Skip to content
Search to learn about InterSystems products and solutions, career opportunities, and more.

InterSystems Introduces QuickML™ to add machine learning to applications directly from SQL  

With new enhancement for InterSystems IRIS™ Data Platform, application developers can now easily add automation and predictions to applications without being experts

CAMBRIDGE, Mass., September 23, 2019InterSystems, a global leader in information technology platforms for health, business, and government applications, today launched QuickML™, available to users of the InterSystems IRIS Data Platform™ and the InterSystems IRIS for Health™ Data Platform. The announcement was made at InterSystems Global Summit 2019, the company’s annual conference, which is currently being held in Boston. By putting best-of-breed machine learning (ML) within the hands of SQL-oriented developers, QuickML enables organizations to put predictions within their existing applications without needing extremely-scarce ML expert engineers.

Data is at the core of most business processes, and ML offers amazing power for digital transformation — but the economics of extracting value from this resource are challenging. Development teams are increasingly required to build ML capabilities into data-intensive solutions, but very few of them have the internal resources or necessary expertise to effectively apply such functionality. QuickML solves this issue through an automated ML function available within a familiar all-SQL syntax. QuickML simplifies the process of building, testing, and deploying ML models and speeds the process of integrating them into production applications.

“QuickML allows all developers using InterSystems IRIS to embed machine learning capabilities in their applications in a simple and scalable format. In this way, we see QuickML enabling all of our application partners to deliver accurate predictions as part of their tool set.” said Scott Gnau, vice president of Data Platforms at InterSystems. “The InterSystems IRIS Data Platform powers some of the most important applications on the planet, and QuickML completes the data science suite of functionality. Used in conjunction with our Spark Connector and Predictive Model Markup Language (PMML) runtime engine, data scientists and developers have a suite of tools that serve well in high-performance, large-scale data-centric deployments.”

QuickML will be available in a forthcoming InterSystems IRIS release as a native ML capability. For more information, please visit https://www.intersystems.com/products/intersystems-iris/.

About InterSystems

InterSystems is the information engine that powers some of the world’s most important applications. In healthcare, business, government, and other sectors where lives and livelihoods are at stake, InterSystems has been a strategic technology provider since 1978. InterSystems is a privately held company headquartered in Cambridge, Massachusetts (USA), with offices worldwide, and its software products are used daily by millions of people in more than 80 countries. For more information, please visit https://www.intersystems.com/.

InterSystems PR Contact: Nick Brown
InkHouse PR
intersystems@inkhouse.com
781-966-8390

RELATED TOPICS

Latest News About InterSystems

Take The Next Step

We’d love to talk. Fill in some details and we’ll be in touch.
*Required Fields
Highlighted fields are required
*Required Fields
Highlighted fields are required

By submitting your business contact information to InterSystems through this form, you acknowledge and agree that InterSystems may process this information, for the purpose of fulfilling your submission, through a system hosted in the United States, but maintained consistent with any applicable data protection laws.



** By selecting yes, you give consent to be contacted for news, updates and other marketing purposes related to existing and future InterSystems products and events. In addition, you consent to your business contact information being entered into our CRM solution that is hosted in the United States, but maintained consistent with applicable data protection laws.