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Showcases

Implementation examples for current IT topics

How we approach problems – as traceable code, not as a glossy case study. Each example tackles a concrete technical question and shows one possible solution, openly available on GitHub.

github.com/SCC-Informationssysteme-GmbH/demos-public
Copyright SCC Informationssysteme GmbH 2026
Showcase

spring-mcp-demo

Two business domains – bookstore and customer management – each with its own REST API and its own MCP server. An orchestrator backend talks to OpenAI and both MCP servers via ChatClient and an MCP client, exposing chat and agent endpoints to the React frontend. Shows how multiple MCP servers can be connected and orchestrated with Spring AI 2.0.

JavaSpring BootSpring AIMCPOpenAI APIReact
Showcase

spring-ai-rag-ollama-demo

A Spring Boot backend connects to a local LLM via Ollama – chat model llama3.2 and embedding model mxbai-embed-large, both with no cloud API. Ollama starts automatically via Spring AI's Docker Compose integration, with RAG over Qdrant supplying the matching context.

JavaSpring BootSpring AIRAGOllamaQdrantReact
Showcase

spring-ai-agents-demo

Three LLM agents for the support workflow: classification, RAG-based research against a Qdrant knowledge base, and a draft reply approved by a staff member before it is sent. Shows how multiple agents can be orchestrated with Spring AI.

JavaSpring BootSpring AIMulti-AgentRAGQdrantReact
Showcase

spring-n8n-demo

An order process where n8n handles the workflow logic: orders above €500 trigger an approval request via Slack, while smaller amounts are approved automatically. Shows how a Spring Boot backend can integrate cleanly with a low-code workflow engine and chat notifications.

Spring Bootn8nSlackREST
Showcase

spring-ai-demo

Six typical building blocks of LLM integration with Spring Boot, each as its own channel: simple REST-based chat, prompt templates, retrieval-augmented generation, integration with a vector database (Qdrant), LangChain4j with session memory, and AI-assisted business logic for ticket classification.

JavaSpring BootSpring AIRAGLangChain4jREST
Showcase

spring-t23d-demo

A web application that turns text prompts into FreeCAD code via OpenAI, renders them into an STL file in a sandboxed Docker container, and displays the result directly as a 3D model in the React frontend.

JavaSpring BootReactOpenAI APIDockerFreeCAD
Showcase

spring-tts-demo

A lightweight Spring Boot service that accepts text via a REST endpoint and converts it into audio using the OpenAI text-to-speech API. Shows how an external TTS API can be integrated cleanly into a Java backend to automate voicing text content.

JavaSpring BootText-to-SpeechOpenAI TTS APIREST
Showcase

jee-bpel-demo

A BPEL process on Apache ODE, embedded in a Jakarta EE application (WildFly): orchestrates three approval paths – automatic, manual review, manager with escalation – including correlation sets, pick/onAlarm, and compensation. Shows Jakarta EE 10, JPA/Hibernate, CDI, EJB, JMS, REST/SOAP, and BPEL working together, entirely local via Docker with no license costs.

JavaJakarta EEBPELApache ODEJMSSOAPJSF

More to come

New topics are added continuously as separate repos in demos-public – e.g. from cloud migration or system integration.

Further reading

Official documentation for the technologies used in our showcases – useful if you're exploring them for the first time.

Languages & Frameworks

  • dev.java ↗ Official Java developer portal with tutorials and language reference.
  • Spring Boot ↗ Official documentation for the Java framework behind most of our showcases.
  • Apache ODE ↗ Open-source engine for executing BPEL processes, embedded in Jakarta EE applications.

AI & LLM Integration

  • Spring AI ↗ LLM integration, function calling and RAG for Spring Boot applications.
  • LangChain4j ↗ Java library for LLM applications with chat memory and tool integration.
  • OpenAI API ↗ Reference for the OpenAI API covering chat completions, function calling and code generation.
  • Qdrant ↗ Open-source vector database for semantic search and RAG.
  • Ollama ↗ Local runtime for chat and embedding models via a unified REST API, used in the spring-ai-rag-ollama-demo showcase.
  • Nous Research – Hermes Agent ↗ Open-source agent framework with multi-platform integration (Telegram, Discord, Slack and more), subagents and sandbox backends like Docker and Modal.
  • Composio ↗ Tool integration platform for AI agents with 1,000+ app connections, managed OAuth and sandboxed execution.

AI Tools: Video & Audio

  • Higgsfield ↗ AI platform for video, image and audio generation, including text-to-video and voiceover.

Cloud & Platforms

  • Microsoft Azure ↗ Documentation on Azure services for cloud migration and operation.
  • AWS ↗ Documentation on Amazon Web Services for cloud migration and operation.
  • Google Cloud ↗ Documentation on Google Cloud services for cloud migration and operation.
  • Docker ↗ Documentation on containers and Docker Compose for isolated, reproducible execution environments.
  • Kubernetes ↗ Container orchestration for deploying, scaling and operating distributed applications.
  • OpenShift ↗ Red Hat's enterprise Kubernetes platform with an integrated build and deployment workflow.

Automation

  • n8n ↗ Workflow automation with visual nodes, e.g. for approval and notification processes.

LLM Providers

  • OpenAI ↗ Provider of the GPT models and the API used e.g. in the spring-t23d-demo showcase for code generation.
  • Anthropic ↗ Provider of the Claude model family for chat, code generation and agents.
  • Google DeepMind ↗ Provider of Google's Gemini model family.
  • Mistral AI ↗ European provider of open and commercial language models.
  • Moonshot AI ↗ Provider of the Kimi model family, including Kimi K3.
  • OpenRouter ↗ Bundled access to models from multiple providers through one OpenAI-compatible API – no separate account per provider.

Knowledge Management

  • Obsidian ↗ Note-taking app based on local Markdown files for knowledge organization, planned as a context source for AI agents.

Let's talk.

Tell us about your project – we'll get back to you shortly.

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