Model the operation, connect it live, let agents act. Here is how that plays out in production.
The problem: a carbon-in-leach circuit where operators saw problems hours after the chemistry had already drifted.
What we built: a physics-true twin of the circuit fed by live plant data, with simulation-backed optimisation of the leach train — so setpoint changes are proven in the twin before the plant feels them.
The problem: a rail network where the first sign of an asset failure was a stopped train.
What we built: condition models across the fleet and corridor that intercept degradation early and turn it into scheduled work — across long sections with poor connectivity, where our edge-to-cloud sync earns its keep.
The problem: a treatment operation dependent on a thin roster of experienced operators.
What we built: twin-driven monitoring and control support that captures how the best operators run the plant — and keeps the process inside that envelope around the clock.
The problem: an offshore facility where every round trip to shore-based engineering costs time the process doesn't have.
What we built: agentic control at the edge: agents that simulate corrective actions in the twin, apply them within engineered guardrails and log every decision for review.
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