Case study · An ASX-100 financial services firm (claims operations)
A generative AI Pilot for a claims operations team. Operator-in-the-loop triage co-pilot deployed to production at the end of the 3-week sprint.
Quantified outcomes
Outcome metrics for this engagement are pending partner sign-off and will publish here once verified.
The problem
The claims operations team was triaging incoming claims manually, with a wait queue building during peak periods and an inconsistent specialist-assignment process that produced rework downstream. The team had previously evaluated a workflow-automation vendor solution but rejected it on the basis that it didn't handle the unstructured-document complexity of incoming claims (PDFs, photos, free-text narratives).
The approach
A 3-week Generative AI Pilot, scoped to a single claims category. Week 1: integration with the existing claims-intake system and the evaluation harness against a labelled dataset of 200 past claims. Week 2: operator UI built into the existing claims console (not a separate tool), with explicit confidence scoring on every triage recommendation. Week 3: production deployment with shadow-mode running for the first week, then full handover to the operations team. The operator who would use the system sat in the design sessions from week 1; their input shaped the confidence-score threshold and the manual-override flow that turned out to be the most-used feature in production.
The outcome
The system reached production at the end of week 3 with the operator team running it unaided in week 4. The measured outcomes against the original Gate 2 success criteria all tracked: triage time fell substantially, operator satisfaction was high, and rework downstream — a softer metric we agreed to track at quarter-end — was on a clear downward trend. The client engaged us for an Operate retainer at the 60-day mark to extend the system to a second claims category.
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