Enterprise AI Agents with Java and Spring

Integrating artificial intelligence into enterprise systems does not require switching to a new programming language. You can build powerful, secure, and scalable AI agents using your existing Java skills and the robust Spring ecosystem. This text-based course guides you from the absolute basics of generative AI to deploying fully functional enterprise agents. You will understand how to manage context, leverage vector databases for semantic search, and orchestrate complex workflows. What you will learn: - Understand the core principles of generative AI, large language models, and agentic workflows within the Java ecosystem. - Configure Spring AI to connect securely with Azure OpenAI services and manage model parameters. - Implement Retrieval-Augmented Generation (RAG) using PostgreSQL as a vector database to provide agents with custom enterprise knowledge. - Design autonomous AI agents capable of tool call execution and multi-step reasoning. - Deploy your containerized Java applications to cloud environments using Azure Container Apps. - Apply modern Java development practices, including strong typing, structured logging, and robust error handling for AI integrations. The course starts with foundational AI terminology and Spring configuration basics before moving step-by-step through vector database integration, agent orchestration, and cloud deployment strategies. You will learn through clear, written explanations and practical code walkthroughs designed to build your confidence. This course is designed for Java developers, software engineers, and system architects who want to transition into AI engineering. No prior experience with artificial intelligence or machine learning is required, though a basic understanding of Spring Boot is recommended. Start reading today to bridge the gap between enterprise Java development and modern artificial intelligence.