Socio-technical approaches for the integration of conversation-driven knowledge management in SMEs (KoWima)

Motivation 

Today, organisational knowledge emerges across many different communication channels and formats, such as emails, messengers, documents, or meetings, and therefore often remains fragmented and difficult to access. At the same time, this knowledge is rarely systematically archived or integrated into central enterprise systems such as ERP or CRM, which hampers sustainable knowledge transfer. In addition, traditional knowledge management systems often require considerable maintenance effort, which frequently leads to limited use in everyday work. KoWima addresses these challenges by aiming to automatically capture conversation-based and implicit knowledge, structure it, and make it contextually accessible

Objectives & Methodology 

The research and development project KoWima develops an AI-supported software solution that makes organisational knowledge from everyday communication—such as chats, emails, meetings, or documents—usable in a targeted way. The aim is to consolidate fragmented information and better support employees in their daily work.

Expected Impact & Transfer 

The KoWima system strengthens the use and transfer of knowledge within organisations, reduces knowledge loss, and accelerates work processes. By intelligently linking communication data with enterprise data, problems can be solved more quickly, decisions can be made on a more informed basis, and innovation potential can be better leveraged.