In many companies, valuable knowledge is distributed across systems, departments or individual heads. Information is difficult to find, search times are long, and knowledge is lost when employees leave the company. This makes efficient processes difficult, delays responses to customer inquiries and leads to duplication of work. Establishing a central, company-specific knowledge management system is thus becoming a key task for sustainable efficiency and competitiveness.
Together with the customer, Liquam has developed an AI-based knowledge platform that collects knowledge centrally, intelligently structures it and makes it easily accessible to employees.
A practical example:
An industrial company wanted to secure the knowledge of experienced employees, significantly reduce search times in sales and service, and create a basis for answering customer inquiries through AI. The aim was to build a company-specific knowledge database that intelligently links internal data sources and makes them searchable.
In this project, Liquam has developed an AI-based knowledge platform that brings together internal data sources such as price lists, catalogs, product information, documentation or intranet content. The system was supplemented by structured expert interviews, whose content was automatically transcribed and integrated into the knowledge base.
AI enables semantic search and provides precise, contextual answers. A feedback mechanism allows employees to evaluate the quality of the suggestions and thus continuously improve the platform. A live dashboard provides transparency about usage, search behavior and optimization potential. The solution is scalable, e.g. for multilingual content or integration into self-service portals.
