Artificial Intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction.
Hey Community,
Enjoy the new video on InterSystems Developers YouTube:
Hey Community,
Enjoy the new video on InterSystems Developers YouTube:
Hey Community,
We're excited to invite you to the next InterSystems UKI Tech Talk webinar:
👉AI Vector Search Technology in InterSystems IRIS
⏱ Date & Time: Thursday, September 25, 2025 10:30-11:30 UK
Speakers:
👨🏫 @Saurav Gupta, Data Platform Team Leader, InterSystems
👨🏫 @Ruby Howard, Sales Engineer, InterSystems
Hey Community!
We're happy to share the next video in the "Code to Care" series on our InterSystems Developers YouTube:
In the previous article, we saw how to build a customer service AI agent with smolagents and InterSystems IRIS, combining SQL, RAG with vector search, and interoperability.
In that case, we used cloud models (OpenAI) for the LLM and embeddings.
This time, we’ll take it one step further: running the same agent, but with local models thanks to Ollama.
Article to announce pre-built pattern expressions are available from demo application.
AI deducing patterns require ten and more sample values to get warmed up.
The entry of a single value for a pattern has therefore been repurposed for retrieving pre-built patterns.
Paste an sample value for example an email address in description and press "Pattern from Description".
The sample is tested against available built-in patterns and any matching patterns and descriptions are displayed.
Patterns can also be retrieved by Keyword.
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#InterSystems Demo Games entry
A text-to-sql demo on mqtt data analytics with RAG.
🗣 Presenter: @Jeff Liu, Sales Engineer, InterSystems
#InterSystems Demo Games entry
This demo introduces an AI-powered clinical decision support tool built on InterSystems IRIS. The use case addresses clinician burnout by unlocking the wisdom trapped in 30,000 unstructured clinical notes. We showcase IRIS's powerful vector search to perform hybrid (semantic + keyword) queries for complex diagnostic challenges. The highlight is our multi-modal Retrieval-Augmented Generation (RAG) assistant, which analyzes clinical video content in real-time to find similar past cases and synthesize evidence-based recommendations, transforming how clinicians access and utilize institutional knowledge.
🗣 Presenter: @Vishal Pallerla, Sales Architect, InterSystems
Hey Community!
We're happy to share the next video in the "Code to Care" series on our InterSystems Developers YouTube:
#InterSystems Demo Games entry
The Co-Pilot enables you to leverage InterSystems BI without deep knowledge in InterSystems BI. You can create new cube, modify existing cubes or leverage existing cubes to plot charts and pivots just by speaking to the copilot.
Presenters:
🗣 @Michael Braam, Sales Engineer Manager, InterSystems
🗣 @Andreas Schuetz, Sales Engineer, InterSystems
🗣 @Shubham Sumalya, Sales Engineer, InterSystems
#InterSystems Demo Games entry
Shows how IRIS for Health can supercharge AI development with a Smart Data Fabric to train and feed their AI Models.
Presenters:
🗣 @Kevin Kindschuh, Senior Sales Engineer, InterSystems
🗣 @Jeffrey Semmens, Sales Engineer, InterSystems
Customer support questions span structured data (orders, products 🗃️), unstructured knowledge (docs/FAQs 📚), and live systems (shipping updates 🚚). In this post we’ll ship a compact AI agent that handles all three—using:
#InterSystems Demo Games entry
Our Autonomous Business Intelligent Clerk, or ABiC for short, is a prototype revolutionizing how companies process data and make decisions. Normally, to get insights from data, you’d need IT knowledge or expertise in statistics. But with ABiC, that’s no longer necessary. All you have to do is ask your question in plain language. ABiC understands your interests and intentions, then shows a clear dashboard to guide your decisions. With ABiC, complex data is autonomously analyzed and turned into answers that support users, helping to accelerate business processes. This demo sends the metadata of InterSystems BI cubes to LLM. How does it work? Check out the video for more details!
