Confirm with 2 taps before data reaches the ERP

The problem

The brake is not technical: it is who writes into the master data.

The main cultural brake on digitizing a plant is the fear that AI will enter data on its own and contaminate the ERP's allergen and batch master data. But operators don't want to type more either. Without a fast validation gate, any automation reads as a risk, not a help.

• The main cultural brake on digitizing an empanada plant is the fear that AI will enter data on its own and contaminate the ERP's allergen, batch and expiry master data.
• But operators do not want to type more either: every minute in front of a terminal is a minute not spent on the line.
• Without a fast validation gate, any automation reads as a risk rather than a help — and the project never clears the committee.
• The result is the worst of both worlds: unvalidated data entering the ERP, or data simply not captured because nobody trusts it. In a plant where the master data defines which allergens get printed on the tray, that distrust is not irrational: it is the only defense the quality team has today.

How it fits the IRIS system

Connect with early human verification — two taps at the line.

Connect early-human-verification mode: every capture lands on an industrial tablet as a two-second visual summary. The supervisor confirms (✓) or corrects (✏️) before the data crosses into the central system.

This is the piece that guarantees the master data does not get contaminated and that every data point has a named owner. Without it, the other eleven do not get signed off in committee: nobody approves an AI writing on its own into the system an allergen label depends on. So it is not sold as one more case, but as the entry condition for the whole matrix.

See the full IRIS architecture →

Before and after

Today's data versus validated data

Aspect	Today	With iLEAN
Who writes into the master data	Whoever types, hours later	Whoever validates, in seconds
Allergen and expiry master	Exposed to typing errors	Only confirmed data gets in
Effort for the supervisor	Walk back to the terminal	Two taps on the tablet
Data nobody dares capture	Stays outside	Captured and validated
Correcting an extraction	Does not exist	Stored with its author
Training required	ERP screens	None: confirm or correct

Unvalidated data contaminating the ERP, or data left uncaptured out of distrust → data captured and validated within seconds, clean master data.

Impact estimate

Impact estimate — to be validated with your numbers.

The block below is an estimate to be validated against your plant's actual data. We put it forward so the committee has an order of magnitude; we refine it during the assessment.

• No standalone payback: this is the enabling piece of the whole matrix. Without it, none of the other eleven cases gets signed off in this plant.
• The dominant value is not productivity, it is risk: the batch, allergen and expiry master data stops being exposed to automatic writing.
• Every data point carries the name of whoever saw it, which is what gets asked for when a retail chain demands the traceability of a tray.
• And the quality team's cultural resistance drops at once, because the AI proposes and the person disposes: that is the sentence that unblocks the committee.

Enabling piece for the whole iLEAN matrix — without it, the other pieces don't get signed off with confidence. *Strategic value, not directly monetizable*.

And the fair question from the production manager

“If a person signs in the end, what is the AI saving?” — the work is not in deciding, it is in gathering. Today somebody would have to walk to the terminal, find the batch and type the data in. With the verification gate it all arrives gathered into a two-second summary and is simply confirmed or corrected. The prior extraction is besides an anchored task, where the best models drop below 1.5% error [1]: the supervisor reviews, they do not rewrite.

^[1] OpenAI paper "Why Language Models Hallucinate", 2025 — on the reliability of AI in anchored tasks.