Build more capable and reliable AI systems by combining context-aware retrieval-augmented generation (RAG) with agentic decision-making in an enterprise AI platform, all in Java! This session covers everything from architecture, context construction, and model routing to action planning, dynamic retrieval, and recursive reasoning, as well as the implementation of essential guardrails and monitoring systems for safe deployments. Learn about best practices, trade-offs, performance, and advanced techniques like evaluations and model context protocol.

Level up your Java apps with the power of Gemini. This session explores how Java developers can easily integrate generative AI features into their applications using LangChain4j. We’ll cover everything from building chatbots and implementing in-context learning to creating agentic workflows and using advanced techniques like unstructured data extraction. Learn best practices and build smart, AI-powered Java applications with ease. No Python experience required.