#Artificial Intelligence (AI)

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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.

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Article Luis Angel Pérez Ramos · Oct 31 5m read

Yes, yes! Welcome! You haven't made a mistake, you are in your beloved InterSystems Developer Community in Spanish.

You may be wondering what the title of this article is about, well it's very simple, today we are gathered here to honor the Inquisitor and praise the great work he performed. 

So, who or what is the Inquisitor?

Perfect, now that I have your attention, it's time to explain what the Inquisitor is. The Inquisitor is a solution developed with InterSystems technology to subject public contracts published daily on the platform  https://contrataciondelestado.es/ to scrutiny.

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Discussion Yuri Marx · Oct 12

This anthropic article made me think of several InterSystems presentations and articles on the topic of data quality for AI applications. InterSystems is right that data quality is crucial for AI, but I imagined there would be room for small errors, but this study suggests otherwise. That small errors can lead to big hallucinations. What do you think of this? And how can InterSystems technology help?

https://www.anthropic.com/research/small-samples-poison

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Article Pietro Di Leo · Oct 9 6m read

Introduction

In my previous article, I introduced the FHIR Data Explorer, a proof-of-concept application that connects InterSystems IRIS, Python, and Ollama to enable semantic search and visualization over healthcare data in FHIR format, a project currently participating in the InterSystems External Language Contest.

In this follow-up, we’ll see how I integrated Ollama for generating patient history summaries directly from structured FHIR data stored in IRIS, using lightweight local language models (LLMs) such as Llama 3.2:1B or Gemma 2:2B.

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Article Yu Han Eng · Oct 5 2m read

With the rapid adoption of telemedicine, remote consultations, and digital dictation, healthcare professionals are communicating more through voice than ever before. Patients engaging in virtual conversations generate vast amounts of unstructured audio data, so how can clinicians or administrators search and extract information from hours of voice recordings?

Enter IRIS Audio Query - a full-stack application that transforms audio into a searchable knowledge base. With it, you can:

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Announcement Derek Gervais · Oct 9

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!

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Announcement Derek Gervais · Sep 26

Hey Community,

The InterSystems team recently held another monthly Developer Meetup in the AWS Boston office location in the Seaport, breaking our all-time attendance record with over 80 attendees! This meetup was our second time being hosted by our friends at AWS, and the venue was packed with folks excited to learn from our awesome speakers.

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Announcement Anastasia Dyubaylo · Sep 18

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

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Article Alberto Fuentes · Sep 16 4m read

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.

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Article Alex Woodhead · Sep 13 4m read

Plug-N-Play on Pattern Match WorkBench

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.

Example: Email address

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.

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Announcement Michael Braam · Aug 29

#InterSystems Demo Games entry

⏯️ Copilot for InterSystems Embedded BI

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

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Article Alberto Fuentes · Sep 1 7m read

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:

  • 🧠 Python + smolagents to orchestrate the agent’s “brain”
  • 🧰 InterSystems IRIS for SQL, Vector Search (RAG), and Interoperability (a mock shipping status API)
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Announcement Vic Sun · Jul 31

#InterSystems Demo Games entry

⏯️  AI Clinical Trial Platform

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

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Question Oliver Wilms · Apr 21

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

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Article Alex Woodhead · Jun 19 3m read

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"
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