A representative retail engagement begins with SKU-level demand, stockout and replenishment decisions. BELFORT combines point-of-sale history, seasonal patterns, promotions and relevant external signals in a governed forecasting workflow. Results are evaluated against the existing planning baseline using forecast error, availability, inventory turnover and planner intervention before any automated replenishment is expanded.
A representative banking engagement connects transaction, identity, device and behavioral signals to a real-time investigation workflow. BELFORT designs supervised and anomaly-detection components around explicit decision thresholds, reason codes and human escalation. Effectiveness is validated with prevented loss, false-positive rate, detection latency and investigator workload, with customer impact reviewed by segment.
A representative logistics engagement uses order, fleet, traffic, weather and service-window data to improve dispatch decisions. BELFORT separates optimization from operational safety rules and provides dispatchers with explainable recommendations and fallback routes. Performance is compared with the current process using fuel consumption, on-time delivery, utilization, route stability and exception recovery.