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Case study · 2023

Claims Intake & Triage Platform

A mid-market insurer still handled first notice of loss—the first time a customer reports a claim—through PDFs, shared inboxes, and spreadsheets. Adjusters retyped the same details into the core policy system, and supervisors had no single view of new claims by urgency, type, or SLA risk. The goal was faster, clearer intake without replacing the policy system the business already trusted.

Web & Cloud Engineering Insurance 8 months
Claims Intake & Triage Platform

At a glance

  • Category: .NET / Blazor / Azure
  • Year: 2023
  • Client: Regional Property & Casualty Insurer

01 / Business Challenge

  • Policyholders abandoned digital forms when errors were confusing or the experience did not work well on phones.
  • Photos and PDFs arrived by email and were not reliably tied to a structured claim record.
  • Potential fraud and duplicate claims were often reviewed days after intake.
  • The legacy policy system was built for batch updates, not the steady stream of activity a modern intake channel creates.
  • Leadership required a full audit trail and controlled handoff to the existing policy administration platform—not a rip-and-replace.

02 / Our Approach

How we executed this engagement in practice. The phases below describe the delivery rhythm we use across ServiceNow, custom engineering, and mobile programs.

We separated the problem into two experiences: a public, mobile-friendly intake journey for policyholders and an internal Blazor workbench for adjusters and supervisors. Both use ASP.NET Core APIs. Azure Functions handled callbacks from document extraction services; results landed in SQL Server tied to claim numbers. A triage rules engine prioritized the queue and flagged exceptions for supervisors, while scheduled and on-demand sync jobs kept the legacy system as the official system of record.

Phase 01

Discovery & alignment

Workshops, process and systems review, success metrics, and scope clarity.

Phase 02

Design & planning

Architecture, experience and workflow design, risks, and a concrete delivery plan.

Phase 03

Build & validation

Implementation, integration, testing, demos, and refinements with your teams.

Phase 04

Go-live & enablement

Controlled rollout, training and documentation, handover, and post-launch tuning.

  • Implemented guided FNOL with progressive disclosure, localization, and accessibility review.
  • Integrated document ingestion pipeline with human-in-the-loop correction for low-confidence fields.
  • Built adjuster queues with filters, notes, attachments, and SLA timers.
  • Added integration adapters and retry policies for nightly and on-demand sync to the core PAS.
  • Deployed to Azure App Service with staging slots and database migration discipline.
  • Authored operational metrics: intake completion rate, time-to-first-touch, and rework rate.
Outcome Highlights

Business Impact at a Glance

Measured Impact
31%

Straight-through processing for low-complexity claims improved by 31%.

Measured Impact
4

Average triage queue wait dropped from 4.2 hours to 89 minutes.

Measured Impact
41%

Duplicate-submission incidents identified within the same business day rose from 41% to 94%.

Measured Impact
4

Adjuster rework (re-keying the same loss details) decreased by an estimated 4.1 hours per adjuster per week.

Verified Outcome

Customer satisfaction scores for the digital FNOL path increased measurably in post-claim surveys.

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