Spring AI & Embabel Training

Evaluate and implement LLM-backed features in your existing Java and Spring stack. Follow a core path through Spring AI, then work with modules in RAG, tool calling, MCP, evaluation, observability, and agentic workflows with Embabel, selected around your use case.

Book a 30-min call Request by email

Two-day in-house course for up to 12 participants. Delivered in Zürich, at your office across Switzerland or Europe, or fully remote; examples are aligned with your team's providers, Spring versions, and use cases.

When This Training Is Worth Your Team's Time

For CTOs and engineering managers who need their JVM team to make informed AI engineering decisions, not just reproduce a demonstration.

  • You Have a Concrete Use Case

    The team needs to decide whether model calls, RAG, tools, or an agentic workflow fit an identified product or operational need.

  • A Pilot Needs Engineering Discipline

    Developers need practical ways to evaluate outputs, observe model interactions, control tool access, and reason about cost.

  • The JVM Is the Operating Context

    Your domain logic and delivery platform already use Java and Spring, and the team wants to assess Spring-native integration before adding another runtime.

Core and Tailored Modules

The agenda is configured for depth rather than maximum coverage. Before delivery, we agree a core path through model integration, RAG or tools, evaluation, and one deeper workflow, then select the supporting modules that fit your use case.

  • 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

    Practise prompt design, context assembly, and structured responses. Compare techniques for output parsing and controlling model interaction.

  • RAG & Vector Stores

    Build Retrieval-Augmented Generation pipelines to ground models in your own data. Use vector stores and embeddings to implement RAG patterns with Spring AI.

  • 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 model-backed features with repeatable cases. Set up observability, inspect model interactions, and implement chat memory and guardrails appropriate to the use case.

  • Multi-Model Strategies

    Compare local and hosted models, then practise selecting and routing them based on measured quality, latency, data-handling requirements, and cost.

  • Agentic Patterns

    Model multi-step workflows with typed actions and goal-directed planning in Embabel. Discuss where evaluation, guardrails, and human approval remain necessary.

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 with Java and Spring Boot.

  • 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

Concepts, live coding, and hands-on exercises are connected to the systems, providers, and operational constraints your team works with.

Format

In Zürich, on-site at your office, or fully remote. We adapt exercises and tooling to your environment.

Duration

2 days. For in-house delivery, we adapt the agenda and can split it into focused modules.

Language

Delivered in English or German. Italian available on request.

Prerequisites

Good knowledge of Java and Spring Boot. Experience using Docker Desktop or Podman is helpful but not required. No prior AI or ML knowledge is required.

Frequently Asked Questions

Where does the training take place?

In Zürich, at your office anywhere in Switzerland or Europe, or fully remote.

Is the training available in German?

Yes. We deliver the training in English or German – Italian is available on request. Course materials are in English.

How long does the training take?

2 days. For in-house courses we adapt the content individually and can split it into focused modules.

Which LLM providers are covered?

Spring AI's portable abstractions work with OpenAI, Azure OpenAI, Anthropic, Google, Mistral, and local models via Ollama – we adapt the examples to the providers your team uses.

How much does the training cost?

We deliver in-house, for up to 12 participants. The final price depends on group size, duration, and how much we tailor the content. Book a 30-minute call or email hello@42talents.com. We reply personally to emails within one business day.

Related Spring Courses

Explore the other courses in our Spring training curriculum.

Build the capability your roadmap needs

Tell us which capability your team needs to build. We'll shape the course around your stack, delivery goals, and current codebase.

In-house, up to 12 participants. Content tailored to your codebase and your stack.

Book a 30-min call Request by email