In many companies, critical know-how exists not only in documents, but in employees’ expertise: in routines and manual processes, in interpreting machine behavior, in identifying deviations – all built on years of practical experience. When employees leave the company, this valuable tacit knowledge often leaves with them. Together with the growing shortage of skilled workers, this creates a significant challenge for industrial organizations.
This is where our AI-supported wiki chatbot comes in. Company knowledge is systematically captured, structured within a semantic wiki, and made accessible via an internal chatbot using natural language. When generating responses, the chatbot draws on validated internal knowledge as well as additional relevant sources as needed.
The challenge is that experiential knowledge cannot simply be queried – it must be systematically elicited and transferred. To achieve this, we apply methods from engineering psychology, combining engineering, psychology, and instructional design. By using targeted observation, structured interviews, and context-based questioning techniques, knowledge is reconstructed directly within operational workflows.
The result is a digital knowledge system that makes expertise accessible across the organization. The chatbot delivers this knowledge directly within day-to-day processes – via simple, user-friendly queries in the language of the workforce.
Keep valuable expertise within your company: Contact us!
Fraunhofer Institute for Process Engineering and Packaging IVV