Rhapsody uses AI to reduce integration timelines from months to days

Due to regulatory requirements and industry standards, healthcare integration is inherently complex, requiring expertise across industry standards, data engineering, networking, and message processing. As healthcare organizations expand and data sources multiply, organizations face growing pressure to establish reliable, compliant connections more quickly.

Integrating data from electronic medical records, laboratory systems, claims platforms, and third-party applications often involves significant manual effort from interpreting requirements to validating mappings and resolving connectivity issues. These challenges are compounded by a shortage of specialized integration skills, causing projects to stretch over months and slowing the rollout of new services.

Supporting acute and ambulatory care providers, payers, life sciences companies, and health technology builders, Rhapsody saw firsthand how dependent clinical and operational workflows were on consistent data flows. “Our customers consistently face challenges around interoperability,” says Kevin Day, chief technology officer at Rhapsody. “With a limited pool of specialized skills, integration projects can take months to complete.”

As expectations for speed, reliability, and compliance increased, Rhapsody identified the need to better support integration teams throughout the integration lifecycle helping organizations deliver integrations faster without increasing complexity or reliance on scarce specialist skills.

Rhapsody focused on embedding intelligence directly into its existing integration solutions reducing manual effort and accelerating knowledge transfer without disrupting established tools or processes. The company introduced Axon, an AI-powered agent designed to help engineers address the complexity of healthcare data integration.

Axon provides in-context guidance across requirements confirmation, build, testing, and troubleshooting, helping teams progress integrations with fewer handoffs and less manual effort. Embedded directly into existing integration engines, it supports requirements analysis, data mapping, message transformation, and testing while remaining adaptable to different healthcare environments. In addition to supporting developers during the build process, Axon can also execute agentic actions that further accelerate the development of new integrations.

The solution uses generative AI to interpret healthcare standards, integration requirements, and Rhapsody-specific product knowledge at scale. Amazon Bedrock underpins Axon’s generative AI capabilities by providing access to large language models with built-in guardrails and governance, giving Rhapsody the choice between models to deliver the right outcome both technically and commercially. Axon combines these models with retrieval-augmented generation, using Amazon OpenSearch Service to index documentation, support cases, and integration artifacts to deliver accurate, context-aware responses.

“AWS gave us the flexibility to embed advanced AI capabilities directly into our integration solutions,” says Day.

By embedding generative AI directly into established workflows, Axon is designed to help accelerate healthcare integration without disrupting existing tools, helping organizations reduce complexity while delivering integrations faster.

Built on AWS, Axon enables Rhapsody’s integration solutions to deliver real-time, in-context knowledge securely and at scale. By operating within environments designed to meet stringent healthcare compliance requirements, Axon helps organizations adopt generative AI more efficiently without compromising security or regulatory standards. As a result, customers using Axon will reduce overall system integration development timelines, reducing these projects from months to days.

“Axon on Amazon Bedrock helps healthcare organizations reduce the time and effort required to develop data integrations in complex environments,” says Day. These gains are driven by improvements across key stages of the integration lifecycle. In testing with early adopters, Axon reduced time spent clarifying and validating integration requirements by up to 80 percent and cut integration build and testing time by a similar margin. The active effort required to establish connectivity between systems also dropped from approximately 16 hours to just 4 hours.

“We’re not just automating tasks, we’re helping healthcare organizations deliver data with greater speed and confidence,” Day adds.