Dental Technology Provider Accelerates Development Feedback Loop by Pairing AI With JRebel

The JRebel customer featured in this case study is the market leader in practice management software for dental providers. With a large engineering department consisting of 90+ developers, they focus on delivering a modern, secure application to customers. However, backend complexity was interfering in modernization efforts, resulting in redeploys of 7-10 minutes or more.

The Problem: Significant Backend Complexity Leads to Long Redeploy Times 

Supporting dental practices with all aspects of practice management — from scheduling to billing and more — leads to a highly complex business application with 11 distinct production tiers. This monolithic application was built on Groovy on Grails running on the JVM, resulting in significant backend complexity and tightly coupled code. And while Groovy is Java-compatible, it has concise syntax and dynamic typing that makes it harder to refactor — leading redeploys of 7-10 minutes or more.   

“It was magic when it worked, and then slowly the complexity and the maintenance issues showed up,” explains the lead engineer at the dental technology provider. “No one had an answer.” 

This slow feedback loop frustrated the team and stalled their progress, especially when they introduced Cursor for AI-generated Java code. While more senior developers could write a prompt and commit to a code change in one or two tries, less experienced developers often needed several iterations to perfect a prompt-generated code change — frequently interrupting developers’ flow and eating hours of development time waiting on redeploys.  

The Solution: Accelerate the Feedback Loop With AI + JRebel 

One weekend, the team’s lead engineer was getting frustrated by those rapid-fire interruptions while trying to fix a bug. Then he remembered a tool he had heard about years earlier: JRebel. “That weekend when I was struggling, I had to do something, and I tried JRebel,” he explains. By eliminating redeploys, he could tinker with AI prompts in Cursor and test the code changes without waiting 10 minutes each time.  

He was impressed at how JRebel accelerated the development feedback loop, complementing the investment the team had already made in an AI-code generation tool. 

But the story didn’t end after that weekend project: he encouraged his direct team to try JRebel, and word of the time-saving power quickly spread among the team of 90+ Java developers. “After getting the rest of our teams on board, I became popular among our developers,” he says.  

Because JRebel integrated natively into all the IDEs the team was using — including IntelliJ, VS Code, and Cursor — they were able to quickly apply to existing workflows and give immediate time savings back to the team. 

This frees up developers to work on higher-value tasks, such as new business features and migrating from Java 11 to Java 17. 

“With JRebel, I only need to restart or rebuild my project two or three times a week. It all feels seamless — that's huge for me.”   

The Results: Deeper Collaboration and Faster Iteration  

The team achieved remarkable productivity gains after adopting JRebel. Redeploys that previously took 7-10 minutes or more are now instantaneous. This rapid feedback loop empowers developers to validate their code immediately without losing their flow state.  

Furthermore, JRebel saves the developers crucial time during code reviews, which has resulted in increased collaboration between developers. When changing branches, they just pull in a colleague's branch, eliminating the need to redeploy again or rebuild again. 

The dental technology provider’s developers quickly learned the power of rapid iteration to fuel innovation — and you can too. 

“I’d absolutely recommend JRebel to other Java developers. If they’re on the latest versions of Java it’s even better, and they’ll see their build times cut in half or more.”