Enabling Computer Vision for Insurance Maintenance with AI Solutions

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.

The client required an AI-powered platform capable of:

Conducting automated home maintenance checks via image analysis.

Detecting and assessing residential utilities from images.

Ensuring seamless deployment with zero downtime and scalable infrastructure.

Solution

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.

1. Intelligent Image Analysis & Object Detection

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.

2. Automated Inspection & Real-Time Processing

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.

3. Seamless Deployment & Scalability

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.

Story Highlights

• Implementing Computer Vision enabling Intelligent Image Analysis & Object Detection
• Horizontal & Vertical Scaling for Efficient Resource Utilization
• Test Time Augmentation Implementation