Hey Community!

We're happy to share the next video in the "Code to Care" series on our InterSystems Developers YouTube:

⏯  Can AI Fix Bugs? Inside the Benchmarking Effort

If you’ve ever watched a true artisan—whether a potter turning mud into a masterpiece or a luthier bringing raw wood to life as a marvelous guitar—you know that magic isn’t in the materials, but in care, craft, and process. I know this firsthand: my handmade electric guitar is a daily inspiration, but I’ll admit—creating something like that is a talent I don’t have.

Yet, in the digital world, I often see people hoping for “magic” from generative AI by typing vague, context-free prompts like “build an app.” The results are usually frustratingly shallow—no artistry, no finesse.

I am brand new to using AI. I downloaded some medical visit progress notes from my Patient Portal. I extracted text from PDF files. I found a YouTube video that showed how to extract metadata using an OpenAI query / prompt such as this one:

ollama-ai-iris/data/prompts/medical_progress_notes_prompt.txt at main · oliverwilms/ollama-ai-iris
 

I combined @Rodolfo Pscheidt Jr https://github.com/RodolfoPscheidtJr/ollama-ai-iris with some files from @Guillaume Rongier https://openexchange.intersystems.com/package/iris-rag-demo.

I attempted to run

python3 query_data.py
Traceback (most recent call last):
  F

Thirteen years ago, I attained dual undergraduate degrees in electrical engineering and math, then promptly started full-time at InterSystems using neither.One of my most memorable and stomach-churning academic experiences was in Stats II.On an exam, I was solving a moderately difficult confidence interval problem.I was running out of time, so (being an engineer) I wrote out the definite integral on the exam paper, punched it into my graphing calculator, wrote an arrow with “calculator” over it, then wrote the result.

Hey Community!

We're happy to share the next video in the "Code to Care" series on our InterSystems Developers YouTube:

⏯  Can AI fix bugs? The setup

Audience

Those curious in exploring new GenerativeAI usecases.

Shares thoughts and rationale when training generative AI for pattern matching.

Challenge 1 - Simple but no simpler

A developer aspires to conceive an elegant solution to requirements.
Pattern matches ( like regular expressions ) can be solved for in many ways. Which one is the better code solution?
Can an AI postulate an elegant pattern match solution for a range of simple-to-complex data samples?

Consider the three string values:

• "AA"
• "BB"
• "CC"

The expression: "2 Alphabetic characters" matches all these values and other intuitively

Hey Community!

We're happy to share the next video in the "Code to Care" series on our InterSystems Developers YouTube:

⏯  Agentic AI in Action: Building a Decision-Making Loop with LLMs

#InterSystems Demo Games entry

⏯️ Care Compass – InterSystems IRIS powered RAG AI assistant for Care Managers

Care Compass is a prototype AI assistant that helps caseworkers prioritize clients by analyzing clinical and social data. Using Retrieval Augmented Generation (RAG) and large language models, it generates narrative risk summaries, calculates dynamic risk scores, and recommends next steps. The goal is to reduce preventable ER visits and support early, informed interventions.

Presenters:
🗣 @Brad Nissenbaum, Sales Engineer, InterSystems
🗣 @Andrew Wardly, Sales Engineer, InterSystems
🗣 @Fan Ji, Solution Developer, InterSystems
🗣 @Lynn Wu, Sales Engineer, InterSystems

☤ Care 🩺 Compass 🧭 - Proof-of-Concept - Demo Games Contest Entry

Introducing Care Compass: AI-Powered Case Prioritization for Human Services

In today’s healthcare and social services landscape, caseworkers face overwhelming challenges. High caseloads, fragmented systems, and disconnected data often lead to missed opportunities to intervene early and effectively. This results in worker burnout and preventable emergency room visits, which are both costly and avoidable.

Care Compass was created to change that.

Disclaimer: Care Compass project is a technical demonstration developed by sales engineers

Thank you community for translating an earlier article into Portuguese.
Am returning the favor with a new release of Pattern Match Workbench demo app.

Added support for Portuguese.

The labels, buttons, feedback messages and help-text for user interface are updated.

