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    Draslovka–Avathon mining partnership: autonomy stack implications for plant engineers

    February 10, 2026|

    Reviewed by Tom Sullivan

    Draslovka–Avathon mining partnership: autonomy stack implications for plant engineers

    First reported on International Mining – News

    30 Second Briefing

    Draslovka and Avathon have formed a strategic commercial partnership to deploy AI‑enabled, autonomous and data‑driven operational systems across global mine sites. The combined offering links Draslovka’s real‑time mineral processing and chemical optimisation technologies with Avathon’s Autonomy for Operations platform to automate decision‑making in areas such as leach chemistry control, reagent dosing and plant throughput management. For operators, the move signals faster rollout of integrated autonomy stacks that sit on top of existing control systems rather than requiring full greenfield digital rebuilds.

    Technical Brief

    • For other mining operations, the model suggests incremental autonomy upgrades without wholesale control‑system replacement.

    Our Take

    AI and artificial intelligence keywords appear in 1,498 mining pieces in our database, signalling that Draslovka and Avathon are entering a space where digital tools are already being tested across planning, processing and maintenance rather than a niche side-line.

    Within the 1,862 tag-matched ‘Projects’ and ‘Product’ items, most AI-related coverage focuses on OEMs and large miners, so a chemicals-focused player like Draslovka moving into AI-powered solutions suggests downstream process optimisation (reagents, leaching, recovery) is becoming a competitive battleground.

    The absence of specific commodities or regions in this item contrasts with many other AI-tagged mining stories that are tied to copper, gold or iron ore projects, implying Draslovka and Avathon may be aiming for platform-style tools that can be applied across multiple ore types and jurisdictions rather than a single-commodity niche.

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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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