Oracle AI Experience Sessions
Developing Agentic AI Apps and Workflows
Build and deploy production-ready AI applications and agents through hands-on engineering workshops focused on AI data foundations, scalable inference, and intelligent orchestration. Using Python, Oracle AI Database, and Oracle Cloud Infrastructure (OCI) Enterprise AI, you’ll implement retrieval-augmented generation (RAG) pipelines, agent workflows, vector search, multimodal retrieval, persistent memory, and hybrid inference architectures with runnable code throughout. Explore practical patterns for optimizing AI performance, reasoning, and cost while building scalable applications that combine enterprise data, AI models, and adaptive agent behavior.
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AI Builders Track
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Launch Context-Aware AI Applications with Oracle AI Database
In this lab, you’ll use Oracle AI Database to power GenAI applications with enterprise data.
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Unify the Data Layer with Oracle Autonomous AI Lakehouse
This workshop highlights the process of building an object store–centric data lake with Oracle Autonomous AI Lakehouse.
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Assemble and Deploy an AI Agent Using RAG and SQL
Learn how to build and deploy an AI agent using retrieval-augmented generation (RAG) and SQL integration on Oracle AI Data Platform.
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Data Fundamentals for AI Application Development
This workshop introduces data and database concepts that underpin modern AI applications, and why they matter.
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Building AI Agents with Python, RAG, and LangChain
Building on the first session, this workshop focuses on implementing a production-style RAG pipeline and evolving it into an agentic application.
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Implement Persistent State, Recall, and Adaptive Reasoning
Building on the previous session, this hands-on workshop shows how to implement agent memory as a first-class capability end to end on Oracle AI Database.
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Deploy a Fleet Vehicle Route Optimization Application with NVIDIA cuOpt on OCI
Modern supply chains operate under constant pressure from fluctuating demand, volatile costs, and constrained capacity.
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Build an Enterprise Data Chat Agent with NVIDIA AI-Q Blueprint on OCI
In this hands-on workshop, you’ll deploy NVIDIA GPU workloads on Oracle Kubernetes Engine (OKE) in OCI and build an enterprise data agent using the NVIDIA AI-Q Blueprint.
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OCI Optimize AI Workloads with Intelligent Model Selection (OCI Enterprise AI)
As AI applications move into production, optimizing cost, latency, and response quality becomes just as important as building them.
Launch Context-Aware AI Applications with Oracle AI Database
In this lab, you’ll use Oracle AI Database to power GenAI applications with enterprise data. You’ll interact with a live business application that uses several data sources, vectorizes structured and unstructured data, plus learn how RAG applications enhance context-specific information. You’ll have a working application that blends transactional data with AI services, showing how enterprises can embed GenAI directly into mission-critical processes.
Unify the Data Layer with Oracle Autonomous AI Lakehouse
This workshop highlights the process of building an object store–centric data lake with Oracle Autonomous AI Lakehouse. In this hands-on lab, you’ll access an embedded toolset to integrate, transform, and share data efficiently, helping AI models use high-quality data to generate better insights.
Assemble and Deploy an AI Agent Using RAG and SQL
Learn how to build and deploy an AI agent using retrieval-augmented generation (RAG) and SQL integration on Oracle AI Data Platform. You’ll interact with large language models, enterprise documents, and relational databases to answer natural language queries with contextual accuracy. The session covers document ingestion, vector search, SQL querying, and deployment best practices, providing a hands-on experience creating intelligent, enterprise-ready AI applications.
Data Fundamentals for AI Application Development
This workshop introduces data and database concepts that underpin modern AI applications, and why they matter. We pay particular attention to the convergence of JSON, graph, time series, and vector data, alongside an intro to similarity functions, vector search, and more. The hands-on labs tie these concepts directly to higher-level patterns in later workshops, such as Retrieval-Augmented Generation (RAG) and agentic systems, making this session ideal for developers building production-ready applications.
