Now live: a hybrid process digital twin for amine gas sweetening — it names the fault and the root cause, not just the alarm. Explore the platform →

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Getting Started

What We Need From Your Plant

Four things, and none of them is a new sensor.

Calibrating the model to a new unit is engineering work — we will not pretend otherwise. It is also short, and it runs entirely on records your plant already has on file.

What we ask for.

  1. 1

    Equipment datasheets

    Design duty, surface areas, passes, clean U, solvent specification. This is what anchors the physics to your unit instead of to a generic flowsheet, and it is the single most valuable thing you can hand over.

  2. 2

    A tag list and a P&ID

    The tag register with units and descriptions, and the drawing. Every box that carries a live value is marked in the drawing itself, so the picture and the calculation cannot drift out of step.

  3. 3

    A history export

    Routine operating history at one-minute resolution, plus the slow laboratory series for solvent strength. The reference train runs on 85 channels over thirteen days — no special test period, just normal operation.

  4. 4

    One calibration pass

    Block parameters are fitted offline against that history and baked to a file. After that, queries run on unseen data without refitting, which is what keeps a single-point diagnosis fast.

What we do not need

  • No step tests. No new instrumentation. No connection to your control system. No migration of your historian into anyone's cloud. And where a channel simply does not exist, we tell you what the model cannot see rather than estimate it — twelve such blind spots are published for the reference train, each with what to watch instead.

The method is easiest to judge from the output.

The platform runs on a real amine train with thirteen days of one-minute history behind it. Open a diagnosis and read the evidence for yourself.

Open the platform