Denodo Expands AWS Integration Portfolio for Enterprise GenAI Workloads
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.
The company said enterprises moving from AI experimentation to production are running into consistent data-related issues. According to Denodo, “AI agents fail to deliver reliable outcomes when they lack real-time awareness, operate on incomplete or incorrect data, or act outside governance and compliance boundaries.” The company argues these limitations are not caused by AI models themselves, but by underlying data architecture and governance.
To address this, Denodo is integrating its data management platform with AWS services including Amazon SageMaker, Amazon Bedrock AgentCore, and Amazon QuickSight. The goal is to extend access to operational and analytical data across on-premises systems, SaaS platforms, and multiple cloud environments, without physically moving the data. Denodo describes this as a “logical data foundation” designed to provide real-time, governed, business-contextual data for AI systems.
A key part of the integration is with Amazon Bedrock AgentCore, which Denodo says enables AI agents to securely access enterprise data at scale. In this setup, Denodo defines what data is available, enriches it with semantic context through its data layer, and applies governance policies, while AgentCore manages authentication, routing, and access control.
Denodo said the combined approach is intended to ensure AI agents “operate within business rules while delivering reliable, high-quality business outcomes at scale,” particularly in distributed data environments. Denodo is also extending its platform alongside Amazon SageMaker to provide what it calls “live, zero-copy access” to enterprise data across hybrid and multi-cloud systems. The integration includes connections to more than 200 enterprise systems, including SAP, Oracle, and Salesforce.
The company is also integrating with Amazon SageMaker Catalog to add business metadata and context to data used by AI agents. According to Denodo, this ensures that “data accessed across both AWS services and non-AWS environments is consistently understood and aligned with business meaning.” Denodo added that it applies governance controls such as attribute-based access control, dynamic data masking, and data lineage tracking, which work alongside SageMaker’s native controls.
Denodo’s integration with Amazon QuickSight is positioned around reducing the gap between analytics and execution. By combining QuickSight with Denodo’s real-time data access layer, the company says users can build AI-driven workflows and automated processes using current enterprise data without needing to replicate or move datasets. The aim, according to Denodo, is to shorten the time required to develop and deploy AI-enabled workflows and improve decision-making speed across business functions.
“Agentic AI requires more than powerful models. It requires trusted, real-time, and well-governed data,” said Suresh Chandrasekaran, Executive Vice President at Denodo. “Our collaboration with AWS focuses on delivering a unified data foundation that enables organizations to scale AI agents with confidence across the entire data landscape.”
Denodo said the combined approach with AWS is intended to help organizations move from AI pilots to production systems with governance and control in place. The company’s platform is available through AWS Marketplace, where customers can access trial and procurement options, including private offers and alignment with AWS Private Pricing Agreements.
