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⏯ First Customers Using Vector Search - Real World Experiences and Lessons Learned @ READY 2025

Introduction

As AI-driven automation becomes an essential part of modern information systems, integrating AI capabilities into existing platforms should be seamless and efficient. The IRIS Agent project showcases how generative AI can work effortlessly with InterSystems IRIS, leveraging its powerful interoperability framework—without the need to learn Python or build separate AI workflows from scratch.
This project explores how ChatGPT and Anthropic Claude, two of the most advanced AI models, can interact with IRIS using Custom GPTs and the Model Context Protocol (MCP).

Hi, Community!

See how to efficiently validate incoming CDA documents and comply with standards using the cloud-based CDA Validation Service!

Streamlining CDA Data Feed Setup in Health Connect Cloud

Supply Chain refers to a set of processes and activities performed by the company's business areas and its suppliers and partners (stakeholders), from the acquisition of raw materials, through production, to delivery to the end consumer. It can be better managed using SCM solutions with the orchestration of the InterSystems IRIS:

What are best practices for JSON transformation in IRIS interoperability? This is for a non-healthcare use case, so any tools we happen to have around FHIR might not be available. The motivating use case is trimming down a verbose and needlessly complex REST API response to feed to an LLM - trying to reduce token usage and maybe get better results from less noisy data.

Specifically, I'm imagining matching based on JSONPath expressions and simplifying structures based on the inferred type of elements rather than a full schema.

Hey everyone.

As part of an ongoing mission to track down orphaned HL7 Messages in our integration engine, I have been digging into our environment to track down the causes.

Having looked at various posts here (including one of my own) there are a few scenarios that can create orphaned messages resulting in excessive disk space usage. These scenarios are generally:

1. Purging an environment with the option "Bodies Too" deselected
2. Code creating/saving a Message but then not sending it
3. BPL errors similar to 2, or a scenario where the response to a Call component is not set.

I am using IRIS for Windows (x86-64) 2022.1 (Build 209) Tue May 31 2022 12:27:55 EDT [Health:3.5.0]. I created Interoperability Production with a Service to read file from S3 bucket and an Operation to write files to a different S3 bucket. I specified AWS  ProviderCredentialsFile.

I see "Terminating Job 7096 / 'From S3 Bucket' with Status = ERROR #5023: Remote Gateway Error: Connection cannot be established, %QuitTask=

Do I need anything like Python libraries or AWS CLI to make this work?

The Interoperability user interface project has continued from 2025.1 and has incorporated many of the items that you – our customers and partners – have suggested and observed.  We are continuing to invest in feedback and updating this important user experience.   In the latest release, 2025.3 for IRIS, IRIS for Health, Health Connect and Health Connect Cloud, the DTL Editor and Production Configuration applications that are available for opt-in. 
NOTE:

• You can switch between the modernized and standard experiences. 
• All other Interoperability screens remain in the Standard user interface.

Hello Community,

Great news for developers who have just started working with InterSystems IRIS! We have hands‑on interactive tutorials available via the Instruqt platform! These are perfect for getting up to speed quickly, playing in real environments, and building confidence with IRIS‑based development.

Here is the list of available tutorials:

• Full Stack Tutorial - Experience how IRIS supports full-stack system architecture. 
• InterSystems Interoperability - Explore IRIS interoperability tools for connecting and integrating systems. 
• IRIS for Health Interoperability - Learn to use IRIS for Health features in application integration with data from an EHR (Electronic Health Record). 
• REST + Angular Application - Practice building applications with IRIS REST services. 
• RAG using IRIS Vector Search - Discover IRIS Vector Search capabilities for AI-powered applications. 

The 2025.3 release of InterSystems IRIS® data platform, InterSystems IRIS^® for Health, and HealthShare^® Health Connect is now Generally Available (GA). This is a Continuous Delivery (CD) release.

Release Highlights:

• Secure Wallet: A new encrypted framework for managing sensitive data, built on the IRISSECURITY database, improving system security and access control.
• Expanded Observability & Cloud Integrations: Enhanced OpenTelemetry metrics, including new process and ECP metrics, plus journal archiving now supports Azure Blob Storage for cost-efficient retention.

