Our client had a difficult-to-use unadaptable system and desperately needed that needed legacy modernization. Application customization was required to onboard every new customer, so the time to market was much too slow.
We pulled out all the stops to modernize our client’s legacy software. We innovated their workflow engine. We introduced microservices, automation, and an agile methodology to speed up and simplify almost every part of the business, from customer onboarding and product development to data management and reporting.
In business flows to improve efficiency
Now fully customizable, up from 64%
Allow for unprecedented scalability and modularization
We implemented a workflow engine with configurable tasks and activities for improved customization. We made the code logic more consistent and introduced microservices architecture to create a more flexible app. We also brought in legacy system migration to the cloud so the new application could expand during peak times.
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.
For both the client and us, legacy modernization is about more than the shiniest technologies. It is about making customers’ lives easier. It is about design workflows and processes that free up employees’ time and makes them more productive. It is about creating an entire system that demonstrates the business impact.
A workflow and rule engine and plug-and-play modules allowed the engineering team more control and agility
Introduced a new stream of revenue generation with multi-tenant implementation
Asset processing and repair decision making was done using AI-powered predictions
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