Leaders and developers at University of Rochester Medicine share how Rhapsody Axon is helping their teams analyze specifications faster, troubleshoot issues more efficiently, and scale interoperability work without adding headcount.
Healthcare interoperability teams are under increasing pressure. More systems, more APIs, more FHIR initiatives, and more vendor relationships.
To help alleviate some of these pressures, University of Rochester Medicine began exploring Rhapsody Axon, an AI-powered assistant designed to support the day-to-day work of interoperability teams.
During a recent webinar discussion, Jennifer Redshaw, Assistant Director of the Application Integration Team at University of Rochester Medicine, shared how her team is navigating growing interoperability demands while supporting connectivity across more than 100 clinical, operational, and business systems.
As integration requirements continue to expand, she noted that teams are increasingly challenged to do more with limited time and resources. “We have a lot to do,” says Redshaw, whose team oversees architecture, business analysis, development, Epic Bridges, and enterprise connectivity efforts.
Rather than viewing AI as a future concept, the organization has begun applying it to one of healthcare IT’s most persistent challenges: integration work.
Accelerating Analysis Work
Healthcare has become increasingly sophisticated in evaluating technology. Organizations know One of the first areas where University of Rochester Medicine saw value was within its business analyst team. Vendor specifications can be lengthy, inconsistent, and frequently incomplete, requiring extensive back-and-forth conversations before development can begin.
Redshaw explained that her team began using AI to review specifications, identify required fields, and surface questions earlier in the process. In one instance, the team received a 254-page specification document.
“I’m not reading that,” joked Redshaw.
Instead, the team used AI to quickly extract the information they needed and move conversations forward more efficiently. The result: faster analysis and more targeted vendor discussions.
Helping Developers Build Faster
For Fred Fowler, Lead Integration Programmer at University of Rochester Medicine, the benefits extend beyond analysis.
Fowler describes how AI has helped developers become more granular in their questions and accelerate build activities, particularly as the organization brings new systems into Epic and supports a growing number of interfaces. Adding that AI has proven particularly useful for understanding complex filters and configurations.
Fowler said some of his earliest experiences with Axon demonstrated its ability to quickly surface relevant information, explain unfamiliar concepts, and help teams determine the next steps more confidently.
“It’s a learning tool,” Fowler noted later in the discussion, explaining that Axon often suggests ideas and approaches teams may not have otherwise considered.
Making Expertise More Accessible
Another benefit has been democratizing knowledge across the team. Integration environments are complex, and organizations often rely heavily on a small number of highly experienced engineers. By providing explanations, recommendations, and step-by-step guidance, AI can help newer team members ramp more quickly and reduce dependency on institutional knowledge.
For Redshaw, even non-developers can benefit. When she needed assistance with a platform function she was unfamiliar with, AI not only explained the limitation but also walked her through an alternative approach step by step.
Importantly, neither Redshaw nor Fowler view AI as a replacement for expertise. In fact, Fowler cautioned that organizations still need people who understand integrations and workflows.
“You still need to have the knowledge behind it to make the tools work for you,” he says.
A Practical Path Forward
University of Rochester Medicine’s experience highlights an important lesson for healthcare organizations exploring AI: You do not need to start with transformational use cases.
Sometimes the greatest value comes from solving everyday problems. “Just start somewhere. Just pick something,” advises Fowler.
For interoperability teams facing growing demands and limited resources, that “something” may be the opportunity to finally reduce manual effort and scale the work that matters most.
Watch the on-demand webinar to hear directly from University of Rochester Medicine as they discuss how their team is using Rhapsody Axon to simplify integration work, accelerate analysis, and reduce manual effort across a complex healthcare environment.
You’ll also see a live demonstration of Axon in action, including AI-assisted troubleshooting, documentation research, code support, and agentic integration workflows.
See how Rhapsody is helping organizations build the interoperability foundation required for AI at scale.
