Integrations · Azure AI Foundry
Power Automate + Azure OpenAI + Copilot Studio form a complete no-code/low-code AI automation stack — connecting 900+ connectors with LLM intelligence. Build agents that span every system in your enterprise without writing custom integration code.
What's Possible
Power Automate flows invoke Azure AI Document Intelligence to extract structured data from invoices, purchase orders, and forms — then write extracted fields directly to Dataverse, SharePoint lists, or downstream APIs.
Approval chains in Power Automate call Azure OpenAI to provide decision context — summarising the approval item, surfacing relevant history from Dataverse, and recommending approve/reject with supporting rationale.
Canvas apps and model-driven apps in Power Apps call custom Azure AI connectors — enabling natural language search, AI-generated form fields, and embedded chatbots without leaving the application.
Dataverse row creation or update events trigger AI-augmented flows. A new customer record triggers an enrichment agent; a support case update triggers sentiment analysis and priority re-scoring.
Copilot Studio agents are embedded directly into Power Apps canvas apps via the AI Builder integration — giving field workers, operations staff, and customer-facing teams an AI assistant within existing apps.
Azure OpenAI generates natural language summaries of Power BI report changes — delivered as Power Automate notifications when KPIs cross thresholds, with an explanation of the contributing factors.
How We Connect It
Power Platform uses custom connectors backed by Azure API Management to call Azure OpenAI and Azure AI services. Service principal authentication from Power Platform to Azure is established via Entra ID app registrations.
Dataverse serves as the central data store, with Power Automate connecting to 900+ external systems via pre-built connectors. Azure AI Document Intelligence handles unstructured inputs before writing structured output to Dataverse.
Copilot Studio provides the conversational layer for end-user-facing agents, while Power Automate handles background automation. Both are deployed and managed through the Power Platform admin centre.
Use Cases
Scenario: Supplier invoices arrive by email. A Power Automate flow extracts the attachment, sends it to Azure AI Document Intelligence, maps extracted fields (vendor, amount, line items) to Dataverse, and triggers a three-way PO match.
Outcome: 92% of invoices processed straight-through with zero manual data entry. AP team reviews exceptions only, reducing processing cost per invoice by over 70%.
Scenario: Field inspectors use a Power Apps canvas app to log equipment checks. The embedded Copilot agent interprets inspection notes in natural language, classifies defect severity, and pre-populates the work order in Dynamics 365 Field Service.
Outcome: Inspection report submission time drops from 45 minutes to 12 minutes. Defect classification consistency improves as AI applies a standardised rubric across all inspectors.
Scenario: An employee submits a leave request in a Power Apps form. Power Automate checks team calendar coverage via Microsoft Graph, calculates leave balance from the HR system, and routes to the manager with an AI-generated coverage summary.
Outcome: Leave approval cycle drops from 2 days to same-day. Managers have full context before approving — reducing approval reversals caused by calendar conflicts.
Scenario: A sales rep completes a deal qualification form in a Power App. Power Automate calls Azure OpenAI with the deal parameters and retrieves relevant case studies from SharePoint via Azure AI Search, assembling a tailored proposal draft.
Outcome: Proposal turnaround drops from 3 days to 4 hours. Proposal quality improves as AI populates relevant proof points rather than sales reps writing from blank.
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