Building Smart Solutions with AI Builder and Microsoft Syntex

What is Artificial Intelligence

Artificial Intelligence or AI is a term frequently used and overused. This brief introduction will give you an idea what AI is and how it can help your organization with recurring business problems.

• What is AI?
• How to use AI Efficiently

Introducing AI Builder in Power Platform

AI Builder is a central service that can be used throughout the Power Platform. This module introduces the Power Platform and the AI Builder tool to embed AI into your Power Apps and Power Automate flows.

• What is AI Builder
• Introducing the Power Platform
• Licensing Requirements for AI Builder
• AI Builder Custom and Prebuilt Models
• AI Model Deployment Pipeline
• LAB: Setup Trial Environment for AI Builder

Train your Model with Microsoft Dataverse

Before we can use AI models, we first need to train them. This module covers how to prepare data that will be used to train the model.

• Discovering Text-based AI Models: Sentiment, Text Translation, Language Detection, Entity Extraction...
• What is Microsoft Dataverse?
• Loading data in Microsoft Dataverse Tables
• Train your Model
• Lab: Train a Category Classification Model

Using AI Models in Power Platform

Creating and training your models is one thing, implementing them correctly is another. You need to build Power Apps Canvas Apps or Power Automate flows so your models can flourish.

• Import Data to a Power Automate Flow
• Apply AI Model and Process Results
• Using Power Apps Prebuilt AI Controls
• Extracting Model Results in Canvas Apps
• Lab: Detect and Store Objects in Images

AI Builder Prediction Models

Microsoft Dataverse is an integral tool for makers, included in the Power Platform. Data stored there can be processed to predict hard-to-measure or time-critical data. AI Can help us process that information and predict this metadata.

• Import Structured Data in a Table
• Predict Future Outcomes using a Custom Model
• Use Model Results Throughout Microsoft 365
• Lab: Predict Microsoft Dataverse Columns using AI

Document-Based Models

Every day, invoices, receipts, IDs, and a bunch of other documents need to be processed and stored in your company. With document-based AI models, you can process these in an automated way and store the extracted data wherever you like.

• Compare Document Processing Models
• Collect Data and Train Model
• Use any Model in Apps or Flows
• Lab:

SharePoint Document Processing in Microsoft Syntex

Microsoft Syntex is a Content Understanding and Processing service that uses AI to find and organize your documents. Rather than manually uploading hundreds of documents and extracting metadata manually, Microsoft Syntex can automate that process for you.

• Microsoft Syntex Introduction
• Setup SharePoint for Syntex
• Microsoft Syntex Model Types
• Structured Document Processing
• Classify and Detect Unstructured Data
• Model Metadata Enhancement with Taxonomy
• Implement and use Models in SharePoint

Image Detection and Classification

By training your own AI Models on predefined data, you can allow processes to automatically classify images or even detect your organization-specific objects in these images.

• Classifying vs Detecting Models
• Prepare Images with the Lobe App
• Train model by Classifying and Detecting Images
• Lab: Create an Image Detection Model

Managing AI Builder Models

Your custom trained models always have room for improvement. In this module, you will learn how you can manage your custom models, retrain them, or even share them with your colleagues or others. You will also learn how to add security to your models.

• Mange, Retrain and Publish Different Model Versions
• Share and Distribute your Model
• Continuously Improve your Model
• Secure your AI Models with Role Based Security
• Lab: Set Up Continuous Improvement and Administer your Models