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Are you looking to build custom Copilots but unsure about the differences between Copilot Studio and Azure AI Foundry? As a Microsoft Technical Trainer with over a decade of experience, I’ve spent the last 18 months focusing on Azure AI Solutions and Copilot. Through numerous workshops, I’ve seen firsthand how customers benefit from AI solutions beyond Microsoft Copilot.
Microsoft 365 Copilot Chat offers seamless integration with Generative AI for tasks like document creation, content summarization, and insights from M365 solutions such as Email, OneDrive, SharePoint, and Teams. It ensures compliance with organizational security, governance, and privacy policies, making it ideal for immediate AI assistance without customization.
On the other hand, platforms like Copilot Studio and Azure AI Foundry provide greater customization and flexibility, tailoring AI assistance to specific business processes, workflows, and data sources for more relevant support. In this blog, I’ll share insights on building custom copilots, and the tools Microsoft offers to support this journey.
Technical Insights into Two Leading AI Platforms
Copilot Studio and Azure AI Foundry are two flagship platforms within the Microsoft AI ecosystem, each tailored for distinct purposes. Both are integral to the development and deployment of AI-driven solutions. Let’s dive into a comprehensive comparison to explore how they differ in scope, target audience, and use cases.
Target Audience
Copilot Studio
Copilot Studio is ideal for business users and developers looking to implement conversational AI with minimal setup. It is well-suited for industries like retail, customer service, and human resources.
Azure AI Foundry
Azure AI Foundry caters to software developers, data scientists, and technical decision-makers focused on building complex, scalable AI solutions. It is commonly used by enterprises in healthcare, manufacturing, and finance.
Core Solution Focus
Copilot Studio
Copilot Studio is centered around creating and customizing conversational copilots and bots, often made available to users as ‘virtual assistants’. It emphasizes a low-code/no-code environment, making it accessible to organizations looking to integrate AI-powered assistants into their workflows, all without the need of developing and writing code. Its primary goal is to enable tailored conversational experiences through customizable plugins – offering both Microsoft and 3rd party connectors to interact with, generative AI, and integration with tools like Microsoft Teams, Power Platform, Slack, Facebook and others. Copilot Studio is accessible from https://copilotstudio.microsoft.com and can be used through different licensing options.
Image 1: Copilot Studio interface with the different tabs to customize your copilot, as well as the testing pane.
Azure AI Foundry
Azure AI Foundry, conversely, is a robust platform designed for developing AI applications and solutions at scale. It focuses on foundational AI tools, including an extensive AI Large Language Model catalog, where the models allow fine-tuning, tracing, evaluations, and observability. Targeted at developers and data scientists, Azure AI Foundry provides access to a suite of pre-trained models, a unified SDK, and deeper integration with Azure’s cloud ecosystem.
The Azure AI Foundry Management Center is available from https://ai.azure.com. While there is no specific license cost for using Azure AI Foundry, note that the different underlying Azure services such as Azure OpenAI, Azure AI Search and the LLMs will incur consumption costs.
Image 2: Azure AI Foundry Management Center, allowing for model deployment, fine-tuning, AI Search indexes integration and more.
Capabilities Overview
Customizability
Copilot Studio enables organizations to build conversational bots with extensive customization options. The best part is that users don’t need to have developer skills and can add plugins, integrate APIs, and tailor responses dynamically. For example, a retail company can create a chatbot using Copilot Studio to assist customers in real-time, pull product data from SharePoint and answer queries about pricing and availability. You could also build a virtual assistant that helps conference attendees with questions and provides info on speakers, schedule, traveling information and more.
Image 3: Conference Virtual Assistant responding to a prompt about the conference agenda and offering detailed information on titles, speakers, sessions, and timings.
Azure AI Foundry specializes in advanced AI capabilities like Retrieval-Augmented Generation (RAG), model benchmarking, and multi-modal integrations. For instance, Azure AI Foundry allows a healthcare organization to use generative AI models to analyze large datasets and create research summaries while ensuring data compliance and security.
Image 4: Azure AI Foundry Safety + Security management options, follow Microsoft Responsible AI Framework guidelines.
