Agenda

Development to Inference with Private AI

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.

Get inspired by the Montevideo City Council’s commitment to transforming urban life and empowering over one million citizens with an AI. With Cloudera, a small team built a hybrid platform, data lakehouse and AI capabilities. The modern architecture liberates municipal data to fuel real-time analytics, surveillance-based AI models, and public-facing data applications. Learn how they utilized AWS to supercharge their AI model training while keeping their data foundation on-premises, focusing on governance and realizing measurable civic value at scale.

Enterprise AI demands more than powerful models and GPUs. It requires a data foundation that can continuously support analytics, retrieval, inference, and agentic AI without the complexity of fragmented storage and data movement.

In this session, learn how Cloudera and VAST Data combine enterprise data services with an AI-native data platform to create a unified foundation for AI.

We'll explore how organizations can maximize GPU utilization, reduce operational complexity, eliminate unnecessary data movement, improve AI infrastructure efficiency, reduce TCO and accelerate the journey from analytics to production AI.

Explore how the bank implemented a multi-agent AI framework to validate and accelerate hundreds of critical financial data flows running on Nifi.. Learn how the new AI solution replaced time-consuming, manual reviews with automated evaluations integrated directly into the NiFi ecosystem. Find out how the use of specialized AI agents reduced manual validation efforts by 99% to deliver significant gains in productivity, operational quality, and risk reduction. Hear how agentic AI on Nifi accelerates production use cases, eliminates errors, and establishes an automated foundation for growth.

Data Center to Edge with Full Control

The next frontier of data infrastructure is not just a lakehouse that stores more data — it is a lakehouse that understands more, heals itself, 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 structured data. Take a peek inside the agentic lakehouse — how AI-driven optimizations make your platform self-healing, self-tuning, and continuously performant. 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.

Discover how the State Tax Authority of Santa Catarina (SEF-SC) recovered millions in assets after consolidating billions of fragmented tax documents into a data lakehouse powered by Cloudera. By automating risk scoring across different data sources, SEF-SC reduced manual audit selection and equipped teams with self-service analytics. The new architecture helped deliver impressive returns, notably R$750 million in recovered tax credit and targeted audits in 2026 alone. Find out how else SEF-SC is driving operational efficiency and using data and AI to increase public revenue for health, education, and security.

Find out why realtime data capabilities were critical for Banco Galicia to redefine customer loyalty programs, and lead innovation in Argentina. With a Cloudera data lakehouse and realtime data-in-motion capabilities, the bank can now reward customer loyalty faster than ever before. This is a major competitive advantage in a changing economic environment. Find out what capabilities and best practices delivered operational efficiency and real results for both the bank and its customers.

Global AI investment is skyrocketing, yet enterprises worldwide are hitting a critical roadblock: the challenge of translating massive spend into measurable business value. To bridge this gap and win stakeholder trust, leadership must move past theoretical use cases and prove exactly how AI transformations will deliver holistic impact within their own unique business environments, constraints, and data ecosystems.

The strategic barriers to this realization are clear. Recent data shows that 47% of enterprises name poor data quality as their number one obstacle to AI value, while only 43% possess the necessary security, governance, and guardrails to manage it. This session explores how the strategic partnership between AWS and Cloudera addresses these foundational challenges head-on. We will discuss the executive blueprints required to overcome these barriers, mitigate governance risks, and build a trusted data foundation that turns AI investments into a predictable driver of enterprise growth and competitive advantage.

Deep Dive into Cloudera Technologies and its Open Source Foundations

This presentation explores how Data in Motion architectures can enable the continuous processing of large volumes of data with low latency and high scalability.

The adopted architecture, the integrated use of Kafka, Flink, and Iceberg, the main technical challenges of the implementation, and the volumes achieved during processing will be discussed.

For years, companies have built platforms to integrate, process, govern, and democratize their data. The next transformation happens when data moves beyond simply powering dashboards and models to guiding agents capable of executing business processes.

In this session, Lucas Araújo will explore how the Cloudera ecosystem can provide a trusted and distributed data foundation, while Semantix AI adds context, memory, policies, tools, and governance to transform corporate data into secure agentic execution.

This session will offer a practical perspective on the architecture required to take AI agents from experimentation to production in enterprise and regulated environments.

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, it’s imperative to close the loop between a user’s intent and actual work that leads to the desired outcome.

An agentic copilot experience, an intelligent layer embedded directly into your workflow, 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.

Discover how public safety agencies are transforming response to car theft with diverse datasets, including license plate images, and delivering auditable operational intelligence for law enforcement. Find out how advanced analytics on Cloudera helps identify stolen vehicles quickly, by automating the analysis of millions of camera records with vehicle recovery databases and other data sources.  Learn how the use case was developed and optimized to shift focus from simple event counts to actionable metrics for law enforcement. See how the new solution has optimized response times, informed camera placement and increased the true effectiveness of police technology.

Learn how Cloudera AI Inference Service can enable you to run LLMs on your own infrastructure, bringing the power of open-source models into fully private, on-premises and 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. But Private AI is only part of the picture. Experience how Cloudera's new AI Gateway gives you a single control plane to route requests to both private and public models, enforce policies, track usage, and manage costs — all without fragmenting your AI strategy.

This session shows how financial data moves from raw ingestion to governed, AI-ready consumption on an Iceberg-based lakehouse. Using a real-world finance scenario, we will show you how to transform data into trusted tables, enrich the data, validate its quality, and make the data usable for analytics, AI assistants, and responsible decisioning workflows.

Explore how to design and implement an agentic workflow from end to end. We will walk through a real use case, show how the agent creates its own to-do list and plans the work, keeps execution within guardrails, and leaves a complete audit trail along the way. Expect a hands-on, practical look at how governed AI agents actually come together.