Overview

Fast Healthcare Interoperability Resources (FHIR) is a standardized framework developed by HL7 International to facilitate the exchange of healthcare data in a flexible, developer-friendly, and modern way. It leverages contemporary web technologies to ensure seamless integration and communication across healthcare systems.

Key FHIR Technologies

• RESTful APIs for resource interaction
• JSON and XML for data representation
• OAuth2 for secure authorization and authentication

Hi Community,

In the first part of this series, we examined the fundamentals of Interoperability on Python (IoP), specifically how it enables us to construct such interoperability elements as business services, processes, and operations using pure Python.

Now, we are ready to take things a step further. Real-world integration scenarios extend beyond simple message handoffs.They involve scheduled polling, custom message structures, decision logic, filtering, and configuration handling.In this article, we will delve into these more advanced IoP capabilities and demonstrate how to create and run a more complex interoperability flow using only Python.

To make it practical, we will build a comprehensive example: The Reddit Post Analyzer Production. The concept is straightforward: continuously retrieving the latest submissions from a chosen subreddit, filtering them based on popularity, adding extra tags to them, and sending them off for storage or further analysis.

The ultimate goal here is a reliable, self-running data ingestion pipeline. All major parts (the Business Service, Business Process, and Business Operation) are implemented in Python, showcasing how to use IoP as a Python-first integration methodology.

Modern data architectures utilize real-time data capture, transformation, movement, and loading solutions to build data lakes, analytical warehouses, and big data repositories. It enables the analysis of data from various sources without impacting the operations that use them. To achieve this, establishing a continuous, scalable, elastic, and robust data flow is essential. The most prevalent method for that is through the CDC (Change Data Capture)  technique. CDC monitors for small data set production, automatically captures this data, and delivers it to one or more recipients, including analytical data repositories. The major benefit is the elimination of the D+1 delay in analysis, as data is detected at the source as soon as it is produced, and later is replicated to the destination.

This article will demonstrate the two most common data sources for CDC scenarios, both as a source and a destination. For the data source (origin), we will explore the CDC in SQL databases and CSV files. For the data destination, we will use a columnar database (a typical high-performance analytical database scenario) and a Kafka topic (a standard approach for streaming data to the cloud and/or to multiple real-time data consumers).

Overview

This article will provide a sample for the following interoperability scenario:

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Enjoy the new video on InterSystems Developers YouTube:

⏯ Using SerenityGPT to Build Out an Application GenAI Middleware at InterSystems @ Ready 2025

Introduction

In this article, we will explore various approaches to extending and customizing the behavior of InterSystems IRIS (and IRIS Health) built-in interoperability message routers.

Message routers perform one of the core functions of Enterprise Application Integration (EAI) and are among the most frequently used business processes in interoperability productions.

When I started my journey with InterSystems IRIS, especially in Interoperability, one of the initial and common questions I had was: how can I run something on an interval or schedule? In this topic, I want to share two simple classes that address this issue. I'm surprised that some similar classes are not located somewhere in EnsLib. Or maybe I didn't search well? Anyway, this topic is not meant to be complex work, just a couple of snippets for beginners.

The Interoperability user interface now includes modernized user experiences for the DTL Editor and Production Configuration applications that are available for opt-in in all interoperability products. You can switch between the modernized and standard views. All other Interoperability screens remain in the Standard user interface. Please note that changes are limited to these two applications and we identify below the functionality that is currently available. 

To try out the new screens prior to upgrading, you can download the 2025.

What is XML?

XML (eXtensible Markup Language) is a flexible, text-based, and platform-independent format used to store and transport data in a well-structured way that is both human- and machine-readable. XML permits users to define custom tags to describe the meaning and organization of their data. For example: <book><title>The Hitchhiker's Guide</title></book>.

An XML document is self-descriptive and structured as a hierarchical tree of elements. Every document has a single root element that encapsulates all other content.

