Instead of working through rigid user interfaces, what if we could simply interact with the system using natural language?

In this session, we’ll explore how to transform traditional Spring Boot applications into intelligent, conversational systems by integrating AI capabilities using Spring AI.

In this session, you will learn how to:

- Interact with the system using natural language leveraging LLMs behind the scenes
- Maintain conversational context across interactions using Chat Memory
- Generate Structured Outputs from LLMs that can seamlessly integrate with your domain models
- Use Embedding Models and Vector databases to enable semantic search, similarity matching, and contextual understanding
- Build Retrieval-Augmented Generation (RAG) to augment LLMs with external knowledge sources to produce accurate, and context-rich responses
- Leverage MCP to enable LLMs interact with external systems

By the end of this session, you’ll gain a clear, practical understanding of how to leverage Spring AI in your Spring Boot applications. You’ll understand the patterns and approaches to build systems that are not just functional, but intelligent, adaptive, and more user-friendly.

- Basic understanding of Spring Boot
- Target audience: Developers, and Architects
- Preferred session duration: 1 hour