BFSI

Enabling Computer Vision for Insurance Maintenance with AI Solutions

Kagen AI developed an AI-powered inspection system, integrating computer vision and automation technologies to enhance home insurance maintenance checks. The solution streamlined risk assessments, improved precision, and optimized operational workflows for scalable and real-time processing.

90%
Inspection Accuracy Improved
30%
Operational Efficiency Enhanced
89%
Improved Precision
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Business Requirements
Our client, a leading US-based risk assessment business serving Fortune 500 companies, specializes in insurance and financial risk management. They aimed to modernize home insurance maintenance checks by automating visual inspections, reducing manual workload, and enabling real-time risk assessment.
Conducting automated home maintenance checks via image analysis.
Conducting automated home maintenance checks via image analysis.
Detecting and assessing residential utilities from images.
Detecting and assessing residential utilities from images.
Ensuring seamless deployment with zero downtime and scalable infrastructure.
Ensuring seamless deployment with zero downtime and scalable infrastructure.
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Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s.
Our Solutions
Kagen AI collaborated with the client to build a robust AI-powered inspection system integrating computer vision and automation technologies to streamline home insurance inspections.
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Intelligent Image Analysis & Object Detection
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  • Implemented YOLOv5 models to detect and assess home utilities with high accuracy.
  • Augmented datasets with diverse background images to minimize false positives and improve model precision.
  • Enhanced underrepresented sections using advanced data annotation techniques, refining model performance.
Automated Inspection & Real-Time Processing
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  • Leveraged AI-powered object detection to analyze and classify key residential utilities.
  • Applied Test Time Augmentation (TTA) to enhance detection accuracy across varied environmental conditions.
  • Optimized the image segmentation pipeline to process 50 images per second with just 1-second latency.
Seamless Deployment & Scalability
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  • Automated deployment using Azure Kubernetes Service (AKS) and Docker containers.
  • Designed a scalable architecture supporting both horizontal and vertical scaling for optimal resource utilization.
  • Ensured zero-downtime deployment, allowing continuous updates without disrupting operations.
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Story Highlights
Implementing Computer Vision enabling Intelligent Image Analysis & Object Detection
Horizontal & Vertical Scaling for Efficient Resource Utilization
Test Time Augmentation Implementation
Breakdown
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