What You Should Know
- The News: Greenway Health, in collaboration with AWS, has launched the “Agentic AI Factory,” a platform designed to mass-produce secure, compliant AI agents for healthcare.
- The Shift: Unlike standalone chatbots, these “agentic” tools are built to actively execute tasks—from patient registration to billing—within the existing EHR workflow, effectively creating an “Automated Healthcare Practice.”
- The Governance: To counter trust issues, Greenway introduced the AIRE (AI Innovation and Responsible Enablement) framework, a rigorous checkpoint system ensuring every agent is traceable, explainable, and ethically governed before deployment.
Greenway Health’s Agentic AI Factory and the “Automated Healthcare Practice”
In a major collaboration with Amazon Web Services (AWS), Greenway announced the launch of its Agentic AI Factory—a production engine designed to move AI from “one-off experiment” to “standard utility.”
The distinction is critical. Generative AI creates content; Agentic AI does things. Greenway’s new ecosystem, dubbed The Automated Healthcare Practice™, aims to deploy fleets of these digital agents to handle the administrative drudgery that currently consumes 50% of a clinician’s day.
“Innovation is no longer an event, it’s a rhythm,” said Phil Nick, Vice President and Distinguished Engineer at Greenway Health. “With the Agentic AI Factory, we’re deploying new agents in weeks instead of months.”
The “Factory” Model: Speed with Guardrails
The challenge with deploying AI in healthcare isn’t just intelligence; it’s trust. A hallucinating chatbot in a retail app is an annoyance; in an EHR, it’s a lawsuit.
Greenway’s solution is to treat AI development like a manufacturing line. By leveraging AWS infrastructure—including Amazon Bedrock for model hosting and AWS HealthLake for data fluidity—Greenway has built a standardized assembly line for digital workers.
- Strands Agents build the bots.
- Bedrock Guardrails moderate them.
- Model Context Protocol (MCP) servers ensure they play nice with existing APIs.
This “Factory” approach allows Greenway to double its development speed while maintaining a standardized safety protocol.
AIRE: The Governance Checkpoint
At the heart of this factory is the AIRE framework (AI Innovation and Responsible Enablement). Think of it as the Quality Assurance (QA) department for digital employees.
Before any agent is deployed to a doctor’s office, it must pass an “AIRE Checkpoint”—a rigorous audit of its explainability and security. The goal is to solve the “Black Box” problem. Clinicians don’t just need to know what an AI suggests; they need to know why it suggested it. “We believe technology should serve the clinician, not the other way around,” notes Greenway CEO Richard Atkin. By enforcing traceability, AIRE attempts to restore the human oversight that “black box” algorithms often strip away.
