Moving into the future with legacy modernization

When we started this partnership, our client was working with a system that was too slow, rigid, and complex. We worked closely with the engineering and operations team during the planning phase of the project, and we realized that one thing they needed was flexibility. Flexibility would bring the speed they needed, especially once workflows were streamlined. We brought it in when we implemented a workflow engine with configurable tasks and activities. The operations and engineering teams now have more business flow customization, giving them the flexibility they need. That flexibility also gives them unprecedented control over their tasks, further improving efficiency, and giving them more time for business-critical work.

Early in the project planning, we saw how automation could support the system modernization for the client. We implemented a business rule engine with a decision tree, inference, and rete algorithms. That way, many repair and processing decisions are now automated, taking that whole process off the client’s plate. We also increased the operations team’s efficiency by implementing Fair Market Value (FMV) predictions. These have been programmed using machine learning and are based on historical data using AI algorithms, logic notification, and repair decisions. This allows the client to determine prices and value without having to make complex calculations and negotiations, which speeds up customer onboarding and more.

When the client asked us to take on this modernization initiative, we knew we wanted to structurally change processes, apps, and the culture. It wasn’t going to be enough to layer some automation and microservices on top of a lumbering old system. We had to build an entirely new system, almost from scratch, and we took the opportunity to embed modern development culture into the system to support the modern tools and software. We embedded an agile approach into the development pipeline. This allowed us to demonstrate the progress of the project to the client and allows the engineering and operations team to follow an agile methodology in their current development processes. We also used Azure DevOps as the microservices architecture to automate the deployment, a tool that the client will be able to utilize and update however they need in the future.