Interest in producing goods locally again has risen. This leads to new challenges for companies producing locally, especially since they are mostly small enterprises and do not always have resources to adapt Industry 4.0 technologies. Therefore, collaborating in networks can strengthen local production. We propose an online system with an underlying planning component that is supported by a large-scale language model to coordinate value chains within a network by utilizing the tacit production knowledge within the companies. Before any type of information processing can happen, however, the data – in this case, the tacit knowledge – needs to be acquired and formalized in such a way that is easy and quick, but also sufficient enough in detail and quality for the computer system. To this end, we conducted a study with 16 participants to simulate the collection of knowledge regarding the production of four pieces of furniture by having them describe simplified production steps. We analyze the results and show that the use of the collaborative system has a positive effect on the soundness of resulting production plans. In a second step, we utilize artificial intelligence methods to fill incomplete plans. Results and implications for future research are presented as well.