Hapag-Lloyd, the only German shipping company among the top five global container shipping companies, is increasingly relying on artificial intelligence (AI).
Hapag-Lloyd is convinced that state-of-the-art technologies will help it to master the complex challenges currently facing the shipping industry. This is why the company has placed a focus on innovative digital solutions as part of its Strategy 2030. The aim is to achieve a punctual delivery rate of 80% and to optimise performance and costs.
Haapi Assistant for efficient interface management
The Haapi Assistant, which is based on generative AI, supports Hapag-Lloyd’s staff in managing interfaces (APIs) and enables smooth communication between the various teams. Business analysts at the liner shipping company are in contact with customers and have to answer API-specific questions, such as whether a track and trace interface is available and how customers can use it.
In the complex and fast-moving environment of container shipping, information can often only be obtained after lengthy research, as various teams are involved. Not everyone involved always has the same information base or knows how to create a ticket to resolve an IT problem, for example. As a result, the business analysts and project managers sometimes need up to a week to answer the request and invest up to six working hours. The long processing time, in particular, can have a negative impact on customer satisfaction.
Workflow improved by up to 96% in the pilot project
The “Haapi Assistant” uses an architecture based on the IBM data and AI platform watsonx. The Haapi user can not only identify the correct project manager and provide contact information, but also provide general information on Hapag-Lloyd’s interface management. This speeds up research and the response to customer inquiries.
Development teams can also use the digital assistant. This helps them to complete their tasks and rectify HTTP errors. Instead of spending time checking various sources of error, “Haapi” uses internal sources such as log files to give the developers clues as to which factors may be decisive, such as an incorrectly set date parameter. In the pilot project, the teams were able to improve the workflow by up to 96% by using “Haapi”, according to Hapag Lloyd.
