Enterprise AI for Banking with Spring AI, RAG, MCP & Agents is a hands-on, architecture-driven course that demonstrates how governed AI capabilities can be added to a realistic Spring Boot banking platform. Everything built in this course is a working educational prototype. The code is designed to teach enterprise AI architecture: how the components fit together, why particular design decisions are made, and how these patterns can be applied in a regulated banking context.
Throughout the course, you will learn how to design AI systems that combine:
- large language models and prompt contracts;
- evaluation and controlled refusal;
- Retrieval-Augmented Generation with PostgreSQL and PGVector;
- MCP-based banking tools;
- governed agent gateways;
- controlled conversational memory;
- context recovery;
- guardrails and confirmation boundaries;
- multi-step workflows;
- multi-agent orchestration.
Spring AI is used as the primary framework for implementing the AI layer. The objective is not to recreate an AI framework from scratch, but to understand how Spring AI fits into a broader enterprise architecture where deterministic banking services, authorization boundaries, audit trails and validation rules remain authoritative.