Over time, while I was working with Interoperability on the IRIS Data Platform, I developed rules for organizing a project code into packages and classes. That is what is called a Naming Convention, usually. In this topic, I want to organize and share these rules. I hope it can be helpful for somebody.

Disclaimer: This guide is a good fit for Interoperability projects. When you have integrations, data flows, when you use IRIS for ETL processes, etc. Overall, when your code is combined with Productions.

Hey Community!

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      ⏯  Source Control Interoperability Productions in a Decomposed Format @ Ready 2025

Hi all,

Let's do some more work about the testing data generation and export the result by REST API.😁

Here, I would like to reuse the datagen.restservice class which built in the pervious article Writing a REST api service for exporting the generated patient data in .csv

This time, we are planning to generate a FHIR bundle include multiple resources for testing the FHIR repository.

Here is some reference for you, if you want to know mare about FHIR The Concept of FHIR: A Healthcare Data Standard Designed for the Future

OK... Let's start😆

1. Create a new utility class datagen.utli.

Hi community,

I have a service that uses EnsLib.RecordMap.Service.FTPService to capture files in an FTP directory.

Instead of uploading them all at once, I would need to do so one at a time.

I have a class that extends this class because it preprocesses, saves everything in the RecordMap class, and then processes all the records at once.

When I invoke the BP, it does so through the method set tStatus = ..SendRequest(message, 1).

I've set the SynchronousSend flag to 1, but it continues processing all the files at

Hi Community,

Enjoy the new video on InterSystems Developers YouTube:

⏯ How to Boost Data Quality with Interoperability @ Ready 2025

To manage the accumulation of production data, InterSystems IRIS enables users to manage the database size by periodically purging the data. This purge can apply to messages, logs, business processes, and managed alerts.

Please check the documentation for more details on the settings of the purge task:
https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls?KEY=EGMG_purge#EGMG_purge_settings

An issue that many users ran into is still finding old messages after running the purge task for messages. For example, a user has a purge task for messages that has NumberOfDaysToKeep=45.

Hi,

It's me again😁, recently I am working on generating some fake patient data for testing purpose with the help of Chat-GPT by using Python. And, at the same time I would like to share my learning curve.😑

1st of all for building a custom REST api service is easy by extending the %CSP.REST

Creating a REST Service Manually

Let's Start !😂

1. Create a class datagen.restservice which extends  %CSP.REST 

Class datagen.restservice Extends %CSP.REST
{
Parameter CONTENTTYPE = "application/json";
}

2.

I know the next ones:

1. Place all different settings in environment variables. You have a different .env file for each environment, and you must add some code to Production for reading and setting these values. It's good for deploying into containers, but challenging for management when we have a large production. I mean, we have many settings that can vary depending on the environment: active flag, pool size, timeouts, and so on. Not only endpoints.

2. My own case.

Hey Community,

The InterSystems team put on our monthly Developer Meetup with a triumphant return to CIC's Venture Café, the crowd including both new and familiar faces. Despite the shakeup in both location and topic, we had a full house of folks ready to listen, learn, and have discussions about health tech innovation!

For historic reasons we've got a mix of ADT feeds coming out of our PAS (TrakCare) to a wide range of downstream systems. In particular, there are some that are direct from TrakCare to the downstream systems, and many more that pass through Ensemble as our integration engine.

This is complicating management of the integrations, and so we'd like everything to go through the integration engine.

I was really surprised that such a flexible integration platform with a rich toolset specifically for app connections has no out-of-the-box Enterprise Service Bus solution. Like Apache ServiceMix, Mule ESB, SAP PI/PO, etc, what’s the reason? What do you think? Has this pattern lost its relevance completely nowadays? And everybody moved to message brokers, maybe?

Wiki time: An enterprise service bus (ESB) implements a communication system between mutually interacting software applications in a service-oriented architecture (SOA) .

Hey Community!

We're happy to share a new video from our InterSystems Developers YouTube:

⏯  Python Interoperability Productions @ Ready 2025