Worked example
An agent that checks referrals for completeness and routes them to the right service — so your admin team works a sorted queue, not a raw inbox.
Illustrative — a representative problem and how we'd approach it, not a past client engagement.
Scenario. Incoming referrals pile up in an undifferentiated admin inbox — checking each for completeness, flagging the time-sensitive ones, and routing to the right clinician or service is manual.
The solution. A Build on your intake admin; the completeness and urgency rules are yours, tuned on your real referral flow. It sorts and routes administratively — it does not read or summarise clinical content or make any clinical judgement; a person owns every clinical decision.
- Incoming referrals (admin queue)
- Intake agent — completeness check, urgency flag, routing (administrative only)
- Completeness + urgency rules
- Admin works the sorted queue; clinician owns every clinical decision
- Sorted, flagged, routed referral queue
The outcome we’d target. The outcome we'd target: admin working a sorted, urgency-flagged referral queue — the completeness and urgency rules tuned on your real referral flow, the clinical/admin boundary explicit by design.
This worked example applies the AI Fluency framework — how we frame which door fits