We’re delighted to be recognized again by Gartner in their recent report. Enterprises are experiencing significant challenges getting their models out of the lab and into production and keeping them there with full visibility, accountability to the business with risk controls. Stu Bailey, ModelOp
CHICAGO (PRWEB) May 18, 2021
ModelOp, the pioneer of ModelOps software for enterprises, has been named in the "Where are They Now?" section of Gartner “Cool Vendors in AI Operationalization and Engineering 2021” report. The report notes that "one of the major roadblocks that clients face when it comes to value realization of AI projects — putting AI models into production".
ModelOp was the first company to develop and release a ModelOps platform for operationalizing all types of models regardless of where and how they're created and where they execute. The Cool Vendor report comes at a time of growing momentum for ModelOp and ModelOps:
- In April, Independent Research Firm Corinium Intelligence published the results of the first-ever State of ModelOps survey, with responses from 100 AI-focused executives from top global financial services companies in North America and Europe, including Charles Schwab, Citigroup, Morgan Stanley, American Express and JPMorgan Chase.
- The recently held ModelOps Summit featured a keynote presentation from Erick Brethenoux, VP Analyst and AI Research Agenda Lead, Gartner, and panel discussions featuring executives from Ally Bank, Charles Schwab, New York Life, Regions, KPMG, BNY Mellon, and more.
ModelOp Center software takes the models developed in Data Science and Machine Learning (DSML) Platforms - so-called Model factories - and delivers them into the production with full visibility, control and accountability. This gives Enterprise AI Architects and the entire organization a centralized view of all models in production. The ModelOp Center integrates with the full Enterprise Stack, including runtime environments (on prem and cloud), CICD tools (e.g. Github), Data Science & Machine Learning tools (e.g.: AWS SageMaker), ticketing systems (e.g. ServiceNow, Jira), business intelligence tools (e.g. Tableau), and others so that data scientists, software developers, DataOps, DevOps, ITOps, risk and compliance teams - as well as the business unit leaders - have full visibility and accountability to performance against technical, operational, business and compliance metrics, all from within their existing tools and without the need to monitor separate AI Operationalization dashboards.
ModelOp has focused on the challenges of operationalizing models since its inception. ModelOp was named as a Cool Vendor in Gartner "Cool Vendors in Data Science, 2014".
"We're delighted to be recognized again by Gartner in their recent report," said Stu Bailey, co-founder and chief enterprise AI architect at ModelOp. Bailey continued, "Large non-digital native enterprises are experiencing significant challenges getting their models out of the lab and into production and keeping them there with full visibility, accountability to the business and compliance with risk controls. As a ModelOps pioneer, we're excited by the explosion of interest and investment that organizations are making in this critical capability for AI-driven enterprises."
The complete “Cool Vendors in Enterprise AI Operationalization and Engineering 2021” report can be accessed here.
For additional information:
- Read the ModelOps guide, 4 Steps to Successful Model Operations
- Download the State of ModelOps 2021 Report
- Learn more about ModelOp Center
About ModelOp:
ModelOp, the pioneer of ModelOps software, enables enterprises to address the critical governance and scale challenges necessary to fully unlock the transformational value of enterprise AI and Machine Learning investments. Core to any AI orchestration platform, G2000 companies use ModelOp Center to govern, monitor and orchestrate models across the enterprise and deliver reliable, compliant and scalable AI initiatives.
Gartner Disclaimer: Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s Research & Advisory organization and should not be construed as statements of fact. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Gartner, Cool Vendors in Enterprise AI Operationalization and Engineering, 27 April 2021, Arun Chandrasekaran, Farhan Choudhary, Georgia O'Callaghan, Soyeb Barot, Robert Thanaraj, Chirag Dekate, Erick Brethenoux
Gartner, Cool Vendors in Data Science, 2014, 23 April 2014, Lisa Kart, Neil Chandler, Alexander Linden, Rita Sallam