Topstar GmbH is one of the largest seating furniture manufacturers in Europe. With its TOPSTAR and WAGNER brands, it has been developing not only innovative seating and table solutions for almost 50 years, but also designing complete rooms with inspiring ideas for offices, hotels, restaurants, and public spaces. 400 employees work enthusiastically to provide expert support for all customer requirements, from conception to implementation. The company supplies over 50 countries worldwide.

For over 20 years, Topstar has been active in scientific research in addition to its economic activities and has implemented a large number of projects in this field. The company actively helped shape the beginning of Industry 4.0, the precursor to today’s AI age, and in 2018 integrated fully functional robotic vehicles into a completely redesigned real-time production facility for high-quality seating furniture from the WAGNER brand.

First step:
Real-time production with AGVs (Autonomous Guided Vehicles)

Within just 12 months, the “STEPS” research project, funded by the German Federal Ministry of Education and Research, created what is probably the most modern real-time controlled production line for high-quality seating furniture in Europe. The highlight: internal transport is supported by small robotic vehicles. They move completely autonomously using sophisticated sensor technology, communicate via their own Wi-Fi network, and are capable of learning. They receive their work orders automatically via the respective production plan. This technology, which has been in use since 2018, is constantly being further developed with the AI tools available today. For example, the vehicles will soon be able to listen and speak and expand their area of application to the entire shop floor, depending on where they are needed.

Second step:

AI in other areas of the company – example: sales

In extensive training courses, the sales teams at TOPSTAR and WAGNER familiarized themselves with the possibilities of AI in customer management and tackled this challenge with great commitment. Recurring tasks (such as route planning) and complex research work (e.g., identifying specific potential customers per country or region) were identified as areas of application. The tools used here are GPTs (Generative Pre-Trained Transformers), i.e., “small” AI agents that can be created by each employee themselves, for example, using the full version of Chat GPT. For more complex tasks, it makes sense to develop more broadly based AI agents in collaboration with external specialists. These then use multiple AI systems, are fed by larger amounts of data, and deliver faster and, above all, more accurate results. Initial experience has shown that iterative prompting, i.e., an increasingly refined specification for the AI, is a key success factor. Each AI has its own special features and generates better and better solutions with each “loop.”

Two specific use cases from sales

1. Automated research and new customer acquisition
Objective: The AI searches for new, potential customers from a specific sector in a predefined region based on relevant criteria. It compares the customer portfolios with our company’s offerings and determines our USP positions. In the best-case scenario, the AI independently approaches the customer with suitable solutions in words and images and independently prepares appointments and thus potential deals for the sales staff. Possible result: “A new customer every day” with little effort for the company and the best possible input for the customer.

2. Automated customer categorization and route planning
Goal: AI complements our CRM by clustering existing customers (ABC) and identifying all relevant characteristics about them. In addition to this data and a stored visit frequency, the system accesses real-time traffic data in the travel area and thus creates the complete route planning. Possible result: Similar to the above, on the one hand, sales staff are relieved of a lot of work, and on the other hand, every customer receives top support, nothing is forgotten, and even important details (“Mr. Meier has his birthday today,” etc.) optimize the customer experience.

Admittedly, there is still some way to go before we reach the examples described, but it is not that far and we are already on our way. What is exciting for us is that customers are also addressing similar issues. We recently discussed with a very large customer how long the AIs on both sides would exchange information before humans would ultimately come back into play. The latest studies attest that AI not only has more factual knowledge, but also greater negotiating skills. However, we believe in the “human being” on both sides and are looking forward to the near future with great excitement.

Author: Prof. Dr. Rainer Maria Wagner, Managing Director of Topstar GmbH