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Worked example

An agent that clears the routine in a review queue and surfaces only the exceptions — so your expert's time goes to the calls that need judgement.

BuildAugmentationCross Industry

Illustrative — a representative problem and how we'd approach it, not a past client engagement.

Scenario. An expert's review queue mixes routine items with the few that need real judgement — and everything waits behind everything.

The solution. A Build, run as Augmentation — the expert owns the routine/exception threshold; we'd calibrate it on your real queue before anything runs on the routine tier.

Build — solution shape (illustrative)

The outcome we’d target. The outcome we'd target: the expert spending their time on the exceptions, not the routine — the routine/exception threshold owned by your expert and calibrated on your real queue before anything runs on the routine tier.

This worked example applies the AI Fluency framework — how we frame which door fits