Pattern Descriptions can be requested for the new language.

The single AI Model for transforming user prompt into Pattern match code was fully retrained.

Values to Pattern Code Model also retrained

The separate AI model for generating Pattern match code from a sample list of values has been retrained.
The previous model release exhibited

INTRO

Barricade is a tool developed by ICCA Ops to streamline and scale support for FHIR-to-OMOP transformations for InterSystems OMOP.Our clients will be using InterSystems OMOP to transform FHIR data to this OMOP structure.As a managed service, our job is to troubleshoot any issues that come with the transformation process.Barricade is the ideal tool to aid us in this process for a variety of reasons.First, effective support demands knowledge across FHIR standards, the OHDSI OMOP model, and InterSystems-specific operational workflows—all highly specialized areas.

My use case is I want AI to extract six pieces of key information from medical visit notes.

It works okay with notes from Epic patient portals. I am struggling with one of my own visit Summaries. So far I have not been able to instruct ollama to give me a JSON response where it gave me what I am asking for.

My original medical_progress_notes_prompt was:

Medical progress note:
---
(document)
---

You are an expert in analyzing medical progress notes. Please carefully read the provided progress note above and extract the following key information:

Extract these six (6) properties from the progress note:
-

Audience

Those curious in exploring new GenerativeAI usecases.

Developers and analysts looking for a quick way to tame the Pattern Match operator.

In both ObjectScript and SQL this has a quite visually dense format.

if booking?2A1"-"1(1"CARD",1"RAD")1.5N

SELECTDISTINCT PatientRef
FROM APPOINTMENT.BOOKING
WHERE Active='Y'AND
LocationCode %PATTERN '2A1"-"1(1"CARD",1"RAD")1.5N'

Challenge

Use generative AI to assist create and modify pattern match code from different natural language input.

Artificial Intelligence (AI) is getting a lot of attention lately because it can change many areas of our lives. Better computer power and more data have helped AI do amazing things, like improving medical tests and making self-driving cars. AI can also help businesses make better decisions and work more efficiently, which is why it's becoming more popular and widely used. How can one integrate the OpenAI API calls into an existing IRIS Interoperability application?

Hi developers!

This will be a very short article as in April 2025 with Lovable and other Prompt-to-UI tools it becomes possible to build the frontend with prompting. Even to the folks like me who is not familiar with modern UI techics at all.

Well, I know at least the words javascript, typescript and ReactJS, so in this very short article we will be building the ReactJS UI to InterSystems FHIR server with Lovable.ai.

Let's go!

I combined @Rodolfo Pscheidt https://github.com/RodolfoPscheidtJr/ollama-ai-iris with some files from @Guillaume Rongier https://openexchange.intersystems.com/package/iris-rag-demo.

My own project is https://github.com/oliverwilms/ollama-ai-iris

I can run load_data.py and it connects to IRIS (same container).

When I try to run query_data.py https://github.com/oliverwilms/ollama-ai-iris/blob/main/query_data.py , it cannot connect to ollama:

ConnectionError: Failed to connect to Ollama. Please check that Ollama is downloaded, running and accessible.

I wonder if I need to add in query_data.py, how it

Hi, colleagues!

As you can see the new topic of the programming contest - AI Agents. 

The topic was over-hyped recently on the Internet and has different meanings. You might get curious about what we mean by AI agents in regard to the InterSystems programming contest.

Hi Developers!

We are happy to present the bonuses page for the applications submitted to the InterSystems AI Programming Contest!

See the results below.

See the Langchain IRIS Tool in action on YouTube. You can see IRIS metrics, discover classes, generate fake data, and so on. Project using Ollama, IRIS VectorDB, Streamlit and Langchain.

What if you could speak in a chat to check what happens in Interoperability, is there any errors, and even solve some types of issues.

With MCP server, you can connect any of your MCP Client, for instance Claude, to IRIS, and ask to check on Interoperability

If you want to know if a class about a topic already exists asking a simple natural language question, it is possible now. Download and run the application https://openexchange.intersystems.com/package/langchain-iris-tool to know all about your project classes in a Chat.

