Hi Community,

We’re excited to invite you to take part in shaping the next generation of ObjectScript development tools. We’re working on an AI-powered ObjectScript coding assistant designed specifically for IRIS developers. Not a generic AI adapted for ObjectScript, but a solution built from the ground up to understand ObjectScript idioms, IRIS APIs, interoperability productions, and real-world developer workflows.

To make sure we build something truly useful, we need your input.

👉 ObjectScript Coder Agent Developer Survey 👈

The Rut

Up until early this year, I haven't been not doing much coding at all -- I had gotten sick of it.

After many years as a hands-on software engineer and data scientist, I got burned out around 2015. I switched to business development roles focused on "external innovation," then joined InterSystems in 2019 as a product manager. I missed the creative aspects of coding, but not the tedium. The endless cycle of boilerplate, debugging, and context-switching had left me creatively depleted. Like Jim Carrey's character in Yes Man, I found myself saying "no" to new projects -- so much so that I

We're excited to announce the Early Access Program for IntegratedML Custom Models, a powerful new capability coming in IRIS 2026.1!

What Is It?

IntegratedML Custom Models extends the existing IntegratedML/AutoML feature by letting you deploy your own custom Python ML models directly within SQL queries.

Introduction

In InterSystems IRIS 2024.3 and subsequent IRIS versions, the AutoML component is now delivered as a separate Python package that is installed after installation. Unfortunately, some recent versions of Python packages that AutoML relies on have introduced incompatibilities, and can cause failures when training models (TRAIN MODEL statement). If you see an error mentioning "TypeError" and the keyword argument "fit_params" or "sklearn_tags", read on for a quick fix.

Root Cause

• scikit-learn updated to version 1.6.0, deprecating fit_params.
• scikeras is no longer updating the

We've recently made available a new version of InterSystems IRIS in the Vector Search Early Access Program, featuring a new Approximate Nearest Neighbor index based upon the Hierarchical Navigable Small World (HNSW) indexing algorithm. This addition allows for highly efficient, approximate nearest-neighbor searches over large vector datasets, dramatically improving query performance and scalability.

The HNSW algorithm is designed to optimize vector search for high-dimensional data by building a graph-based structure, making it faster to find approximate neighbors in large collections of

The Data Platforms team is very pleased to announce the 2021.2 release of InterSystems IRIS Data Platform, InterSystems IRIS for Health and HealthShare Health Connect, which are now Generally Available (GA) to our customers and partners.

Release Highlights

InterSystems IRIS Data Platform 2021.2 makes it even easier to develop, deploy and manage augmented applications and business processes that bridge data and application silos. It has many new capabilities including:

Enhancements for application and interface developers, including:

• Embedded Python 
• Interoperability Productions in Python
• Upda

Preview releases are now available for the 2021.2 version of InterSystems IRIS, IRIS for Health, and HealthShare Health Connect.

As this is a preview release, we are eager to learn from your experiences with this new release ahead of its General Availability release next month. Please share your feedback through the Developer Community so we can build a better product together.

 InterSystems IRIS Data Platform 2021.2 makes it even easier to develop, deploy and manage augmented applications and business processes that bridge data and application silos. It has many new capabilities including:

 Enha

GA releases are now published for the 2020.3 version of InterSystems IRIS, IRIS for Health, with IntegratedML!

This is the first InterSystems IRIS release that includes IntegratedML, a new feature that brings "best of breed" machine learning to analysts and developers via simple and intuitive SQL syntax. Developers can now easily train and deploy powerful predictive models from within IRIS, right where their data lives. Documentation for IntegratedML is available as a User Guide. Virtual Summit 2020 features a number of sessions and an Experience Lab featuring IntegratedML, see overview here.

Preview releases are now available for InterSystems IRIS Advanced Analytics, and InterSystems IRIS for Health Advanced Analytics! The Advanced Analytics add-on for InterSystems IRIS introduces IntegratedML as a key new feature.

The build number for these releases is: 2020.3.0AA.331.0

Full product installation kits, container images, and evaluation license keys are available via the WRC's preview download site.

Community Edition containers can also be pulled from the Docker store using the following commands:

• docker pull store/intersystems/iris-aa-community:2020.3.0AA.331.0
• docker pull

Greetings Developer Community!

InterSystems IntegratedML (formerly known as QuickML) is ready for external beta, and is looking for some users to kick the tires!

IntegratedML is an all-SQL machine learning (ML) feature in IRIS that:
    • Gives users the ability to create, train and deploy powerful models from simple SQL syntax
    • Wraps "best of breed" open source and proprietary ML and "automl" frameworks such as TensorFlow, XGBoost, H2O-3, and DataRobot
    • Focuses on ease of deployment, so you can add predictions to your application with a single SQL function call 

You are a good fit for