ModelOp Extends Automation and Governance for AI and Machine Learning Models
Anurag Khadkikar | April 30, 2021
ModelOp, the pioneer of ModelOps software for large enterprises, today announced significant updates to the ModelOp Center platform, expanding automation for governing and tracking artificial intelligence (AI) and machine learning (ML) models, making it simpler and quicker to efficiently deploy models and recognize the business benefit and revenue contribution.
“Enterprises have made significant investments in their existing IT and governance processes and systems. “It is critical to integrate with these processes and systems to bring models into business quicker and ensure they continue to achieve desired business outcomes,” says Dave Trier, Vice President of Product at ModelOp. “Integration of existing systems eliminates technological and workflow redundancy and enables enterprises to capitalize on the significant investments they have already made in their data and analytics platforms, infrastructure, stores, and security systems.”
In the State of ModelOps 2021 Report, respondents identified a lack of integration with existing systems and applications as the most challenging barrier to operationalizing models. New capabilities included in the ModelOp Center upgrade include:
• Snowflake, SQL Server, PostgreSQL, IBM DB2, Spark, and HDFS integration enables direct data consumption from these commonly used data sources. ModelOp Center employs an abstraction layer that enables models to connect to a wide range of data sources and model execution sites for batch and online business use cases.
• Integration with Vericode allows automatic code scanning for assurance of code completeness for and every model when implemented.
• Integration with Vault provides unified access control to models and the applications, data sources, and systems with which they interact during their operational life.
• An improved user interfaces with guided task lists, allowing a wider range of users with varying levels of expertise to conveniently track and govern models during their operating existence.
If enterprises increase their use of AI models, they quickly understand that ModelOps automation is needed to scale and develop their AI efforts. According to Gartner, more than half of AI models are never completely deployed due to insufficient model operational processes.
ModelOp Center solves this problem by automating the governance, tracking, and orchestration of post-development AI/ML models across platforms and teams, lowering costs and business risks, and speeding time to production.
A comprehensive process library, customized metadata, and reporting models will reduce time to operationalization by up to 50%. Customers can benefit from real-time tracking and integration of development platforms, data sources, IT systems, Model Risk Management systems, and enterprise apps to simplify and scale AI and ML models, reducing costs by up to 30%.
ModelOp, the ModelOps software leader, enables large enterprises to solve the crucial governance and scale complexities required to fully achieve the transformative potential of enterprise AI and Machine Learning investments. G2000 companies use ModelOp Center, which is at the heart of every AI orchestration platform, to govern, track, and orchestrate models around the enterprise and deliver reliable, compliant, and scalable AI initiatives.