An eyewear order is not a standard e-commerce order. It carries a prescription, a lens, an index, a coating, a frame — and a promise with a deadline.
Captured from any source — web, app, store, marketplace. The SLA clock starts immediately.
SLA armedAI gives a plain-English clinical read. Inconsistent cylinders, missing axes, suspect powers — caught here.
AI assistedIn-house bank or lab order — decided per prescription, per index, per coating. The fork in every order's road.
Stock checkThe longest leg of the critical path closes. Lab-dependency risk drops off the order's score.
Risk easesPass → fitting. Fail → the loop: re-order, re-surface, re-check. Every failure burns days, and the engine knows it.
Can loop backLens meets frame on the bench. Final craftsmanship stage before the order leaves the building.
BenchOut the door, tracked against the final hours of its SLA window.
In transitPromise kept. The order's history feeds the demand model for what to stock next.
SLA metA transparent 0–100 risk score from schedule pressure, lab dependency, QC history and lens complexity — auditable, not a black box.
For every high-risk order, the AI writes why it will breach and the one action the team should take right now.
A background watcher scans every five minutes and emails the team before the SLA dies — not after.
“High-risk lab orders breaching SLA” — typed in English, translated to validated filters. No SQL, no training needed.