Innomotics has introduced its DigiMine AI Pyro solution to help South African cement and lime producers simultaneously achieve stable output, predictable quality, lower fuel consumption and controlled emissions. The solution uses real-time process data alongside historical production and quality information, employing patented Fingerprint Technology and Hybrid AI architecture to continuously identify optimal operating conditions unique to each plant. It forecasts key kiln parameters, including sintering zone temperature, kiln inlet temperature, kiln inlet oxygen and kiln inlet nitrogen oxide for the next 15 to 30 minutes, and generates optimised setpoints for open-loop or closed-loop operation. Innomotics reports that AI Pyro deployments have demonstrated specific heat consumption reductions of between 2% and 5%, and thermal substitution rate improvements of about 1% to 3% where alternative fuels are used. For lime operations, the solution includes AI-based soft sensors that continuously predict free lime content, complementing periodic laboratory measurements to prevent overburning and underburning. Fingerprint Technology combined with AI-based dependency modelling strengthens anomaly prediction by detecting process deviations earlier than conventional threshold-based monitoring. The company states that the combination of Fingerprint Technology, neural network prediction models and Hybrid Control transforms complex process data into operational intelligence, supporting stable kiln operation, improved energy efficiency, consistent product quality and a pathway towards autonomous process optimisation.