Ask the plant a question. Get an answer it can prove.
Ask sits beside every tool. It reads the screen you are on and the plant knowledge base behind it, then answers in plain language. If the answer is not in the data, it tells you that instead of guessing.
MVPEvery figure above is counted in the minimum viable product: the amine train modelled for gas sweetening and post-combustion carbon capture.
What it does
Every tool publishes a structured snapshot of exactly what it is displaying. Ask which KPI is out of band, or why a fault fired, and the answer comes from the numbers in front of you — not from a general impression of how amine plants behave.
Faults and what drives them, root causes, indicators, sensor tags, equipment, recorded fault episodes, engine notes, open items — and the blind spots, so it can tell you what the model cannot see.
The full knowledge base runs to roughly 65,000 tokens. Searching first and sending only the cards a question needs keeps a typical query near 2,000. That is the difference between a few dollars a month and a few hundred — at one train.
If the snapshot does not carry the answer, it says so and points at the tool that would show it. It never estimates a figure the data does not hold, and it never invents a tag, a fault or a timestamp.
How it works
The assistant panel is always there, next to the work.
Each tool reduces what is on screen to structured values — the same numbers you can see, without the chart geometry.
Records are flattened into short cards and scored against the question. Only what is needed is retrieved, under a fixed budget with a per-card cap so one long fault record cannot consume it.
Screen snapshot first, knowledge base second. General process-engineering knowledge is allowed, but it is flagged as such rather than blended in silently.
Where it applies
The platform is focused on acid gas removal — gas sweetening and post-combustion carbon capture — because that is where the model is calibrated and where the fault library is real. The method underneath is not amine-specific: a physics reference model, residuals against expected-healthy, fuzzy diagnosis over graded indicators, and costed consequences. Extending it to another unit means new datasheets and a new calibration, not a new platform.
The platform runs on a real amine train with thirteen days of one-minute history behind it. Nothing on these pages is a mock-up.
Open the platform