2026-02-03

New Customer – Worlds Largest Mining Co.

Starting with the Canadian business this well known mining company has selected Refresh AI to govern, de-duplicate and classify all equipment and spare parts in SAP HANA.

At Fresh we are not new to the mining industry. In the last decade, we have seen our mining and commodity customers reorganize themselves quite significantly to focus on strategic products and markets. With this strategy, there has been a large amount of consolidation and acquisition of assets to suit the particular product and market mix of any given player. This inevitably means that post-acquisition of new operations, there can suddenly exist a large amount of data that may not be “a cut and paste” in to your current data set or ERP system.

This normally presents a great one-time opportunity to introduce master data governance, MDG as well as bulk cleansing and spare parts rationalization using our AI enabled software toolset. At this particular new mining customer, all of the existing 100 000+ assets and materials in Microsoft Dynamics AX had to be migrated to SAP S4 HANA quickly, but this challenge brought with it a significant opportunity for de-duplicating, renaming and cutting edge AI automated specification of materials to unlock new benefits for both Supply Chain / Purchasing and Operations / Maintenance.

Refresh software was selected after multiple demos against other software, outsourcing and AI approaches. The Refresh software was seen as the most automated and AI-enabled version of master data governance with its proprietary datasets, proven AI workflows and deep domain experience in the product information management (PIM) / Material Master Data Management (MDM) space. Both Refresh Desktop and Refresh Server were licensed in full by the customer, secure in the knowledge that these had already been proven over the previous 3 years in the Australian mines of the same company where today it helps deliver a single-version-of-truth item master, driving a lean optimized supply chain, and a high-uptime, low-cost maintenance process.

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