Control that sees
the whole plant.
Most plants run hundreds of PID loops that each hold one variable but stay blind to interactions, constraints and economics. We add the layer that closes that gap — and prove it on one unit first.
Instrumented plants, conservative control.
The best operating point usually sits on a constraint, and classical control backs away from it. Three limits show up again and again.
Loop interaction
Tune one PID and you disturb the next. Operators de-tune for safety and run far from the optimum.
Constraint handling
Classical loops can’t hold a variable on a limit — exactly where the most profitable point lives.
No economic layer
Setpoints are chosen by habit, not by continuously solving for cost, yield and energy.
A control layer that predicts, optimises and reveals.
Predict & supervise
MPC and adaptive control anticipate interactions instead of reacting to them.
Optimise economics
Continuously retarget controllers against cost, yield, energy and emissions.
See the unseen
Digital twins estimate health and margins that are rarely instrumented directly.
Stay in control
Every move is bounded, logged and reversible — operators keep the final say.
Where model-based control earns its place.
The platform is industry-agnostic; these are the processes where advanced control delivers the most, and the markets we focus on.
Polymers
Reactor control and endpoint prediction for batch and continuous polymerisation.
Metals & minerals
Energy-intensive electrolysis and furnace processes with tight constraints.
Oil & gas
Gas processing and separation — product purity up, energy and flaring down.
Water & utilities
Pumping, aeration and energy optimisation across distributed assets.
Aquaculture
Emerging control problems in recirculating systems and feeding.
Carbon capture
New, tightly-coupled processes where model-based control earns its place.
Let’s run a proof of value.
One well-instrumented unit, a read-only pilot, and a quantified benefit estimate — with a reusable playbook for what comes next.
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