Two taps before it touches the ERP

The problem

The real brake on digitization is not technical, it is trust.

In a multi-customer EMS plant, the main cultural brake on digitization is the fear that AI will enter data on its own and contaminate the ERP or MES master.

• In a multi-customer EMS plant the ERP and MES masters are the contract: part numbers, BOM revisions, work order status and consumption. Everything the plant bills rests on them.
• So the honest fear is the one that gets voiced in the first meeting: that AI writes on its own and contaminates the master, and that nobody notices until a customer audit does.
• The result is the opposite of the intended one. Either data is not captured at all, or it is captured and then left in a parallel system nobody trusts enough to push.
• And the second failure mode is just as expensive: data typed hours later by somebody who never saw the board, the reel or the traveler it describes, and who is reconstructing it from a photo on their phone or from what a colleague told them.

How it fits the IRIS system

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

Connect early human verification mode. Every capture (photo, voice, parsed email) reaches an industrial tablet as a 2-second visual summary. The supervisor confirms (✓) or corrects (✏️) before the data crosses into the ERP/MES master.

This is the piece the other eleven rest on. Every capture arrives as a two-second visual summary and a person confirms or corrects it before it crosses. Without this gate, nobody in an EMS plant signs off on the rest of the matrix — and they are right not to. With it, the conversation stops being about trusting a model and starts being about how much typing disappears.

See the full IRIS architecture →

Before and after

Today's data entry versus verified entry

Aspect	Today	With iLEAN
Who writes to the ERP master	A person, typing hours later	A person, confirming in seconds
Who the author is	Whoever types it	Whoever looked at the board or the reel
Capture latency	Hours, or never	Second-level
What a correction leaves behind	Nothing	A trail plus feedback for extraction
Data nobody captured out of distrust	A permanent gap	Captured, because it is validated first
AI writing unsupervised	The fear that blocks the project	Not possible by architecture

Unvalidated data contaminating the ERP/MES, or data not captured due to distrust → data captured and validated with second-level latency, clean master.

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 — the brief calls it strategic value, and that is exactly right: it is the enabling piece that unlocks the whole matrix, not a case you justify on its own savings.
• What it protects is the ERP and MES master, which is what the plant bills, audits and defends in front of every customer.
• It converts the cultural objection into an architecture decision: data crosses only after a human confirmation, and that cannot be configured away by anyone, at any level.
• And every correction is stored with its author, so extraction improves precisely where it fails instead of everywhere at once.

Strategic value · the piece that unlocks the whole matrix. Estimate to be validated.

And the fair question from the production manager

“If a person confirms in the end, what is the AI actually saving?” — the work is not in deciding, it is in assembling. Today somebody walks to a terminal, finds the work order and types. Here it arrives assembled and they confirm or correct. Assembling that summary is an anchored task where the best models drop below 1.5% error [1], so most confirmations are a single tap.

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