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Spring AI & Embabel Training

Develop and extend software systems with AI capabilities. Learn how to embed modern language models with Java and Spring AI in applications and build intelligent, enterprise-ready solutions.

The rise of artificial intelligence has opened up countless new possibilities. This course focuses on Spring AI and covers selecting suitable language models, prompt engineering, RAG patterns, agentic workflows, and interaction with AI systems, all within the familiar Spring ecosystem.

What You Will Learn

Through practical hands-on sessions, you'll gain concrete insights into how Spring AI tools can be used to develop intelligent, enterprise-ready applications, from chat interactions and image generation to audio transcription and agentic patterns.

  • LLMs & Spring AI Fundamentals

    Understand the fundamentals of language models, explore the Spring AI framework, and connect to providers like OpenAI, Anthropic, and Ollama using Spring AI's unified model client API.

  • Prompt Engineering

    Master prompt engineering best practices: stuffing, chaining, and structuring prompts. Learn output parsing, structured responses, and how to optimise model interaction.

  • RAG & Vector Stores

    Build Retrieval-Augmented Generation pipelines to ground models in your own data. Work with vector databases, embeddings, and implement RAG patterns in the Spring ecosystem.

  • Function Calling & MCP

    Integrate AI with your APIs and systems through function and tool calling with Spring AI. Build MCP clients and servers for structured AI-system interaction.

  • Media Integration

    Generate images with AI models, transcribe audio, process speech, and develop multimodal applications that combine text, image, and audio capabilities.

  • Observability & Quality

    Evaluate and test AI-powered features effectively. Set up observability and monitoring, implement chat memory and guardrails, and build confidence in AI-driven behaviour.

  • Multi-Model Strategies

    Combine local and cloud models for cost-effective AI. Learn model selection, optimisation techniques, and strategies for balancing performance, quality, and cost.

  • Agentic Patterns

    Design AI-powered agents for complex tasks: workflow automation, multi-step reasoning, goal-driven orchestration, and developing autonomous systems with Embabel.

Who Is This Training For?

This training is for software developers and architects who want to integrate AI functionality into their applications and already have experience developing Spring or Java applications.

  • Spring & Java Developers

    Developers with Spring Boot experience who want to explore AI integration without leaving the Java ecosystem or learning a new stack from scratch.

  • Product Teams

    Teams building features powered by language models who need a structured, engineering-led approach to AI integration, evaluation, and production readiness.

  • Architects & Tech Leads

    Leads evaluating Spring AI for their stack who want a grounded, practical understanding of the patterns, trade-offs, and cost-effective strategies involved.

Training Details

A proven mix of concepts, live coding, and collaboration on building comprehensive AI applications, always geared towards efficient usage of Spring AI in real-life projects and production.

Format

On-site at your office, fully remote, or in our course rooms. We adapt exercises and tooling to your environment.

Duration

2 days. Individually adapted for in-house courses and can be split into focused modules.

Language

Delivered in English or German. Italian available on request.

Prerequisites

Good knowledge of Java and Spring Boot. Practical experience with container platforms (Docker Desktop, Podman). No prior AI or ML knowledge required.

Ready to Get Started?

Tell us about your team and goals. We'll design the right training for your context.

Request this training