Capabilities

From connectivity to autonomous agents.

Six capabilities span classical control, digital twins, optimisation and supervised AI — built on control theory, shown the way an engineer would draw it.

Connectivity

OPC-UA, OPC-DA, REST and cloud connectors stream live and historical data — read-only until you choose otherwise.

Modeling

Linear, nonlinear, first-principles and data-driven models — the right tool for each unit.

Control

MPC, adaptive PID, extremum seeking and fuzzy logic, supervising the existing regulatory layer.

Optimization

Steady-state and dynamic optimisation retarget controllers against cost, yield, energy and emissions.

Intelligence

Hybrid models fuse first-principles physics with machine learning, improving as data arrives.

Agents

Autonomous agents perceive, reason with tools and act — with the operator approving every move.

Control, digital twin, AI & agents

The theory, visually.

From classical feedback to learning models and autonomous agents — the ideas the platform is built on.

Closed-loop feedback — the controller supervises the regulatory PID layer, never replacing it.

Model-predictive control — optimise over a horizon, apply the first move, then re-plan.

Digital twin — a synchronised virtual replica estimates asset health and margins live.

Real-time optimisation — the economic optimum sits on a constraint; classical control backs off.

Hybrid AI — first-principles physics fused with machine learning.

Autonomous agents — perceive, reason with tools, and act, with the operator in the loop.

Let’s run a proof of value.

One well-instrumented unit. A read-only pilot. A quantified benefit estimate. A reusable playbook for the next engagement.

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