AIFLX

Library / Artificial Intelligence

Enterprise AI for Banking with Spring AI, RAG, MCP & Agents

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About this course

AI Usage Disclosure

This course includes the use of artificial intelligence technologies for educational demonstration.

Technology Stack:

  • Spring Boot, Spring AI, Java, Ollama, PostgreSQL, PGVector, Model Context Protocol (MCP)Course Overview

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 Java AI architecture: how components fit together, why particular design decisions are made, and how these patterns can be applied in a regulated banking context.

What You Will Learn

Throughout this advanced Spring Boot course, you will learn how to design AI systems that combine:

  • Large Language Models (LLMs) and prompt contracts
  • Evaluation and controlled refusal patterns
  • Retrieval-Augmented Generation (RAG) with PostgreSQL and PGVectorMCP-based banking tools and model context protocol implementation
  • Governed agent gateways and authorization boundaries
  • Controlled conversational memory and context recovery
  • Guardrails and high-risk action confirmation boundaries
  • Multi-step workflows and deterministic validation rules
  • Multi-agent orchestration and delegation
  • Why Spring AI?

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, microservices

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