Ease of Use
Copilot Studio is designed with simplicity in mind. Its interface supports drag-and-drop functionality, prebuilt templates, and intuitive prompt creation. Users with minimal technical expertise can quickly deploy solutions without complex coding.
Azure AI Foundry, while powerful, demands higher technical proficiency. Its SDKs and APIs are tailored for experienced developers seeking granular control over AI workflows. For example, Azure AI Foundry’s model fine-tuning capabilities require understanding of machine learning, while Copilot Studio abstracts much of this complexity.
Integration with Other Platforms and Tools
Copilot Studio Integration
Copilot Studio seamlessly integrates with Microsoft Office applications like Teams, Outlook, and OneDrive, offering conversational plugins that enhance productivity. For instance, organizations can extend Microsoft 365 Copilot with enterprise-specific scenarios, such as HR bots for employee onboarding.
Image 4: For example, Copilot Studio can integrate with email and Microsoft Dynamics.
Azure AI Foundry Integration
Azure AI Foundry connects deeply with the Azure ecosystem, including Azure Machine Learning, Azure OpenAI Service, and Azure AI Search. Developers and AI Engineers can experiment with multiple models, deploy AI workflows, and its unified SDK supports integration into GitHub, Visual Studio, and Microsoft Fabric. It also provides integration with other AI tools such as Prompt Flow, Semantic Kernel and more.
Image 5: The VSCode Prompt Flow extension can be used by developers to build and validate chat functionality, while connecting to Azure AI Foundry in the backend.
Use Case Examples
Real-Time Assistance with Copilot Studio
An airline can use Copilot Studio to create an interactive chatbot that assists travelers with flight details, weather forecasts, and booking management. The platform’s dynamic chaining capabilities allow the bot to call multiple APIs (e.g., weather and ticketing services) and provide contextual answers seamlessly.
Advanced AI Applications with Azure AI Foundry
A manufacturing company can leverage Azure AI Foundry to optimize production processes. By using multi-modal models, the company can analyze visual data from factory cameras alongside operational metrics to identify inefficiencies and recommend improvements.
Getting Started
I hope it is becoming clearer by now, which path you could follow to start building your custom copilots. As a Learn expert, I also know that customers mostly learn best by doing. To get you started, I would personally recommend going through the following Microsoft Learn tutorials:
Copilot Studio:
- Create and deploy an agent – This tutorial guides you through creating and deploying an agent using Copilot Studio. It covers adding knowledge to your agent, testing content changes in real-time, and deploying your agent to a test page: Link to tutorial.
- Building agents with generative AI – This tutorial helps you create an agent with generative AI capabilities. It provides a summary of available features and prerequisites for getting started: Link to tutorial.
- Create and publish agents – This module introduces key concepts for creating agents based on business scenarios that customers and employees can interact with: Link to tutorial.
Azure AI Foundry:
- Build a basic chat app in Python – This tutorial walks you through setting up your local development environment with the Azure AI Foundry SDK, writing prompts, running app code, tracing LLM calls, and running basic evaluations: Link to tutorial.
- Use the chat playground – This QuickStart guides you through deploying a chat model and using it in the chat playground within the Azure AI Foundry portal: Link to tutorial.
- Azure AI Foundry documentation – This comprehensive documentation helps developers and organizations rapidly create intelligent applications with prebuilt and customizable APIs and models: Link to tutorial.
Conclusion
While Copilot Studio and Azure AI Foundry share Microsoft’s vision for democratizing AI, they are typically used by different audiences and serve distinct purposes. Copilot Studio is the go-to platform for conversational AI and low-code deployments, making it accessible for businesses and their users, aiming to enhance customer and employee interactions. Azure AI Foundry is a powerhouse for advanced AI application development, enabling organizations to leverage cutting-edge models and tools for data-driven insights and innovation, but it requires advanced development skills to build such AI-inspired applications.
Choosing between Copilot Studio and Azure AI Foundry depends on the specific needs and technical expertise of the organization. If you are new to AI, a good place to start is with Copilot Studio and then to grow into a more advanced scenario with Azure AI Foundry.