Introduction

Organizations today need applications that can handle complex, multi-step tasks autonomously while delivering personalized, context-aware responses. AI agents are transforming how businesses interact with customers by orchestrating workflows, retrieving relevant information, and maintaining conversational context across interactions.

Consider Margie's Travel, a vacation rental platform with thousands of properties and continuous guest inquiries. They need intelligent systems to recommend personalized stays, analyze guest feedback, and coordinate specialized tasks like inventory checks and sentiment analysis. With AI agents powered by Azure Database for PostgreSQL, the company can build scalable solutions that combine vector search for semantic understanding, persistent memory for context retention, and multi-agent orchestration for complex workflows.

This module shows you how to build and deploy AI agents using Azure Database for PostgreSQL and orchestration frameworks.

In this module, you learn:

• Understand agentic architectures and how PostgreSQL supports information retrieval and memory.
• Apply vector search and semantic operators for intelligent information retrieval.
• Evaluate agentic frameworks like Microsoft Agent Framework, LangGraph, LlamaIndex, and Foundry Agent Service.
• Implement AI agents using Foundry Agent Service with PostgreSQL integration.
• Integrate agents with Model Context Protocol (MCP) for standardized tool access.

After completing this module, you'll be able to:

• Build multi-agent systems that coordinate specialized tasks using Azure Database for PostgreSQL.
• Implement vector search and semantic retrieval to power context-aware agent responses.
• Deploy agents with Foundry Agent Service that access structured and semantic data.
• Integrate MCP-based tools to extend agent capabilities with external services.
• Design scalable agentic architectures that maintain context and deliver personalized interactions.