Modern AI systems are no longer simple chatbots. Real-world applications require AI assistants that can interact with backend services, execute actions, retrieve data, and coordinate workflows across distributed systems.
In this course, you will learn how to build these systems using Spring AI and Model Context Protocol (MCP). Instead of toy examples, you will implement a complete distributed AI architecture built with Spring Boot microservices. The course is based on a realistic enterprise system called NexaCorp, where an AI assistant interacts with services such as HR, deployment management, notifications, and ticket management.
Includes free 90-day access to IntelliJ IDEA Ultimate for a professional development experience.
What you will build
During this course you will build a production-style AI system that includes:
- Multiple Spring Boot microservices
- A PostgreSQL database with schema-per-service isolation
- A naive AI assistant with manual orchestration
- An MCP-based AI assistant with dynamic tool discovery
- Distributed AI workflows across multiple services
You will see how an AI assistant can coordinate operations like:
- Applying employee leave
- Finding a replacement engineer
- Reassigning deployments
- Triggering notifications across services
Course implementation highlights
This course is fully hands-on and covers:
Enterprise backend setup:
- Build multiple Spring Boot microservices
- Use PostgreSQL with schema-per-service architecture
- Manage schema and seed data using Flyway
- Verify service isolation and inter-service communication