Building AI Agents with Python, RAG, and LangChain
Building on the first session, this workshop focuses on implementing a production-style RAG pipeline and evolving it into an agentic application. Using LangChain and Python, developers work through hands-on labs covering data ingestion, vector search, retrieval, and response generation, then extend into agent workflows, all backed by Oracle AI Database as the system of record and memory core. All implementation is done in Python, giving you practical, runnable code throughout. The emphasis is on practical patterns you'll actually use.
Implement Persistent State, Recall, and Adaptive Reasoning
Building on the previous session, this hands-on workshop shows how to implement agent memory as a first-class capability end to end on Oracle AI Database. You'll implement episodic memory (per-asset threads and per-finding records), semantic memory (auto-extracted facts, preferences, and a queryable asset registry), and procedural memory (operating guidelines distilled from inspection narratives), all assembled into bounded working memory via on-demand context cards. Using the oracleagentmemory Python SDK and a minimal Python harness, you'll build a city-operations inspection copilot with persistent state, cross-inspector recall, and patterns that sharpen as the history grows — covering running-summary compaction, bounded context cards, and hybrid retrieval, with runnable code and production-ready patterns.
Deploy a Fleet Vehicle Route Optimization Application with NVIDIA cuOpt on OCI
Modern supply chains operate under constant pressure from fluctuating demand, volatile costs, and constrained capacity. In this hands-on workshop, explore how NVIDIA cuOpt on OCI powers real-world logistics use cases and learn how OCI Accelerator Packs can help jump-start your AI development. Participants will discover OCI Accelerator Packs, then customize key integration points to fit the needs of a vehicle route optimization application. Teams will leave with a repeatable path to move from idea to running AI workloads in minutes. (Products Used: AI Acceleration Pack (Vehicle Route Optimization))
Build an Enterprise Data Chat Agent with NVIDIA AI-Q Blueprint on OCI
In this hands-on workshop, you’ll deploy NVIDIA GPU workloads on Oracle Kubernetes Engine (OKE) in OCI and build an enterprise data agent using the NVIDIA AI-Q Blueprint. Learn how to connect enterprise knowledge sources, extract multimodal data, and create a developer-friendly workflow for retrieval, reasoning, and cited answers. You’ll also explore architecture patterns relevant to sovereign AI and dedicated cloud environments, where organizations need greater control over data, infrastructure, and AI deployment models. Leave with a practical NVIDIA blueprint you can adapt for enterprise data chat, research, and knowledge discovery use cases. (Products used: OKE, NVIDIA AI Blueprint)
OCI Optimize AI Workloads with Intelligent Model Selection (OCI Enterprise AI)
As AI applications move into production, optimizing cost, latency, and response quality becomes just as important as building them. In this hands-on workshop, you’ll build a customer support assistant using OCI Enterprise AI and implement model routing patterns that direct requests to the most appropriate AI model based on task complexity. You’ll ground responses with enterprise knowledge sources, connect Oracle Autonomous AI Database using NL2SQL and the ADB MCP Server, deploy a Streamlit chat application, and apply OCI AI Guardrails for prompt injection detection. Leave with a working AI assistant and a practical approach for scaling AI applications efficiently while optimizing cost, performance, and model choice.
AI Business Applications Track
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Design, Deploy, and Execute with Agentic AI in Oracle Fusion Agentic Applications
Learn how to design, deploy, and execute AI agents within Oracle Fusion Cloud Applications using Oracle’s agentic applications framework.
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Automate Tasks, Drive Efficiency, and Improve Decision-Making with Agentic AI
Experience firsthand AI agents embedded across Oracle Cloud Applications.
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Talking to Your Data with GenAI in Oracle Cloud Applications
Discover how to engage with business data using natural language.
