23 days → 9 days cycle; 12% retention lift
"Claims were sitting in queues for 3–4 weeks because our adjusters were drowning in first notice of loss calls and nobody was tracking what was missing. ThunderStaff built an AI triage system that ingests FNOL from phone, email, and portal, auto-classifies by severity, and routes to the right adjuster with policy history and photos. Cycle time dropped from 23 days to 9 days. Customer satisfaction on claims handling went from 2.8 to 4.6 out of 5. Our retention rate climbed 12 points because people actually felt taken care of when they needed us most."
The Problem
Claims sat in queues for 3–4 weeks because adjusters were drowning in first-notice-of-loss calls and nobody tracked what was missing.
The Solution
ThunderStaff built an AI triage system that ingests FNOL from phone, email, and portal, auto-classifies by severity, and routes to the right adjuster with policy history and photos.
Key Results
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Insurance Agency
P&C & Commercial Lines • Des Moines, Iowa • 9 Agents
The Problem
Claims sat in queues for 3–4 weeks because adjusters were drowning in first-notice-of-loss calls and nobody tracked what was missing.
The Solution
ThunderStaff built an AI triage system that ingests FNOL from phone, email, and portal, auto-classifies by severity, and routes to the right adjuster with policy history and photos.
Key Results
“Claims were sitting in queues for 3–4 weeks because our adjusters were drowning in first notice of loss calls and nobody was tracking what was missing. ThunderStaff built an AI triage system that ingests FNOL from phone, email, and portal, auto-classifies by severity, and routes to the right adjuster with policy history and photos. Cycle time dropped from 23 days to 9 days. Customer satisfaction on claims handling went from 2.8 to 4.6 out of 5. Our retention rate climbed 12 points because people actually felt taken care of when they needed us most.”
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