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    IntelliSense.io–SEP–Mitsubishi mining deal: key optimisation takeaways for engineers

    September 4, 2026|

    Reviewed by Joe Ashwell

    IntelliSense.io–SEP–Mitsubishi mining deal: key optimisation takeaways for engineers

    First reported on International Mining – News

    30 Second Briefing

    IntelliSense.io has secured a major growth investment from Scottish Equity Partners (SEP), with strategic capital from Mitsubishi Corporation and Hitachi Construction Machinery, to scale its industrial decision intelligence platform for mining and minerals processing. The AI-native system is already deployed on unit operations such as grinding, flotation and thickening, using real-time sensor data and digital twins to optimise throughput, energy use and reagent consumption. Backing from OEMs like HCM signals tighter integration of IntelliSense.io’s optimisation tools with autonomous haulage fleets and smart plant control systems across new geographies.

    Technical Brief

    • Investment round brings together SEP growth capital with strategic equity from Mitsubishi Corporation and Hitachi Construction Machinery.
    • Capital injection is earmarked to accelerate core platform development rather than standalone point solutions.
    • Funding is also targeted at scaling commercial deployment teams into additional mining jurisdictions and language regions.

    Our Take

    Mitsubishi Corporation and Hitachi Construction Machinery feature more often in our coverage on equipment, trading and project equity than on software-led deals, so their backing here suggests OEMs and trading houses are starting to treat data and optimisation layers as strategic infrastructure rather than bolt-on services.

    With this financing falling under both ‘Projects’ and ‘Product’ tags in our 2,469 tag-matched pieces, it sits at the intersection where mine operators have historically moved from pilots to fleet- or network-wide deployments, implying that IntelliSense.io’s tools are likely being positioned for standardisation across multiple sites rather than single-mine trials.

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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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