KNIME and Zementis Announce Strategic Partnership

Share Article

Leading software providers deliver powerful, cost-effective, end-to-end solution to enable data mining, predictive modeling, and production deployment of statistical models based on open standards and cloud computing.

Zementis, Inc., a leading provider of predictive analytics solutions, and GmbH, a software company focused on workflow tools for data mining, today announced a strategic partnership to deliver standards-based solutions across the data mining industry.

Zementis and KNIME are avid supporters of open standards. As the "lingua franca" for data mining and predictive analytics, both companies provide extensive support for the Predictive Model Markup Language (PMML) standard. The PMML standard continues to gain momentum, giving users a true option to exchange models between various software applications.

The KNIME platform provides a modular pipeline to visually create data flows, analyze and build predictive models, while the Zementis ADAPA scoring engine solves the last mile to deployment, integration, and scalable execution for such models in a typical IT production environment. Models created seamlessly in KNIME are readily deployed in Zementis ADAPA via PMML, adding a quantum leap in business agility, significantly reducing the total cost of ownership (TCO) for predictive analytics and increasing their value to the enterprise.

"A true SaaS offering, the ADAPA Predictive Analytics Edition on the Amazon Elastic Compute Cloud (Amazon EC2) requires zero client install and provides a pay-as-you-go option, eliminating need for the upfront investments in hardware or software licenses," said Dr. Michael Zeller, CEO of Zementis. "We are delighted to partner with KNIME to further embrace open standards and the synergies with the KNIME open-source workflow platform."

"We welcome our new partnership with Zementis because it fits perfectly with our overall strategy," said Prof. Michael Berthold, CEO of "Zementis' adaptive decision technology will be a great complement to our product pipeline by adding an additional way to streamline the integration of KNIME into enterprise IT infrastructure. Being able to deploy predictive models fits in nicely with our grid support, server infrastructure and reporting toolkits."

Extending over and above product and technology synergies, the strategic partnership also complements the presence of both companies in the United States, Europe, and Asia.

Zementis, Inc. is a software company focused on predictive analytics and advanced Enterprise Decision Management technology. We combine science and software to create superior business and industrial solutions for our clients. Our scientific expertise includes statistical algorithms, machine learning, neural networks, and intelligent systems and our scientists have a proven record in producing effective predictive models to extract hidden patterns from a variety of data types. It is complemented by our product offering ADAPA®, a decision engine framework for real-time execution of predictive models and rules. For more information please visit

David DeVol
Zementis, Inc.
619.330.0780 x 1008
info (at) zementis (dot) com

ABOUT GmbH provides commercial enterprise solutions and services around the open-source platform KNIME. The modular data exploration platform, initially developed at the University of Konstanz, Germany, enables the user to visually create data flows - or pipelines, execute selected analysis steps, and later investigate the results through interactive views on data and models. Our product pipeline includes a KNIME Enterprise Server, grid support, reporting solutions, and commercially-supported KNIME distributions for typical requirements in business environments. We also offer services such as support for KNIME, data analysis, hands-on training and the development of customized components for KNIME. Please see for more information.

Fabian Dill GmbH
Technoparkstr. 1
8005 Zurich, Switzerland
Fabian.Dill (at) knime (dot) org


Share article on social media or email:

View article via:

Pdf Print

Contact Author

David D. Devol

Wendy Cheung
Visit website