#Artificial Intelligence (AI)

Introducing Smart Clinical Sidechick — the intelligent, no-drama partner your EHR wishes it could be. She reads FHIR data in real time, interprets lab results without ghosting, and explains clinical alerts like she actually cares. Built with GPT-4 brains and YAML sass, she’s not here to replace your main EHR—just to make it look bad. Tired of irrelevant alerts and cryptic warnings? Sidechick serves up real, explainable insights, not vague “elevated risk” vibes. And when your backend crashes, she doesn’t panic—she self-heals. Secure, responsive, and (unlike your last vendor) emotionally availab

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.p

Hi Community,

We’re excited to introduce the AskMe assistant—try it out for yourself!

I read the article by @Rodolfo Pscheidt:

https://community.intersystems.com/post/ollama-ai-iris

I forked his app and copied selected files from @Guillaume Rongier iris-rag-demo to make it containerized:

oliverwilms/ollama-ai-iris
 

I ran load_data.py and I got this output:

irisowner@e10968e4da42:/irisdev/app$ python3 load_data.py
Document ID: cbfa2f20-6627-407b-bbad-31722d18ca13
modules.json: 100%|█████████████████████████████████████████████████████████████| 349/349 [00:00<00:00, 778kB/s]
config_sentence_transformers.json: 100%|████████████████████████████████████████| 123/123 [00:00<00:00,

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.

Hi Community,
Traditional keyword-based search struggles with nuanced, domain-specific queries. Vector search, however, leverages semantic understanding, enabling AI agents to retrieve and generate responses based on context—not just keywords.
This article provides a step-by-step guide to creating an Agentic AI RAG (Retrieval-Augmented Generation) application.

Implementation Steps:

1. Create Agent Tools
   • Add Ingest functionality: Automatically ingests and index documents (e.g., InterSystems IRIS 2025.1 Release Notes).
   • Implement Vector Search Functionality
2. Create Vector Search Agent
3. Handoff to Triage (Main Agent)
4. Run The Agent 

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

# IRIS-Intelligent Butler
IRIS Intelligent Butler is an AI intelligent butler system built on the InterSystems IRIS data platform, aimed at providing users with comprehensive intelligent life and work assistance through data intelligence, automated decision-making, and natural interaction.
## Application scenarios
 adding services, initializing configurations, etc. are currently being enriched
## Intelligent Butler
IRIS Smart Manager utilizes the powerful data management and AI capabilities of InterSystems IRIS to create a highly personalized, automated, secure, and reliable intelligent life and wo

I just realized I never finished this serie of articles!

In today's article, we'll take a look at the production process that extracts the ICD-10 diagnoses most similar to our text, so we can select the most appropriate option from our frontend.

Looking for diagnostic similarities:

From the screen that shows the diagnostic requests received in HL7 in our application, we can search for the ICD-10 diagnoses closest to the text entered by the professional.

To speed up the search process, we stored the vectorized text of the diagnosis received at the time of capturing the HL7 message in ou

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!

With the introduction of vector data types and the Vector Search functionality in IRIS, a whole world of possibilities opens up for the development of applications and an example of these applications is the one that I recently saw published in a public contest by the Ministry of Health from Valencia in which they requested a tool to assist in ICD-10 coding using AI models.

How could we implement an application similar to the one requested? Let's see what we would need:

1. List of ICD-10 codes, which we will use as context for our RAG application to search for diagnoses within the plain texts

Hi Community,

We're continuing to improve and teach our Developer Community AI, and in this iteration, we've added descriptions of Open Exchange Applications to the knowledge base!

This new feature will allow DC AI to search app descriptions to answer your questions. This will give you better answers that require programming, not just general information.

To add this knowledge to your search, just tick the checkbox Open Exchange Applications:

Hey Community!

We're happy to share the next video in the series dedicated to Gen AI on our InterSystems Developers YouTube:

⏯ Is your data ready for AI?

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.

InterSystems has been at the forefront of database technology since its inception, pioneering innovations that consistently outperform competitors like Oracle, IBM, and Microsoft. By focusing on an efficient kernel design and embracing a no-compromise approach to data performance, InterSystems has carved out a niche in mission-critical applications, ensuring reliability, speed, and scalability.

A History of Technical Excellence

During its earlier years, InterSystems distinguished itself through its groundbreaking database architecture, which addressed inefficiencies in legacy relationa

Hey Community!

We're happy to share the next video in the series dedicated to Gen AI on our InterSystems Developers YouTube:

⏯ Energy Consumption for AI

Hey Community!

We are pleased to invite everyone to participate in the new webinar in German dedicated to AI:

➡️ Interoperability as a catalyst for AI

⏱ Date & Time:  March 11, 2025, 3:30 pm CET

👨‍🏫 Speakers:  

• @Thomas Nitzsche, Sales Manager, InterSystems
• Dr. Olaf Iseringhausen, Head of Competence Center Health Care Solutions, Bechtle
• Dr. @Erion Dasho, Clinical Advisor, InterSystems

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 happy to share the next video in the series dedicated to Gen AI on our InterSystems Developers YouTube:

⏯ AI model distillation

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. However, it's already possible to create tools to serve as assistants for specialists or o

Learning LLM Magic

The world of Generative AI has been pretty inescapable for a while, commercial models running on paid Cloud instances are everywhere.  With your data stored securely on-prem in IRIS, it might seem daunting to start getting the benefit of experimentation with Large Language Models without having to navigate a minefield of Governance and rapidly evolving API documentation.   If only there was a way to bring an LLM to IRIS, preferably in a very small code footprint....

Some warnings before we start

1. This article targets any recent version of IRIS (2022+) which includes Embe

Hi Community!

We're happy to share the next video in the series dedicated to Gen AI on our InterSystems Developers YouTube:

⏯ Open Source LLMs

Hey Community,

Enjoy the new video on InterSystems Developers YouTube:

⏯ First Vector Search on IRIS

Hey Community!

Check out the new video dedicated to Gen AI on our InterSystems Developers YouTube:

⏯ Healthcare Use-Case: Patient Portal Messages

Hi Community,

We're excited to invite you to the webinar 2025 Data Management: Technology Trends & Predictions.

Join this webinar for an engaging and insightful tech talk on the latest trends in data management technology in the UK and Ireland.

⏱ Date & Time: Thursday, January 23, 10:30 AM GMT

👨‍🏫 Speakers: 

• Andy Hayler, Practice Leader, Bloor Research
• @Mike Fuller, Regional Director of Marketing, InterSystems UK&I

Hey Community!

Check out the new video dedicated to Gen AI on our InterSystems Developers YouTube:

⏯ AI Governance in IT solutions

We all know that having a set of proper test data before deploying an application to production is crucial for ensuring its reliability and performance. It allows to simulate real-world scenarios and identify potential issues or bugs before they impact end-users. Moreover, testing with representative data sets allows to optimize performance, identify bottlenecks, and fine-tune algorithms or processes as needed. Ultimately, having a comprehensive set of test data helps to deliver a higher quality product, reducing the likelihood of post-production issues and enhancing the overall user experience. 

In this article, let's look at how one can use generative AI, namely Gemini by Google, to generate (hopefully) meaningful data for the properties of multiple objects. To do this, I will use the RESTful service to generate data in a JSON format and then use the received data to create objects.