The client is a renowned Aerial Intelligence brand

The Client Requirement

Earlier, this company was looking for ways to reduce their operational cost, time and produce comprehensive reports for their clients. Inspecting roof claims in traditional methods has become a tiring job for them, and also, it is a dangerous and time-consuming process. They were after a unique end-to-end solution for settling the claims accurately. 

So, the client was looking for a completely autonomous system that would aid them in improving safety and security, cut-off loss adjustment expenses, and help them provide accurate risk assessment reports.

How Data Labeler helped them reach the next level? 

Data Labeler helped in annotating the roof damage from hail. We made use of our advanced Bounding Boxes technology for object detection to identify if any spots are visible on the roof, which looks like damage. We trained the model to identify how hail damage looks like. This helped us to find out if it is really a damage made by a hail storm.

In this way, bounding box annotation helped the client customize their requirements and identify almost all the possible damages on the roof. Data Labeler’s Train Machine Learning model allowed them to detect the degree of damage and settle the insurance claims seamlessly.

The Result

• The team could meet the client’s quality benchmark by achieving 100% accuracy throughout the project
• This allowed them to detect the degree of damage and settle the insurance claims seamlessly
• We helped in improving safety and security and cut-off loss adjustment expenses

Data Labeler offers accurate, convenient, customized, and quality labeled datasets for Machine Learning and AI initiatives.

Need help with data annotation, tagging or any labeling services, contact Data Labeler today for efficient and affordable data labeling services – Sales@DataLabeler.com