Context: Organizations often struggle to extract meaningful insights from vast internal data repositories. Traditional search systems fall short in delivering conversational, context-aware responses. With the rise of large language models (LLMs), there's a growing need to integrate these capabilities with enterprise data securely and efficiently.

Solution: The Azure Search + OpenAI Demo showcases a Retrieval-Augmented Generation (RAG) application that combines Azure OpenAI Service with Azure AI Search. It enables users to interact with their own documents through a ChatGPT-like interface. The solution indexes documents using Azure AI Search and retrieves relevant content to ground GPT model responses, ensuring accuracy and relevance. It supports multi-turn chat, citations, and customizable settings, and is deployable via GitHub Codespaces or local environments.

Impact: This demo empowers businesses to build intelligent, domain-specific assistants that enhance knowledge discovery, reduce information retrieval time, and improve decision-making. By leveraging Azure’s scalable infrastructure and OpenAI’s language models, organizations can create secure, production-ready AI experiences tailored to their internal data.