Microsoft Power Automate Tutorials || Module 21 : Invoice process With AI Builder ( Form Processing)

Introduction to Power Automate and AI Model for Invoice Processing

Overview of the Tutorial

• The tutorial focuses on building an AI model using AI Builder to automate the invoice processing workflow.

• It highlights the challenges companies face in manually processing large volumes of invoices from various sources, which is time-consuming.

Steps to Create an AI Model

• The process consists of five steps:

1. Create an AI model tailored to business needs.

2. Train and publish the model.

3. Create a flow for receiving invoice documents.

4. Utilize the AI model within flows.

5. Store extracted data in appropriate data sources like Excel or databases.

Creating an AI Model for Invoice Processing

Initial Setup

• Users must log into flow.microsoft.com and navigate to AI Builder to start creating their invoice processing model.

• Various pre-built models are available, including options for form processing, which is essential for handling PDF invoices.

Document Requirements

• To create a successful model, at least five documents with identical layouts are required; consistency in document format is crucial for effective training.

Best Practices and Document Collection

Guidelines for Document Selection

• Use simple documents with primary text; avoid those with excessive images or checkboxes as they complicate processing.

Adding Documents to the Model

• A collection must be created that includes all necessary sample documents, which can be uploaded from local storage or cloud services like SharePoint or Azure Blob Storage.

Analyzing and Tagging Documents

Document Analysis Process

• After uploading, users need to analyze the documents so that the AI can learn how to extract relevant information effectively.

Tagging Fields

• Each field (invoice number, name, amount) must be tagged accurately across all documents during this phase to ensure proper data extraction later on.

Training and Publishing the Model

Training Phase

• Once tagging is complete, users can train their model by clicking on 'train', which may take some time depending on document complexity.

Publishing the Model

• After training completion, users should publish their model so it can be utilized in Power Automate and Power Apps environments.

Testing and Using the Published Model

Quick Testing Procedure

• Users can perform a quick test by uploading a new invoice document; successful extraction will show confidence scores indicating accuracy of captured fields (invoice number, name, amount).

Creating a Flow for Invoice Processing

Setting Up Email Triggering Flow

• A new flow is created using Gmail as a trigger point; it activates when emails containing PDF attachments arrive in the inbox.

Mapping Data into Excel

• The final step involves mapping extracted data from invoices into designated columns (invoice number, name, amount), ensuring seamless integration into Excel tables upon email receipt.

Conclusion of Tutorial

Summary of Achievements

• The tutorial concludes by summarizing how users have learned to create an AI model for invoice processing and integrate it within automated workflows effectively.