Course · Training · Workshop
Spring AI: Intelligent Applications with Java
Develop and extend software systems with AI capabilities. Experience how to embed modern language models with Java and Spring AI in applications and build intelligent applications.
The rise of artificial intelligence has revolutionized our world and opened up countless new possibilities. Applications with advanced language capabilities can now be developed more efficiently and with less complexity. This course focuses on Java libraries like Spring AI. Central topics covered include selecting suitable language models (LLMs), prompt engineering, and interaction with AI systems. Through practical hands-on sessions, you'll learn to use various models for scenarios like chat interactions, image generation, and audio transcription. You'll gain concrete insights into how Spring AI tools can be used to develop intelligent, enterprise-ready applications.
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Content
– Introduction to LLMs and Spring AI:
- Fundamentals of Artificial Intelligence and Language Models
- Overview of the Spring AI Framework – Basics of AI Interaction:
- Understanding prompts and output parsing
- First steps with chat models
- Processing structured responses – Prompt Techniques and Advanced Concepts:
- Prompt Engineering Best Practices
- Stuffing, chaining, and structuring prompts
- Optimizing model interaction – Retrieval Augmented Generation (RAG):
- Using your own data with LLMs
- Vector databases and embeddings
- Implementing RAG patterns – Function Calls and Structured Results:
- APIs and system integration
- Function and tool calling with Spring AI
- MCP Clients and Servers – Media Integration:
- Image generation with AI models
- Audio transcription and speech processing
- Developing multimodal applications – Advanced Practices:
- Evaluation and quality assurance
- Observability and monitoring
- Chat Memory and guardrails – Multi-Model Approaches:
- Combining local and cloud models
- Model selection and optimization
- Cost-effective AI strategies – Agentic Patterns:
- AI-powered agents for complex tasks
- Workflow automation with AI
- Developing autonomous systems – Outlook and Best Practices:
- Trends in AI development
- Operating productive AI applications
We focus on deepening and understanding a specific selection of topics.
The actual course content may differ from the above depending on the trainer, delivery, duration and the composition of participants.
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More about Spring AI
Spring AI is an application framework from the Spring ecosystem that enables developers to seamlessly integrate AI capabilities into Java applications. It abstracts the complexity of various Large Language Models (LLMs) and AI services behind a unified, Spring-style API, supporting concepts like Retrieval Augmented Generation (RAG), prompt engineering, vector databases, and agent-based workflows. With Spring AI, enterprise-grade AI applications can be built using the same proven patterns Java developers already know from Spring Boot.Further resources:
History
The Spring AI project was launched in 2023 and officially introduced at the SpringOne conference in Las Vegas. The rise of Large Language Models like GPT-4 and the public breakthrough of ChatGPT in late 2022 created the need for a framework that brings AI capabilities easily into existing Java enterprise applications. The first publicly available version, 0.8.0, was released in February 2024.
Spring AI 1.0 GA was released in May 2025, bringing stable support for diverse LLM providers, vector databases, the Model Context Protocol (MCP), and agent-based patterns. The framework has been evolving rapidly since then, addressing the growing enterprise demands for secure, scalable, and maintainable AI integration.