Presenters:
🗣 @Tomo Okuyama, Sales Engineer, InterSystems
🗣 @Nobuyuki Hata, Sales Engineer, InterSystems
🗣 @Tomoko Furuzono, Sales Engineer, InterSystems
🗣 @Mihoko Iijima, Training Sales Engineer, InterSystems
#InterSystems Demo Games entry
For venture capitalists (VCs), evaluating research can be challenging. While researchers typically possess years of training and deep expertise in their field, the VCs tasked with assessing their work often lack domain-specific knowledge. This can lead to incomplete understanding of scientific data and an inability to direct organizational initiatives. To solve this problem, we have designed a solution that empowers VCs with AI-driven due diligence: ResearchExplorer. ResearchExplorer is powered by InterSystems IRIS and GPT-4o to help analyze private biomedical research alongside public sources like PubMed using Retrieval-Augmented Generation (RAG). Users submit natural language queries, and the system returns structured insights, head-to-head research comparisons, and AI-generated summaries. This allows users to bridge expertise gaps while securely protecting proprietary data.
Presenters:
🗣 @Jesse Reffsin, Senior Sales Engineer, InterSystems
🗣 @Lynn Wu, Sales Engineer, InterSystems
Hi Community,
Enjoy the new video on InterSystems Developers YouTube:
#InterSystems Demo Games entry
The Trial AI platform leverages InterSystems cloud services including the FHIR Transformation Service and IRIS Cloud SQL to assist with clinical trial recruitment, an expensive and prevalent problem. It does this by ingesting structured and unstructured healthcare data, then uses AI to help identify eligible patients.
Presenters:
🗣 @Vic Sun, Sales Engineer, InterSystems
🗣 @Mohamed Oukani, Senior Sales Engineer, InterSystems
🗣 @Bhavya Kandimalla, Sales Engineer, InterSystems
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 l
Hey Community!
We're happy to share the next video in the "Code to Care" series on our InterSystems Developers YouTube:
Those curious in exploring new GenerativeAI usecases.
Shares thoughts and rationale when training generative AI for pattern matching.
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:
The expression: "2 Alphabetic characters" matches all these values and othe
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#InterSystems Demo Games entry
An AI Agent Platform specifically built for the healthcare industry that requires no technical background to utilize. By simply defining a goal or initiative, a swarm of AI agents will conduct operations to achieve the stated end goal and measure their own efficacy along the way to continuously improve. Healthcare organizations today are facing a myriad of challenges that impact financial and clinical performance. These problems are well known, and there is a general consensus on how many of them can be alleviated with AI. However, healthcare organizations face unique challenges in implementing AI:
Presenters:
🗣 @Daniel Cole, Sales Engineer, InterSystems
🗣 @Jeff Morgan, Sales Engineer, InterSystems
🗣 @Raef Youssef, Sales Engineer, InterSystems
🗣 @Jose Ruperez, Senior Sales Engineer, InterSystems
🗣 @Harry Tong, Principal Solutions Architect, InterSystems
🗣 @Nicholai Mitchko, Sales Engineering Manager, InterSystems
Hey Community,
Watch this video to learn about AI Co-Pilot, which simplifies DTL coding and offers personalized assistance which makes it accessible to users with varying levels of technical expertise:
⏯ Accelerate DTL Coding with AI Cloud Service @ Global Summit 2024
#InterSystems Demo Games entry
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
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 engine
#InterSystems Demo Games entry
Leverage InterSystems's FHIR SQL Builder to project FHIR data to a dataset for vector embedding, and feed the vector store to a RAG chain with LLM and Chatbot.
🗣 Presenter: @Simon Sha, Sales Architect, InterSystems
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.
The separate AI model for generating Pattern match code from a sample list of values has been retrained.
The previous model r
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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. Barricade helps bridge k
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Hey Community!
We're happy to share the next video in the "Code to Care" series on our InterSystems Developers YouTube:
Hey Community!
We're happy to share the next video in the "Code to Care" series on our InterSystems Developers YouTube:
⏯ Role of Data and Interoperability in Effective AI in Healthcare
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")1.5NSELECTDISTINCT PatientRef
FROM APPOINTMENT.BOOKING
WHERE Active='Y'AND
LocationCode %PATTERN '2A1"-"1(1"CARD",1"RAD")1.5N'Use generative AI to assist create and modify pattern match code from different natural language input.
| English Description | French Description | Spanish Description |
| module A one of Strin |
Hi Community!
We’re excited to announce that several winners of the InterSystems AI Programming Contest have been invited to showcase their projects at the Tech Exchange during InterSystems Ready 2025!
Join us on Wednesday, June 25, to explore innovative, real-world solutions built with InterSystems IRIS, AI, LLMs, and intelligent agent technologies — directly from the developers who created them: