Data-driven, AI model-based crushing circuit optimisation and control represent a significant leap forward in the mining industry, especially when integrated with advanced computer vision and real-time neural control. By employing sophisticated AI algorithms, these systems can continuously analyse vast streams of operational data, enabling real-time adjustments to the crushing process for optimal performance. The incorporation of computer vision technology is pivotal, as it provides rich data-source previously untapped of the characteristics of the material being processed. This synergy allows for a more accurate and dynamic control compared to traditional, hard-engineered control systems, which often rely on static settings and are less adaptable to varying conditions. The real-time aspect ensures immediate response to any changes in the input material or operational conditions, leading to increased efficiency, reduced energy consumption, and minimised wear and tear on the equipment. Overall, the transition to these advanced, data-driven, autonomous solutions heralds a new era in the mining industry, promising enhanced efficiency, sustainability, and profitability.