How to Deploy AI Foundry Models to Frontend

Question

Hi,

I have a doubt! How can I integrate my Azure AI Foundry Models to the frontend deployment so that the output/it's final product is usable after model development.

If Suppose I have my backend in Power Automate flow (As a Workflow Developed), how can I integrate to frontend deployment using Azure AI Foundry for Model Building (E.g. If my models are needed for Voice Responses, Chat Responses, etc.. based on Input from User)

One of the method is through Power Apps as frontend.

Is there any other way we can get the model deployment?

Any solution or along with Microsoft Official Documentation will be highly helpful.

Thanks in Advance!

Answer 1

Hi Ashwath Bala S,

You can connect Azure AI Foundry models to Power Automate and subsequently to Power Apps for voice-based requirements. While Azure AI Foundry provides access to various AI models, including those for speech, you may still need to leverage Azure AI Speech Services for specific functionalities such as Speech to Text and Text to Speech.

To implement a voice-based solution, you can use Power Automate to create flows that connect to the AI Foundry models. This integration allows you to utilize the capabilities of the models in your applications. However, for comprehensive voice functionalities, integrating Azure Speech Services may be necessary, as they specialize in handling voice input and output.

while you can use AI Foundry models in conjunction with Power Automate and Power Apps, Azure Speech Services may still play a crucial role in fulfilling voice-based requirements effectively.

Kindly refer below link: connect-services-ai-foundry-portal

Thank You.

Answer 2

Hello Ashwath Bala S,

Thank you for posting your question in the Microsoft Q&A forum. 

Integrating Azure AI Foundry models into your frontend deployment requires a structured approach, especially when using Power Automate as the backend workflow. The most straightforward method involves exposing your AI models as REST APIs through Azure AI Foundry, which can then be consumed by Power Apps or custom frontend frameworks like React or Angular. For enterprise-grade solutions, Azure API Management (APIM) provides a secure layer to manage, throttle, and monitor these API calls efficiently. 

If your application involves voice or chat responses, Microsoft Copilot Studio offers a no-code integration path for conversational AI, while Azure Static Web Apps combined with Azure Functions can serve as a lightweight alternative for serverless deployments. Official Microsoft documentation recommends deploying models as scalable endpoints in Azure AI Foundry, then connecting them to Power Automate via HTTP actions for seamless workflow integration. For advanced scenarios, consider using Azure AI Speech Services alongside your custom models to enhance real-time interactions. 

Key references include Microsoft’s guides on deploying AI models, Power Automate custom connectors, and API Management best practices to ensure a robust and scalable implementation. 

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