AI and ML for Auto Repair and Insurance Workflows

Our partner has developed a system that streamlines workflows for auto repair shops and insurance companies.

Their system utilizes advanced technology such as artificial intelligence, machine learning, and image recognition. This technology enables the system to automatically estimate vehicle repair costs. The estimation is based on accident images and information. The client sought out AI and ML consulting for their limitations.

Despite their success, the client needed specific tasks related to security, compliance, scalability, and performance. The heavily regulated insurance sector required them to address security and compliance issues effectively. Accommodating the increasing data volumes and ensuring scalability became critical, particularly with regards to Big Data and Analytics. Finally, the client wanted to improve their system's ability to recognize images and handle more repair quotes in the future.

Our partner’s comprehensive solution encompassed several initiatives aimed at prioritizing security and compliance throughout the cloud migration process. They relied on AI and machine learning.

To effectively streamline the machine learning lifecycle, they implemented a framework within SageMaker, an Amazon Web Services (AWS) service.

This move helped control, monitor, and manage machine learning models and was important for our client's business operations.

With many new car models and versions coming into the market, this feature became necessary for them.

Furthermore, with the incorporation of Auto Scaling, SageMaker exhibited its adaptability by dynamically managing deployed endpoints in response to fluctuating traffic and usage patterns. AWS SageMaker's tools allowed for real-time tracking of model drift and timely detection of data quality issues.

They effectively managed model versions and deployments. This was crucial in handling the increasing daily quote volume. It also ensured long-term success.

By diversifying our approach and leveraging the capabilities of AWS SageMaker, we successfully addressed the client's needs while maintaining the highest standards of security and compliance throughout the cloud migration process.

The results demonstrate the remarkable growth achieved by our Accelerance partner. In the beginning, the company had 63,600 car models and did over 200,000 repairs each month. They made a huge $560 million from selling car parts.

However, their accomplishments did not stop there. Their platform performed exceptionally well, processing 250 pictures per minute and generating 5,000 quotes daily in just two years.

Also, the yearly prices increased by a remarkable 300%, confirming their control in the industry with a remarkable 90% market share.

Through an in-depth analysis of the client's data, we identified a promising product opportunity and proactively proposed a new solution.

They fully embraced the idea, developed the solution completely, and got a remarkable $20 million investment to prove its value.

This investment highlights the distinction between a tech provider and a trusted technology partner. A trusted technology partner is fully committed to the success of your business.

Remarkably, this entire process operates smoothly without the need for appraisers, repair facilities, or insurance adjusters. The client has grown a lot, with quotes increasing four times in a year, now averaging 800 quotes daily.