (Natural Language Processing), as well as associate professor Christina Lioma, who is anexpert in Information Retrieval, deriving structured information from apparently unstructured data.
In addition, the consortium comprises he startup company SupWiz, which consists of a group of computer scientists that specialize in developing intelligent tools for customer service and support based on machine learning. Several of SupWiz's employees, including Søren Dahlgaard, himself, have a research background with a PhD from University of Copenhagen and several completed research projects on the CV.
"There is no doubt that this research-strong consortium will put us in a unique position to revolutionize the landscape within customer support." says Søren Dahlgaard, co-founder and Chief AI Officer of the startup company SupWiz.
The company NNIT and the Municipality of Copenhagen contribute with business understanding and the practical possibilities of bringing the solutions into practice. A number of other companies participate for use cases.
The consortium expects the new method, once developed, to have a significant export potential and in the long term may furnish Danish companies with a competitive advantage within customer service
Facts about the project:
- Innovation fund investment: 5.2 m DKK
- Total project budget: DKK 11.2 M
- Duration of project: 2 years
- The project's official title: AMAOS - Advanced Machine Learning for Automatic Omni-Channel Support.
Professor Stephen Alstrup
University of Copenhagen
firstname.lastname@example.org, phone: +45 35 33 56 91
Chief AI Officer Søren Dahlgaard
email@example.com, phone +45 27 59 84 99
Communication Officer Inge Hviid Jensen,
Department of Computer Science, University of Copenhagen
firstname.lastname@example.org, phone: +45 28 75 14 28