Save costs and time in your business by making better and more reliable decisions

In a typical administrative business process, important decisions are constantly being made such as:

• which employee should handle an incoming request,
• which service should be recommended to a specific customer,
• how should a specific product be configured to meet a customer's requirement,
• is a particular customer entitled to a discount
• ...

Each decision maker in this can be supported by a system that helps complete the process faster, with more reliability and consistency. The typical black-box AI methods (such as deep learning) are not suitable for this, though, because they lack much-needed transparency and reliability ("Why was it sent to that person?").

A more promising approach are knowledge-based AI systems, which derive their "intelligence" not from data, but from logical models of rules, regulations and expert knowledge. In this workshop, you will be introduced to the advanced IDP knowledge base system, developed at KU Leuven. Companies in the manufacturing, financial and legal sectors already use it with their customers, but equally internally, to provide various types of decision support.

This system is based on methods and techniques developed for declarative programming systems such as Prolog, but it offers a number of important innovations:

1. instead of focusing only on queries, the IDP system provides a wide range of different functionalities to build rich interactive interfaces to provide support to users in different workflows,
2. instead of relying on programmers, end users can maintain the underlying knowledge base, meaning we can cut out the "middleman" of IT staff and let the business experts update the system themselves. This not only reduces costs and turnaround time, but also puts ownership of decision knowledge in the right hands.