Microsoft Fabric handles your data foundation while Azure AI Foundry powers intelligent agents on top, creating a seamless flow from raw analytics to conversational AI that drives business decisions.​​

How They Complement Each Other

Fabric unifies lakehouses, warehouses, and real-time streams in OneLake for governed data access. Foundry connects via Fabric Data Agents (formerly AI Skills) to query that data securely, generating SQL, KQL, or DAX on the fly without custom code.​​

Agents in Foundry use your identity for passthrough auth, pulling only authorized insights from Fabric workloads. This grounds AI responses in real enterprise data, avoiding hallucinations while scaling across semantic models and event streams.​​

Real-World Integration Example

A retail team loads sales data into Fabric Lakehouse. They build a Data Agent over it, publish the endpoint, then link it to a Foundry Agent. Prompt: “Forecast Q4 revenue by region with stock risks.” Foundry agent calls the Data Agent, which runs KQL on Real-Time Intelligence and SQL on Warehouse, returning precise forecasts with visuals.​

Finance scenario: “Analyze cash flow anomalies from ledgers and predict shortfalls.” Fabric grounds the query in governed datasets; Foundry orchestrates multi-step reasoning with tools for accurate math on millions of rows.​​

Setup in Minutes

In Fabric, create a Data Agent from Lakehouse or Warehouse data, test queries, and publish. Switch to Foundry portal, add the Fabric connection via endpoint, attach to your agent, and deploy. Same-tenant setup ensures security with RBAC and audit logs.​​

Strategic Value for Leaders

This pairing turns Fabric into an AI-ready data layer and Foundry into a smart frontend, cutting dev time 40-60% on agentic apps. Start with high-value queries like sales forecasting or compliance checks, then expand to Teams bots or custom copilots.​​

#MicrosoftFabric #AzureAIFoundry #DataAI #AgenticAI