The Multi-Agent AI framework provides an end-to-end solution for orchestrating multiple autonomous agents in cloud environments. It leverages Neon’s Postgres-compatible serverless database to store conversation history and agent state, Azure Functions to run agent logic at scale, and OpenAI APIs to power natural language understanding and generation. Built-in message queues and role-based behaviors allow agents to collaborate on tasks such as research, scheduling, customer support, and data analysis. Developers can customize agent policies, memory rules, and workflows to fit diverse business requirements.

The Azure AI Travel Agents sample is an end-to-end reference implementation of a conversational agent that helps users plan trips by generating personalized travel itineraries, sourcing flight and hotel options, and answering travel-related questions. Built on the Azure AI Agent framework, it integrates OpenAI’s GPT models for natural language understanding and generation, uses Azure Functions for hosting skills such as weather lookup, and connects to external APIs for real-time booking information. Developers can run the sample locally or deploy it to Azure, extend existing skills or add new ones for currency conversion, local attraction recommendations, or travel alerts. This sample highlights how to orchestrate multiple AI-powered skills and manage context state across turns, enabling a robust, scalable travel assistant solution.