Now it is possible ask your IRIS server using an AI Chat or compose other agent applications to get:

1. List the server metrics
2. Return intersystems iris server information
3. Save the global value Hello to the global name Greetings
4. Get the global value Greetings
5. Kill the global Greetings
6. List the classes on IRIS Server
7. Where is intersystems iris installed?
8. Return namespace information from the USER
9. List the CSP Applications
10. List the server files on namespace USER
11. List the jobs on namespace %SYS

To do it, get and install the new package langchain-iris-tool

Hey Community,

It's time for the first programming contest of the year, and there's a surprise so read on! Please welcome:

🏆 InterSystems AI Programming Contest: Vector Search, GenAI, and AI Agents 🏆

Duration: March 17 - April 6, 2025

Prize pool: $12,000 + a chance to be invited to the GlobalSummit2025!

Hi Community,

Check out this new video that shows how to build the UI for InterSystems FHIR server from scratch using AI with no previous frontend experience:

📺 Building and Deploying React Frontend for the InterSystems FHIR server in 20 minutes with Lovable AI

🗣 Presenter: @Evgeny Shvarov, Senior Manager of Developer and Startup Programs, InterSystems

Hey Community!
The AI Programming Contest has begun, and we want to support you with an inspiring discussion on AI agents. Let’s explore the past, present, and future of AI agents together!

• Do you already use AI agents? If so, which ones?
• What functions could AI agents help you with in your work or personal life?
• What do AI agents still lack to become truly useful and autonomous?

Share your thoughts! The most interesting answers ideas will earn an extra 100 points on Global Masters. 

If you're not yet part of Global Masters, click here and register now!

But remember, no points are as

Hi Developers!

Here're the technology bonuses for the InterSystems AI Programming Contest: Vector Search, GenAI and AI Agents that will give you extra points in the voting:

• Agent AI solution - 5
• Vector Search usage - 4
• Embedded Python - 3
• LLM AI or LangChain usage: Chat GPT, Bard, and others - 3
• IntegratedML usage - 3
• Docker container usage - 2 
• ZPM Package deployment - 2
• Online Demo - 2
• Implement InterSystems Community Idea - 4
• Find a bug in Vector Search, or Integrated ML, or Embedded Python - 2
• First Article on Developer Community - 2
• Second Article On DC - 1
• First Time Contribution - 3
• Video on YouTube - 3
• Suggest a new idea - 1

See the details below.

Introduction

To achieve optimized AI performance, robust explainability, adaptability, and efficiency in healthcare solutions, InterSystems IRIS serves as the core foundation for a project within the x-rAI multi-agentic framework. This article provides an in-depth look at how InterSystems IRIS empowers the development of a real-time health data analytics platform, enabling advanced analytics and actionable insights. The solution leverages the strengths of InterSystems IRIS, including dynamic SQL, native vector search capabilities, distributed caching (ECP), and FHIR interoperability. This innovative approach directly aligns with the contest themes of "Using Dynamic SQL & Embedded SQL," "GenAI, Vector Search," and "FHIR, EHR," showcasing a practical application of InterSystems IRIS in a critical healthcare context.

Hi Community,

This is a detailed, candid walkthrough of the IRIS AI Studio platform. I speak out loud on my thoughts while trying different examples, some of which fail to deliver expected results -  which I believe is a need for such a platform to explore different models, configurations and limitations. This will be helpful if you're interested in how to build 'Chat with PDF' or data recommendation systems using IRIS DB and LLM models.

Hi Community,

We're pleased to invite you to the upcoming webinar in Hebrew:

👉 Hebrew Webinar: GenAI + RAG - Leveraging Intersystems IRIS as your Vector DB👈

📅 Date & time: February 26th, 3:00 PM IDT

Hi all!Here I would like to share how we use vector search and GenAI with InterSystems technology.As an example, I'll describe BG-AppealAI project, which our company submitted to the InterSystems Vector Search, GenAI and ML Contest.BG-AppealAI application can write an appeal if you upload an insurance contract and the insurance company’s letter with a refusal to pay medical expenses.Of course, we are aware that at the moment AI has not reached such a level as to create ready-made legal documents.