#GitHub

I created a new repo called ipm-module-budget from https://github.com/intersystems-community/intersystems-iris-dev-template template.

I cloned the repo to an EC2 instance in AWS. When I try to build image, I see this error:

#8 22.09 [IRISAPP|ipm-module-budget] Reload START (/home/irisowner/dev/)Segmentation fault (core dumped) #8 ERROR: process "/bin/sh -c pip3 install -r requirements.txt && iris start IRIS && \tiris session IRIS < iris.scri pt && iris stop IRIS quietly" did not complete successfully: exit code: 139

Why This Integration Matters

InterSystems continues to push AI capabilities forward natively in IRIS — vector search, MCP support, and Agentic AI capabilities. That roadmap is important, and there is no intention of stepping back from it.

But the AI landscape is also evolving in a way that makes ecosystem integration increasingly essential. Tools like Dify — an open-source, production-grade LLM orchestration platform — have become a serious part of enterprise AI stacks.

In the modern healthcare landscape, finding clinically similar patients often feels like looking for a needle in a haystack. Traditional keyword searches often fail because medical language is highly nuanced; a search for "Heart Failure" might miss a record containing "Congestive Cardiac Failure."

I am excited to share iris-medmatch, an AI-powered patient matching engine built on InterSystems IRIS for Health. By leveraging Vector Search, this tool understands clinical intent rather than just matching literal strings.