New capabilities simplify the AI model deployment journey and ensure trusted AI

Teradata announced new enhancements to its leading AI/ML (artificial intelligence/machine learning) model management software in ClearScape Analytics (e.g., ModelOps) to meet the growing demand from organizations across the globe for advanced analytics and AI. These new features – including “no code” capabilities, as well as robust new governance and AI “explainability” controls – enable businesses to accelerate, scale, and optimize AI/ML deployments to quickly generate business value from their AI investments.

Deploying AI models into production is notoriously challenging. A recent O’Reilly’s survey on AI adoption in the enterprise found that only 26% of respondents currently have models deployed in production, with many companies stating they have yet to see a return on their AI investments. This is compounded by the recent excitement around generative AI and the pressure many executives are under to implement it within their organization, according to a recent survey by IDC, sponsored by Teradata.

ModelOps in ClearScape Analytics makes it easier than ever to operationalize AI investments by addressing many of the key challenges that arise when moving from model development to deployment in production: end-to-end model lifecycle management, automated deployment, governance for trusted AI, and model monitoring. The governed ModelOps capability is designed to supply the framework to manage, deploy, monitor, and maintain analytic outcomes. It includes capabilities like auditing datasets, code tracking, model approval workflows, monitoring model performance, and alerting when models are not performing well.

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“We stand on the precipice of a new AI-driven era, which promises to usher in frontiers of creativity, productivity, and innovation. Teradata is uniquely positioned to help businesses take advantage of advanced analytics, AI, and especially generative AI, to solve the most complex challenges and create massive enterprise business value,” said Hillary Ashton, Chief Product Officer at Teradata. “We offer the most complete cloud analytics and data platform for AI. And with our enhanced ModelOps capabilities, we are enabling organizations to cost effectively operationalize and scale trusted AI through robust governance and automated lifecycle management, while encouraging rapid AI innovation via our open and connected ecosystem. Teradata is also the most cost-effective, with proven performance and flexibility to innovate faster, enrich customer experiences, and deliver value.”

New capabilities and enhancements to ModelOps include:

• Bring Your Own Model (BYOM), now with no code capabilities, allows users to deploy their own machine learning models without writing any code, simplifying the deployment journey with automated validation, deployment and monitoring
• Mitigation of regulatory risks with advanced model governance capabilities and robust explainability controls to ensure trusted AI
• Automatic monitoring of model performance and data drift with zero configuration alerts

Teradata customers are already using ModelOps to accelerate time-to-value for their AI investments.

• A major U.S. healthcare institution uses ModelOps to speed up the deployment process and scale its AI/ML personalization journey. The institution accelerated its deployment with a 3X increase in productivity to successfully deploy thirty AI/ML models that predict which of its patients are most likely to need an office visit to implement “Personalization at Scale.”
• A major European financial institution leveraged ModelOps to reduce AI model deployment time from five months to one week. The models are deployed at scale and integrated with operational data to deliver business value.

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