AI-driven management of dynamic manufacturing environments

Aggregate and inaccurate demand forecasting

AI-based demand forecasting that leverages all relevant historical data

Underperformance of On-Time-In-Full (OTIF) caused by inadequate task-resource timing and allocation

Holistic optimization of all manufacturing and distribution schedules

Frequent change orders causing schedule disruptions

AI-powered predictions of customer order modifications

Costly transitions and inventory levels caused by suboptimal schedules

Elastic solution to fully optimize schedules across millions of variables and constraints

Hard-to-maintain and rigid Linear Programming solutions requiring heavy manual interventions

No-code multiproduct, multipurpose ”what-if” planning and scheduling analyses for different time horizons

Multiple tools, multiple parties, inefficient collaboration

A unified and integrated application to streamline collaboration