About This Architecture

Enterprise-grade AI chatbot architecture on Azure integrating Claude LLM via MCP Server, combining Azure Data Factory ETL pipelines, Event Hubs streaming, Cosmos DB knowledge store, and Azure AI Search for intelligent retrieval. Data flows from multiple sources through ingestion and processing subnets into Synapse Analytics and a knowledge store, enabling the MCP Server to orchestrate Claude API calls with cached context and real-time search results. This pattern demonstrates secure, scalable AI application design with Key Vault secrets management, API Management gateway protection, and WAF policies safeguarding the chatbot frontend. Fork this diagram to customize subnet ranges, add additional LLM providers, or adjust data pipeline stages for your enterprise knowledge base requirements.

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How do I build an enterprise AI chatbot on Azure that integrates Claude LLM with real-time data ingestion and semantic search?

This diagram shows a complete Azure architecture using MCP Server to proxy Claude LLM calls, with Azure Data Factory and Event Hubs ingesting data into Cosmos DB and Azure Synapse Analytics. Azure AI Search enables semantic retrieval, while Azure Cache for Redis optimizes performance, all protected by API Management and WAF policies for production-grade security.