Oracle AI Experience Sessions

AI Builders Track - Foundation

  • 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.

  • 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.

  • Assemble and Deploy an AI Agent Using RAG and SQL (AI Data Platform)

    Learn how to build and deploy an AI agent using retrieval-augmented generation (RAG) and SQL integration on Oracle AI Data Platform.

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 (AI Data Platform)

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.

AI Builders Track - Advanced

  • Building AI Agents with Python, RAG, and LangChain

    This workshop focuses on implementing a production-style RAG pipeline and evolving it into an agentic application.

  • 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.

  • 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.

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.

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

  • 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.

  • Automate Tasks, Drive Efficiency, and Improve Decision-Making with Agentic AI

    Experience firsthand AI agents embedded across Oracle Cloud Applications.

  • AI Powered Analytics with Oracle Fusion Data Intelligence

    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.

AI Powered Analytics with Oracle Fusion Data Intelligence

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

  • 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.