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success story

Intelligent claims processing with AI-based hyperautomation platform

A visual inspection solution to automate fault detection, improve accuracy by 85% and optimize repair cost calculation.
Manual inspection of cracks and seepage, sketching the inspection results, and preparing cost analysis were time-consuming and expensive and were based on subjective analysis and often lacked consistency in determining cost. Could a digital solution ensure objective and accurate data collection and fair repair costs assessment?
Nagarro designed and developed an AI-based visual inspection mobile app and a web application to automate identifying cracks and seepage defects on a wall/roof while also computing the cost of fixing the defects. We developed a guided image capture process within the mobile application to help policyholders take the right images and ensure data quality. A state-of-the-art machine vision-based model would automatically detect the type and severity of the defect from the images captured using the mobile app. The app powered by augmented reality accurately measures the size of the fault and assesses defect repair costs using the built-in business rule engine.
With the camera-based visual inspection, the client saw more than 85% improvement in the accuracy of surface crack detection. The solution allowed them to give end-users the autonomy to share the photos of defects instead of using an employee to assess the damage. This helped gain customer trust and build confidence in the assessment result. Nagarro’s hyperautomation platform for defect detection and the elimination of manual intervention increased efficiency and reduced time for evaluation.