A digital-first insurance carrier was drowning in manual claims triage. EIC redesigned the operating model around AI decisioning with human review only where it mattered.
The carrier had grown policies faster than its operations could absorb. Every claim flowed through the same manual queue regardless of complexity, and experienced adjusters spent most of their day on low-risk, high-volume cases that needed almost no judgment.
We did not bolt a model onto the old queue. We rebuilt the operating model so that automation handled the routine path end to end, and people focused on exceptions, edge cases, and fraud.
We instrumented the existing process to find where time actually went and which claim attributes drove complexity, fraud risk, and rework.
Claims were routed into clear lanes so straightforward cases could be auto-adjudicated while complex and high-risk cases escalated to senior adjusters.
An AI decisioning service scored each claim, drafted a recommended resolution, and surfaced the evidence behind it for fast human verification.
Adjusters reviewed and approved automated recommendations through a purpose-built console, with every override captured as training signal.
We stood up monitoring for accuracy, drift, and fraud capture so the operation could be tuned safely rather than left to run blind.
We help operations leaders design AI-native workflows that hold up in production, not just in a demo.