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    Eclipse SourceOne EKPS upgrade and rebrand: data integration notes for mine engineers

    February 10, 2026|

    Reviewed by Joe Ashwell

    Eclipse SourceOne EKPS upgrade and rebrand: data integration notes for mine engineers

    First reported on International Mining – News

    30 Second Briefing

    Eclipse Mining Technologies is rebranding and releasing a major upgrade of its SourceOne® Enterprise Knowledge Performance System (EKPS) to push AI-enabled decision support beyond mining into other large-scale industries. The new SourceOne release is positioned to integrate operational, planning and maintenance data into a single knowledge layer, aiming to make AI models more auditable and practical for site engineers and managers. For mine operators, this signals tighter linkage between short-interval control, fleet and plant data, and future cross-industry benchmarking on a common EKPS platform.

    Technical Brief

    • Vendor messaging stresses “safe” AI adoption, implying governance, traceability and control features around model deployment.
    • The new release is framed as “significant”, indicating substantial changes to core platform capabilities rather than minor modules.

    Our Take

    Eclipse Mining Technologies sits within a relatively small group of 28 Software stories in our database, suggesting mining-specific platforms like SourceOne are still a niche compared with hardware and project finance coverage.

    With this piece tagged to Projects and Product rather than AI, Eclipse Mining Technologies contrasts with many of the 1,498 keyword-matched ‘AI/artificial intelligence’ items, signalling that some operators are still prioritising integrated planning and data infrastructure before layering on advanced analytics.

    International Mining’s role here reinforces how software vendors such as Eclipse Mining Technologies increasingly use specialist trade media to reach technical decision-makers, which in our coverage often precedes pilots or roll-outs at mid-tier and major operators.

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    Prepared by collating external sources, AI-assisted tools, and Geomechanics.io’s proprietary mining database, then reviewed for technical accuracy & edited by our geotechnical team.

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