The newly established AI Accelerator Cooperative Research Centre (AI CRC) has appointed MaxMine executive chair Tom Cawley as its mining sector lead, as the Adelaide-based mining technology firm reports a new machine learning (ML) system is now running across customer sites.
MaxMine said it has deployed a “production-grade” ML system for load and dump classification across Australian and multinational mine sites, naming customers including Glencore, NRW Holdings and Macmahon. The company said the system has been fully operational for six months.
According to MaxMine, the model was developed using more than 14 million hours of labelled operational data and is designed to automate load and dump classification, reduce site team workloads and improve production data quality. The company also said the system is deployed within a private, secure environment.
In the announcement, MaxMine outlined expected operational outcomes, including reduced workload for site teams by minimising missed or incorrect loads; higher accuracy production tracking in complex and edge-case scenarios; and “high internal development efficiency” through structured data and modern ML pipelines.
Shaun Mitchell, CEO at MaxMine, said, “Our successful implementation of this new machine learning system reinforces what has been observed across the industry: organisations succeeding in AI are those that have the highest-quality datasets. As AI adoption accelerates across mining and other critical industrial sectors, having high-fidelity, ground-truthed data becomes essential for delivering accurate results, improving operational visibility and enabling faster, more informed decision-making.”
The company linked Cawley’s AI CRC appointment to a broader push to increase domestic capability in applied AI. MaxMine said the AI CRC aims to build Australia’s “sovereign AI creation capacity”, enabling sectors such as mining to develop their own AI tools rather than relying on offshore capabilities.
Cawley said, “Despite increasing investments in AI, industries such as mining still struggle to move beyond pilot initiatives to achieve large-scale operational outcomes. Gartner estimates that 60 per cent of AI projects fail due to a lack of AI-ready data, with 42 per cent of organisations abandoning AI initiatives before they reach production. At MaxMine, we’ve demonstrated that Australia has the capability to develop advanced AI tools that work effectively at scale in mining. I hope my role at the AI Accelerator CRC will encourage further innovation across the sector and help to strengthen Australia’s competitive edge in the critical minerals market.”
Professor Anton Van Den Hengel, Chief Scientist at the Australian Institute of Machine Learning and Interim CEO at the AI Accelerator CRC, added, “The ability for a model to be deployed with such accuracy across such a range of asset and site types is rare. MaxMine’s ability to do this points to their uniquely rich, accurate and human error-free data sets, paired with long-term, multi-site, multi- machine training data sets.”
