How Copilot Studio Supports Multimodal AI Models

Microsoft Copilot Studio (formerly Power Virtual Agents) is evolving to support multimodal AI models that process and generate content across text, images, audio, and video. These AI models enhance chatbot capabilities, allowing them to understand natural language, visual content, speech, and other forms of data for more advanced interactions.

This guide provides a step-by-step breakdown of how Copilot Studio integrates multimodal AI models, including GPT-4 Turbo with Vision, Azure Cognitive Services, and AI Builder.

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Understanding Multimodal AI in Copilot Studio

A multimodal AI model can process multiple types of data (text, images, audio, video) and combine them for better decision-making.

Multimodal Capabilities in Copilot Studio

1. Text + Image Processing – Analyze images, recognize objects, and generate text-based insights.
2. Text + Speech – Convert speech to text and vice versa for voice-enabled bots.
3. Text + Video Analysis – Extract information from videos using AI models.
4. Custom AI Integration – Use GPT-4 Turbo with Vision, Azure Cognitive Services, and AI Builder for multimodal processing.

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Step 1: Setting Up Copilot Studio for Multimodal AI

1.1 Create a Multimodal AI-Powered Chatbot

1. Go to Copilot Studio.
2. Click Sign in and log in with your Microsoft account.
3. Click Create a New Bot.
4. Provide:
   • Bot Name (e.g., “Multimodal AI Assistant”).
   • Language (English, Spanish, etc.).
5. Click Create and wait for deployment.

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Step 2: Enabling Image Processing with GPT-4 Turbo (Vision)

2.1 Set Up Azure OpenAI GPT-4 Turbo with Vision

GPT-4 Turbo with Vision can analyze images and extract insights.

1. Open Azure Portal.
2. Search for Azure OpenAI Service.
3. Click + Create → Select GPT-4 Turbo (Vision Capable).
4. Deploy the model and copy the API Key and Endpoint.

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2.2 Integrate Image Processing in Copilot Studio

To process images, Copilot Studio needs to send image URLs to GPT-4 Turbo.

1. Open Copilot Studio → Topics.
2. Click + Add Node → Call an API.
3. Configure the API request:
   • Method: POST
   • URL: https://your-openai-instance.openai.azure.com/v1/completions
   • Headers: { "Content-Type": "application/json", "Authorization": "Bearer YOUR_API_KEY" }
   • Body: { "model": "gpt-4-turbo", "messages": [ {"role": "user", "content": [ "Analyze the following image and describe the objects:", {"type": "image_url", "image_url": "{User Image URL}"} ]} ], "max_tokens": 200 }
4. Save and test the chatbot.

✅ Example Use Case: Users can upload images, and the chatbot can describe the content.

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Step 3: Enabling Speech Capabilities with Azure Speech Services

3.1 Enable Speech-to-Text and Text-to-Speech

Microsoft’s Azure Speech Services allows Copilot Studio to handle voice inputs and generate spoken responses.

3.1.1 Set Up Azure Speech Services

1. Open Azure Portal.
2. Search for Azure Speech Service.
3. Click + Create → Select Speech-to-Text and Text-to-Speech.
4. Copy the API Key and Endpoint.

3.1.2 Integrate Speech with Copilot Studio

1. Open Copilot Studio → Topics.
2. Click + Add Node → Call an API.
3. Configure the API request for Speech-to-Text:
   • Method: POST
   • URL: https://your-region.cognitiveservices.azure.com/speech-to-text/v3.0/transcriptions
   • Headers: { "Ocp-Apim-Subscription-Key": "YOUR_API_KEY", "Content-Type": "application/json" }
   • Body: { "contentUrls": ["{User Audio URL}"], "locale": "en-US" }
4. Save and test the chatbot.

✅ Example Use Case: Users can send voice messages, and the chatbot will transcribe them into text.

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Step 4: Video Analysis with Azure Video Indexer

4.1 Set Up Video Analysis

1. Open Azure Video Indexer.
2. Sign in and create a new Video Indexing Service.
3. Upload a video or provide a video URL.

4.2 Extract Insights from Videos

1. Open Copilot Studio → Topics.
2. Click + Add Node → Call an API.
3. Configure the API request for Video Analysis:
   • Method: GET
   • URL: https://api.videoindexer.ai/{location}/Accounts/{accountId}/Videos/{videoId}/Index?accessToken={AccessToken}
4. Save and test the chatbot.

✅ Example Use Case: Users can upload videos, and the chatbot will extract key insights, speech, and visual elements.

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Step 5: Automating Multimodal AI Workflows

5.1 Using Power Automate to Combine Text, Image, and Voice AI

1. Open Power Automate.
2. Create a new flow → Select Copilot Studio as a trigger.
3. Add actions:
   • Azure Cognitive Services for text analysis.
   • Azure OpenAI for GPT-4 text generation.
   • Azure Speech Services for voice processing.
   • Azure Video Indexer for video processing.
4. Save and deploy the workflow.

✅ Example Use Case: A customer support bot that can analyze product images, process user voice commands, and extract video insights in real-time.

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Final Thoughts

Copilot Studio now supports multimodal AI models, allowing chatbots to understand text, images, audio, and video for richer user interactions.

✅ GPT-4 Turbo with Vision → Image and text-based analysis
✅ Azure Speech Services → Speech-to-Text & Text-to-Speech
✅ Azure Video Indexer → Extract video insights
✅ Power Automate → Automate AI workflows

Would you like a hands-on demo or an example use case for your business?