The shift supervisor dictates while walking the floor

The problem

The supervisor notices the cold room drifting hours before anyone logs it.

Critical operational knowledge -that the sorter is rejecting more fruit than usual, that a cold room reads an odd temperature, that a new operator needs backup- lives only in the shift supervisor's head and never reaches the system, because he can't stop to type while walking the floor.

• The shift supervisor crosses receiving, the sizer, packing, the cold rooms and the oil line all day, with hands busy and no desk nearby.
• They notice what no sensor puts into words: the sorter rejecting more fruit than usual, a cold room reading an odd temperature, a pallet sitting too long at the dock, a new operator who needs backup.
• None of it reaches the system, because typing means stopping, and stopping is not an option in peak season.
• So the observation dies at shift change, and the cold-chain deviation is discovered when the fruit is already soft.

How it fits the IRIS system

Connect in voice mode — a wake word, and the dictation lands on the right lot.

Connect voice mode: with a custom wake-word ('iLEAN, note this'), the shift supervisor dictates while walking. An LLM structures the dictation as an incident linked to the active lot/line/shift, stores it in central memory and returns support by voice or push seconds later.

An avocado that spent too long out of the cold room does not show it today; it shows it at the market a week later. The supervisor is often the first to notice, and the voice note is what turns that intuition into an early warning instead of an anecdote. In a perishable business, that week of lead time is the whole value.

See the full IRIS architecture →

Before and after

The supervisor's round today versus the round that is captured

Aspect	Today	With iLEAN Connect
An odd cold-room reading	Mentioned at handover, maybe	Logged against the room and the lot
Sorter rejecting more than usual	Noticed, never written	An incident linked to line and shift
Effort to record it	Stop and find a terminal	“iLEAN, note this” while walking
Cross-check with live data	None	Against temperature and sorting data
What the next shift inherits	A few verbal minutes	A structured list of open incidents
Talk among operators	—	Never recorded

Knowledge that dies at shift end → enters the system in real time and is cross-checked against live temperature and sorting 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 an enabling piece, and we do not put a number on it by itself.
• Its value is strategic — it enables early detection of cold-chain and quality deviations before they become a loss.
• What that is worth depends on how many deviations your plant catches late today, which is why we size it with your continuous-improvement lead rather than print a generic range.
• It also feeds the flagship: the supervisor's notes are one more source the cross-checking rings compare against sensors and cameras.

Strategic value: enables early detection of cold-chain and quality deviations before they become a loss. *Estimate to be validated with the continuous-improvement lead.*

And the fair question from the production manager

“Will the team feel listened to all day?” — no: iLEAN only records after the wake word, and only the supervisor's voice, never the operators'. On reliability, turning a short dictation into lot, line and symptom is an anchored task, where the best models drop below 1.5% error [1], and the structured note comes back for the supervisor to confirm before it is stored.

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