In the Media

Denodo, a leader in data management, announced new product integrations to support the building and scaling of agentic AI across hybrid and multi-cloud environments supporting customers across financial services, healthcare and life sciences, manufacturing, retail, public sector and others.

Denodo announced new product integrations to support the building and scaling of agentic AI across hybrid and multi-cloud environments, supporting customers across financial services, healthcare and life sciences, manufacturing, retail, public sector and others.

There is a pattern that keeps repeating itself across enterprise AI projects. A company invests in a capable model, deploys it with reasonable expectations, and then watches it underperform in production. Not because the model is weak. Because the data feeding it is stale, incomplete, or contextually meaningless to the system trying to use it. Denodo’s new integrations with AWS are a direct response to that pattern, extending its data management platform into the infrastructure layer where agentic AI actually breaks down.

Denodo has announced new integrations with Amazon Web Services (AWS) aimed at supporting the development and scaling of agentic AI across hybrid and multi-cloud environments. This targets customers in sectors including financial services, healthcare, life sciences, manufacturing, retail, and the public sector.

Denodo has introduced new integrations with Amazon Web Services for agentic AI, covering Amazon SageMaker, Amazon Bedrock AgentCore and Amazon Quick. The additions are intended to help businesses give AI agents access to live, governed data across on-premises, software-as-a-service and multi-cloud systems. They address a common problem in enterprise AI projects, where agents produce weak results because they rely on incomplete, outdated or poorly controlled information.

Denodo, a leader in data management, has announced new product integrations to support the building and scaling of agentic AI across hybrid and multi-cloud environments supporting customers across financial services, healthcare and life sciences, manufacturing, retail, public sector and others.

Executive Editor Tim King discusses why universal semantic layers are evolving beyond BI and analytics to become the governance, interpretation, and control layer for enterprise AI. This look at semantic architecture is brought to you by Denodo. 

Enterprise AI adoption is accelerating quickly, but it’s clear organizations continue to struggle with what some leaders now describe as the “AI trust gap.” As AI become more deeply embedded into operational workflows, enterprises are discovering that access to data alone is not enough to ensure reliable outcomes, especially as AI requires consistent interpretation, governed access, and trusted context across increasingly distributed environments.

At CDO Magazine’s exclusive Roundtable Exchange at Sequoia DC on May 13, senior federal and enterprise data, analytics, and AI leaders from across the Washington, DC, Maryland, and Virginia region came together for a thought-provoking discussion on “Hype vs. Reality: What’s Actually Working in Data, Security, and AI Right Now.”

In this conversation, we spoke with Inessa Gerber, Director of Product Management at Denodo, about the data layer behind autonomous finance, why semantic abstraction matters more than raw infrastructure in enterprise AI, and what must change before agentic systems can reliably operate on live financial data.

L’intelligenza artificiale può essere una “compagna di viaggio”, verso un futuro in cui l’accesso ai dati sarà più democratico. Ce ne parla Andrea Zinno, partner & channel sales director Emea South di Denodo.