Design, Deploy, and Execute with Agentic AI in Oracle Fusion Agentic Applications
Learn how to design, deploy, and execute AI agents within Oracle Fusion Cloud Applications using Oracle’s agentic applications framework. In this hands-on lab, participants will build workflows that reason across enterprise data, orchestrate business processes, and take contextual actions with governance and human oversight. Attendees will also experience the new agentic application user view, where AI agents continuously execute and collaborate across workflows to help run the business.
Automate Tasks, Drive Efficiency, and Improve Decision-Making with Agentic AI
Experience firsthand AI agents embedded across Oracle Cloud Applications. This interactive lab will demonstrate how these agents can automate routine tasks, simplify workflows, and improve decision-making for HR, finance, supply chain, and customer experience teams—helping drive greater productivity and efficiency. Learn how to apply these tools in your business and discover how they can enhance user experiences through personalized and timely interactions for employees and managers.
Talking to Your Data with GenAI in Oracle Cloud Applications
Discover how to engage with business data using natural language. This lab will demonstrate how to use generative AI capabilities in Oracle Cloud Applications and Oracle Fusion Data Intelligence to ask complex questions and receive actionable insights. You’ll use the AI agent approach introduced in the keynote session, interacting with data to deliver a business operations solution. Through guided exercises, you’ll see how GenAI helps users analyze information more intuitively, make data-driven decisions faster, and uncover insights within enterprise data.
AI Strategy Track
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Moderated Executive Roundtables
Connect with peers and industry leaders to explore how organizations are deploying AI across business and technology functions.
Moderated Executive Roundtables
Connect with peers and industry leaders to explore how organizations are deploying AI across business and technology functions. Through executive roundtables and customer-led discussions, you’ll exchange insights on ERP, supply chain management, and AI data platform strategies while examining real-world approaches to governance, security, and scalable AI adoption. Hear customer case studies focused on measurable business outcomes, including supply chain improvements, data management updates, and ROI. Designed for business stakeholders and decision-makers, this track emphasizes practical lessons, peer networking, and guidance for accelerating enterprise AI initiatives.
Closing and trial export
We’ll close the day by summarizing key takeaways and sharing resources to help you continue your AI journey with Oracle. Participants will receive access to trial environments, labs, and documentation to extend hands-on learning beyond the event. This session will leave you equipped with the knowledge and tools to bring AI into use within your organization.
AI Partner Enablement Track
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Capturing the AI Opportunity with Oracle
See how Oracle partners can help customers put AI to work today using embedded AI services, agentic AI capabilities, and AI development platforms across OCI, Oracle Fusion Cloud Applications, and Oracle AI Database.
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Building the AI Use Case and Understanding the Economic Model
This session explores how to identify high-value AI opportunities and connect them to measurable business outcomes.
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Assemble and Deploy an AI Agent Using RAG and SQL
Learn how to build and deploy an AI agent using retrieval-augmented generation (RAG) and SQL integration on Oracle AI Data Platform.
Capturing the AI Opportunity with Oracle
See how Oracle partners can help customers put AI to work today using embedded AI services, agentic AI capabilities, and AI development platforms across Oracle Fusion Cloud Applications, Oracle Cloud Infrastructure (OCI), and Oracle AI Database. This session highlights where partners can create immediate value through implementation, integration, extension, and industry solutions built on Oracle’s growing AI portfolio.
Building the AI Use Case and Understanding the Economic Model
This session explores how to identify high-value AI opportunities and connect them to measurable business outcomes. The discussion will focus on building practical AI use cases, estimating business impact, and understanding the economic model behind AI projects, including implementation costs, operational efficiency, productivity gains, and long-term customer value across Oracle AI solutions and services.
Assemble and Deploy an AI Agent Using RAG and SQL
Learn how to build and deploy an AI agent using retrieval-augmented generation (RAG) and SQL integration on Oracle AI Data Platform. You’ll interact with large language models, enterprise documents, and relational databases to answer natural language queries with contextual accuracy. The session covers document ingestion, vector search, SQL querying, and deployment best practices, providing a hands-on experience creating intelligent, enterprise-ready AI applications.
