![Parvinder Singh](/sites/default/files/author-portraits/parvinder_singh.png)



 

##### Parvinder Singh

Partner Solutions Architect

 ![AWS](/sites/default/files/feeds-images/img_184e0d4684878d04f59bc5947eef8c3e.png)



 

 

 ![Kijoon Lee](/sites/default/files/author-portraits/1216353530658891.nPm0w9YuRLvOBPF2j0kN_height640.png)



 

##### Kijoon Lee

VP of Strategic Alliances

 ![](/sites/default/files/logo-denodo-new.png)



 

 

 ![Suntosh Murthy](/sites/default/files/author-portraits/image%20%283%29%20%281%29.png)



 

##### Suntosh Murthy

Senior Partner Solutions Architect

 ![](/sites/default/files/logo-denodo-new.png)



 

 

 

 

Moving Generative AI from simple experiments to production-scale AI agents introduces major challenges for data teams: complex data pipeline delays, disconnected enterprise systems, and unpredictable cloud compute costs. To build autonomous agents that can accurately reason and take action, organizations need real-time data access across their core platforms without the risk and expense of constantly moving data.

Join AWS and Denodo for a practical deep dive into the data strategies required to scale advanced AI capabilities. We will showcase how to connect foundation models with your distributed enterprise data landscape using **Amazon Bedrock**, **Amazon Quick**, and the **Denodo Platform**.

Discover how a unified data layer delivers up to 10x faster performance, slashes operational expenses, and establishes the clear security boundaries needed to safely scale AI agents from pilot to enterprise reality.

**What You Will Learn**:

- **Live Data Access Across Enterprise Sources**: How to connect AI agents directly to core systems like SAP, Oracle, and OSIsoft PI to deliver real-time insights without the latency of traditional data copying.
- **Controlling AI Costs & Performance**: Practical strategies to maximize system performance and reduce recurring AI token expenses by delivering precision data directly to the model.
- **Enforcing Trusted Governance**: How to safely deploy autonomous workflows using dynamic data masking and access controls that protect corporate intellectual property and maintain compliance audit trails.
- **Use-Case Demonstration**: A look at an autonomous agent successfully connecting real-time operational layers, core business applications, and customer digital channels simultaneously.



 

 

 

  

 ![From AI Pilots to Enterprise Impact: Scaling Agentic AI with Denodo and AWS](/sites/default/files/WB-AWS-AgenticAi-2026-07-detailThumbnail.png)  Company Email\*  

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