Agenda

Moving sensitive data to public AI models is a costly, risky compromise. The true enterprise differentiator lies in scaling trusted, autonomous agents for complex workflows—without sacrificing privacy or succumbing to public cloud "token traps." Discover how Cloudera achieves sovereign AI by bringing high-performance AI directly to your data, whether in hybrid clouds, private infrastructure, or air-gapped data centers.

What You Will Learn:

• Private, Cost-Predictable Model Serving: Securely host models behind your firewall with Cloudera AI Inference service, lowering TCO compared to public APIs.
• Fast-Tracked Agentic Innovation: Rapidly scale autonomous workflows with low-code Cloudera Agent Studio, ensuring safe interaction with production systems.
• Centralized AI Governance: Manage, monitor, and route AI usage via a unified control plane that eliminates "shadow AI" and ensures strict compliance.

Join us to see how a data-to-AI strategy minimizes risk, lowers TCO, maximizes operational sovereignty, and accelerates production-grade enterprise intelligence.

The next frontier of data infrastructure is not just a lakehouse that stores more data — it is a platform that understands more, automates more, and federates context across every boundary to feed your agents. In this session, learn the three pillars of the intelligent lakehouse and how they work together to deliver a complete, governed, 360-degree context layer that makes AI agents more reliable.

With multimodal intelligence — you’ll see how to parse, extract, and vectorize unstructured data, and unify it with your business data. Take a peek inside the agentic lakehouse — how AI-driven optimizations make your platform continuously performant and always optimized for costs. And finally, learn how Apache Iceberg, Trino, and our connectors with Salesforce, ServiceNow, and SAP power true interoperability and federated access for context 360. Discover data anywhere, access data from anywhere, share data products, and power your agents anywhere in the cloud, at the edge, or even on premises, giving you complete freedom to choose the architectures, tools, models, and applications that fit your business today and in the future.

Industrial plant data is often trapped behind costly legacy historians, expensive cloud streaming fees, and unmapped sensor tags. In this 15-minute talk, we will showcase how Cloudera can bridge the gap between plant-floor OT and enterprise AI. We will cover how MQTT Sparkplug B and Cloudera Data in Motion instantly add context to sensor telemetry, strip out noise, and route data to an open lakehouse. You'll see how real-time edge streaming combined with AI agents enables sub-second anomaly detection and human in the loop maintenance actions—all without compromising SCADA safety or relying on cloud connectivity.

Enterprise AI success starts with the right foundation—not just the right model. As organizations scale from AI pilots to production agents, they need to transform enterprise data into trusted intelligence while running AI wherever their data resides.

Join Cloudera and NVIDIA to learn how hybrid data platforms, accelerated data processing, open models, and NVIDIA AI software come together to power secure, scalable agentic AI. Learn how an optimized AI stack - from data and models to CPUs, GPUs, networking, and secure computing - enables enterprise to build and scale intelligent agents across on-premises and cloud environments.

Gain inspiration and insights into how leading organizations are building the foundation for the next generation of enterprise AI.

The Directorate General of Digital Health has implemented one of the largest healthcare Data Lakehouses in Europe, leveraging Cloudera technology and CGM services.

This session will showcase the ecosystem of custom-built tools and AI agents developed to optimize services for healthcare professionals, researchers, and administrators within the Madrid Health Service (SERMAS), as well as to automate, scale, and manage the healthcare Data Lakehouse. Key capabilities include:

Data Management and Governance Tools: Healthcare data catalog, data growth analysis, auditing and data quality, process performance and planning monitoring, and infrastructure health monitoring.

Artificial Intelligence and Assistance: The interactive Chat OGD agent for support and information queries.

The second part of the session will focus on the strategic evolution of the platform, outlining the roadmap for adapting the Data Lakehouse to support and align with the standards of the European Health Data Space (EHDS).

This session explores how achieve ultimate architectural freedom with Cloudera’s breakthrough hybrid cloud innovations. Learn how to power seamless workload mobility via Compute Bursting, secure data mobility with Replication Manager, and fine-grained security through Ranger Remote Authorization Service (RAZ) and the Iceberg REST Catalog.  Experience secure, flexible deployments across any environment.

Deriving real value from your data estate -- from acquiring and preparing data to actively extracting insights -- remains a painstaking hurdle. Because basic chat tools fall short of handling this complexity, we must close the loop between a user’s intent and actual work that leads to the desired outcome. This talk unveils our new agentic copilot experience, an intelligent layer embedded directly into your workflow that brings together specialized agents, business context, and fit-for-purpose compute engines. Whether you are a pipeline builder, business analyst, or operator, learn how to be more productive and get to results faster.

As enterprises move beyond AI experimentation, the challenge shifts to deploying and operating models reliably at scale — while keeping data private and costs predictable. In this session, we'll explore how Cloudera AI Inference Service enables organizations to run LLMs on their own infrastructure, bringing the power of open-source models into fully private, on-premises or cloud environments without ever sending sensitive data to a third party. You'll see how Cloudera handles the operational complexity — from model serving and autoscaling to observability — so your teams can focus on building Agents, not managing infrastructure.