Digital processes and fully automated data processing are already making a significant contribution to the economic success of the logistics sector. The digital processing of the supply chain in the WMS leads to faster throughput times and a better process overview. But the potential is far from exhausted: Logistics Reply has developed the AI-based assistant Leapedia for the WMS to make daily work with the warehouse management software easier and more efficient. The module is based on a multi-agent AI engine that facilitates the analysis of enormous data sets and identifies patterns.

The language model was developed to interpret and respond to requests and commands in natural language. The intelligent search function enables quick and intuitive access to information ranging from specific terms to complex process descriptions. This allows users to interact efficiently with the user-friendly system. If the description in the system is not sufficient, employees receive a link to the online user manual. This significantly reduces search times. The program recognizes input questions in natural language and answers them in that language. With the AI assistant, users can access important information in the WMS regardless of their qualifications, without having to use technical jargon.

High user autonomy for higher productivity

With the WMS application, employees do not waste time with manual searches, but receive the information they are looking for on processes, specialist terminology, system configurations and more directly at a glance. The precise and consistent results reduce potential human error when searching for information. Entering queries and commands in natural language and the intuitive user interface boost efficiency and increase user autonomy: the ease of use reduces the need for support queries during operation. Regardless of the knowledge and language background of the employees, the AI-based assistant understands questions without specific keywords and technical terms - the use of such an assistant can thus counteract the shortage of skilled workers. The application can also be used as a training tool for new employees by providing best practices, instructions or general information on the WMS functions. At the same time, the learning curve for using the WMS is accelerated enormously and productivity is increased. The workload of specialist staff is reduced in the long term and they can use the time gained for other value-adding activities. By saving time, logistics companies, e-commerce retailers and SMEs benefit from freed-up personnel capacities.

AI integration without production downtime

Leapedia is specifically tailored to the respective customer requirements and software environments. This makes the application suitable for different user groups - from small companies to medium-sized transshipment centers and wholesalers. According to the provider, the module can be integrated into the system in a very short time without slowing down or interrupting operations. It can also be updated during ongoing operations.

The AI assistant obtains the database from the information available in the WMS. The module allows the use of different sources of information, which can be customer-specific. "Leapedia is integrated into the WMS Lea Reply, which is based on microservices. These are independent software components with which new processes can be developed individually," explains Alexander Edelmann, Associate Partner at Logistics Reply. This means that freely selectable modules can be put together and updated as required.

AI perspectives for the WMS

Leapedia is one of three AI pilot projects in Lea Reply with which Logistics Reply wants to make the WMS even more efficient, simpler and clearer. In addition to Leapedia, the new AI software applications include Lea Smart Search and Lea Executive Cockpit. Lea Smart Search enables users to submit data queries to the system in natural language without having to select tedious search attributes in the system for manual search queries. This saves time for control room personnel and administrative staff at a logistics site, who often spend hours every day searching and analyzing data. The Lea Executive Cockpit is an application that analyzes and prepares operational data for a management view, giving decision-makers an overview of current business operations at a glance. By integrating the AI-based assistant Leapedia, managers can also work more time-efficiently. Thanks to the technology described above, the system responds to questions entered in natural language with the desired answers and provides decision-makers with the information relevant to the situation at hand.

With an AI assistant, companies can make the use of their WMS more efficient. At the same time, the WMS assistant relieves the burden on employees in the long term, reduces the susceptibility to errors when searching for information and significantly shortens search times. This frees up staff capacity that can be used for other value-adding activities.