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It applies proven Azure design patterns and incorporates **Zero-Trust security**, **Responsible AI**, and **end-to-end observability**, enabling teams to operationalize Generative AI with confidence.\n\nFor full documentation, visit the **[GPT-RAG documentation site](https://azure.github.io/GPT-RAG/)**.\n\nGPT-RAG is built on a Zero-Trust architecture to ensure that all components operate within a controlled, isolated environment. Network access is tightly governed, and communication between services follows least-privilege principles.\n\n## Architecture\n\n![Zero Trust Architecture](media/architecture_zero_trust.png)\n*Zero-Trust Architecture*\n\n## AI Agent Capabilities\n\nThe accelerator supports a broad range of enterprise scenarios—from customer support to decision automation—by enabling systems to process complex queries across large data collections. It is designed for seamless integration into existing environments and can be adapted to both straightforward and advanced operational patterns.\n\nA key capability of GPT-RAG is its support for **AI Agents**, enabling scenarios such as **NL2SQL query generation** and other context-aware interactions. This extensibility allows organizations to build intelligent workflows that retrieve, interpret, and act on data with contextual precision.\n\n![Zero Trust UI](media/gpt-rag-homepage.png)\n*GPT-RAG UI*\n\n## Contributing\n\nWe welcome contributions! See the [contribution guidelines](https://azure.github.io/GPT-RAG/contributing/) for details on how to contribute.\n\n## Trademarks\n\nThis project may contain trademarks or logos. Authorized use of Microsoft trademarks or logos must follow [Microsoft’s Trademark \u0026 Brand Guidelines](https://www.microsoft.com/en-us/legal/intellectualproperty/trademarks/usage/general). Modified versions must not imply sponsorship or cause confusion. 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