Data-driven learning of control rules

Data-driven learning of control rules

DaCoR develops data-driven virtual representations of logistics processes that can be derived independently from company information. This creates flexible models that capture complex operating logics and significantly simplify planning processes.

Real-time ordering of medical products

Real-time ordering of medical products

AI4Demand relieves hospital staff by recording stock levels using computer-aided analysis and triggering replenishment independently. This makes care more efficient and increases the focus on patient care.

Optimization of logistical master data

Optimization of logistical master data

DSCS creates a reliable database by comprehensively evaluating the quality of logistics master data and making optimization potential visible. This minimizes sources of error, strengthens data-driven applications and significantly improves operational and strategic decisions.