Bring Your Organizational Data to Azure AI Services with Microsoft Graph

Using AI to connect business data to the AI ​​applications that matter isn’t just a nice-to-have feature; it’s a necessity in today’s world.

Connecting data from platforms like Microsoft 365 to AI-powered apps can streamline tasks, reduce the need to switch between apps, and increase productivity.

In this blog, we’ll walk you through how to easily connect your business data to Azure using Microsoft Graph (and extend that to integrate with OpenAI services), and show you how powerful and simple these tools can be.

Why should I integrate my data?

Imagine you’re deep in a project and need to find a specific document, email, or chat in Microsoft Teams. Normally, you’d have to go back and forth between Outlook, OneDrive, and Teams, interrupting your workflow and wasting time. This is where integrating business data into your applications becomes incredibly useful.

With Microsoft Graph and Azure OpenAI services, you can bring all this information directly into your apps, keeping everything in one place. This not only saves you time, but also helps you focus on your work. Whether you need to find a file, an email, or a chat history, integrating these tools can streamline your day and keep you on track.

Key Use Cases for Microsoft Graph Powered by Generative AI

The Microsoft Graph is versatile and its applications are endless. Here are some common use cases that are enhanced by generative AI.

Automate Microsoft 365 Workflows Using Generative AI

Using Microsoft Graph with generative AI, you can automate tasks such as:

• Email Management: In addition to automatically sorting and responding to your emails, generative AI can draft personalized replies, summarize long email threads, and even predict and prioritize which emails need your immediate attention.

• File operations: In addition to managing files in OneDrive and SharePoint, generative AI can assist with content creation, generating document summaries, and suggesting relevant files based on the context of the task.
• User Management: Automate user provisioning and updates while generative AI predicts user needs, suggests role changes, and provides insights into user behavior and engagement.

Microsoft Teams Integration to Boost Productivity with Generative AI

The Microsoft Graph enables tight integration with Teams, and generative AI takes it a step further by allowing:

• Create teams and channels: Automate the setup of new teams for your projects, use generative AI to suggest optimal team structures, recommend channels based on project needs, and even draft initial posts to start discussions.
• Conversation Management: While archiving or monitoring conversations for compliance, generative AI can analyze conversation trends, detect sentiment, and provide insights into team dynamics and areas for improvement.
• Custom bots: Develop bots that interact with Teams users, powered by generative AI, to provide more natural and contextual interactions, answer complex queries, and even assist in decision-making processes.

Microsoft Graph can help you automate and streamline workflows by leveraging generative AI, as well as deliver intelligent insights and personalized experiences to dramatically increase productivity and efficiency.

Getting started with Microsoft Graph

Microsoft Graph is a powerful API that lets you connect to a variety of data points across Microsoft 365. This lets you bring email, chat, files, and more into your applications. To get started, you’ll need to set up what’s called an “app registration” in Microsoft Entra Identity (formerly Azure Active Directory). This registration allows your app to securely access data.

Step 1: Set up app registration

1. Sign in to the Azure Portal and navigate to your Microsoft Entra ID.

2. Create a new app registration by specifying a name.

3. Select the type of account that can access this app. Choose whether it is accessible only within your organization or can be used by users from other organizations as well.

4. If you are developing a web app, configure the Redirect URI. For local development, it looks like this: http://localhost:3000.

Here’s a basic example of how app registration would look in code:

{
  "client_id": "YOUR_CLIENT_ID",
  "tenant_id": "YOUR_TENANT_ID",
  "redirect_uri": "http://localhost:3000"
}

Now that our app is registered, we can start fetching data using Microsoft Graph. We’ll be using the library. Microsoft Graph Toolkit (MGT)This makes the process much simpler.

Step 2: Install Microsoft Graph Toolkit

First, install the MGT package.

npm install /mgt

Your app needs to set up a provider to handle authentication and make it easier to call the Microsoft Graph API.

Step 3: Set up authentication

Create graphService.js Files to configure the provider:

import { Providers, MsalProvider } from '@microsoft/mgt';

export const initGraph = () => {
  if (!Providers.globalProvider) {
    Providers.globalProvider = new MsalProvider({
      clientId: 'YOUR_CLIENT_ID',
      scopes: ['User.Read', 'Files.Read', 'Mail.Read', 'Chat.Read']
    });
  }
};

This snippet sets up the authentication process using your app registration details.

Once authentication is set up, you can start importing data such as files, emails, and chats into your app. Let’s look at a few ways to do this.

Step 4: Import and display files

You can import files related to a specific project or client. Here’s how.

import { graph } from '@microsoft/mgt';

const getFiles = async (query) => {
  const response = await graph.api('/me/drive/search(q=\'' + query + '\')')
    .get();
  return response.value;
};

// Example usage:
getFiles('ProjectX').then(files => {
  console.log(files);
});

Step 5: Simplify using MGT components

Instead of writing the code above, you can use MGT’s built-in components to fetch and display data with minimal code.

This one line of code will automatically pull in and display your files. It’s simple, powerful, and easy to implement.