Abstract <p>Growing climate instability is creating new challenges and risks for the resilience of small and medium-sized enterprises (SMEs). This article proposes a prototype architecture for a dynamic expert system comprising several key modules: a user interface, a knowledge base, a server application, and a dynamic data update module with real-time APIs. A distinctive feature of the system is the application of <i>Z</i>⁺-number calculus, implemented using the scikit-fuzzy library, which allows for the accounting of graded confidence in evaluations. This approach provides more robust and adaptive risk assessments that are sensitive to changes in the quality of input data. Interactive visualization of the results is built upon OpenStreetMap. The system’s methodology for self-adaptation of confidence measures based on historical data is described.</p>