A regional food and beverage manufacturer is improving product quality and optimizing energy consumption with AI-recommended facility and machinery adjustments. Operators see the reasoning behind each recommendation and decide whether to act on it, keeping humans in control.
In manufacturing, small performance gains add up fast when they repeat across thousands of production hours.
Drying milk is one of our client’s most complex processes. Throughout each run, operators balance product quality, production performance across airflow and moisture, and energy consumption as conditions shift.
Those decisions rely heavily on operator experience, where they must interpret large volumes of process information to make each call.
Ashling built an agentic solution, designed to fit within the manufacturer's existing systems, and to give operators timely, data-driven recommendations that build on what they already know.
This is AI decision support, with the operator staying in full control.
With AI recommendations guiding each run, operators achieved:
Every gain came from operator decisions. Operators reviewed each recommendation and chose which ones to act on, and every choice fed back into the model.
AI in manufacturing should strengthen operator expertise. That’s why Ashling builds decision support that keeps people in control. The solution gives the manufacturer a practical model for introducing AI responsibly into their complex environment, one that combines technology, operational knowledge, and human judgment to create lasting value.