You create an automated Power Automate flow.
The flow monitors incoming emails.
Based on the email content, it redirects them to the appropriate departments, like sales, finance, or management.
When an email comes with a management report, flow creates a report summary, puts it as the new email content, and sends this email to the management team with the attached original email.
Please select two AI builder models that you should use for your flow.
Click on the arrows to vote for the correct answer
A. B. C. D. E.Correct Answers: C and E
AI Builder provides several prebuilt Machine Learning cognitive models that users can use in their Power Platform products.
AI Builder model list includes models like prediction, object detection, form processor, text classification, category classification, entity extraction, etc.
If your business needs do not match the out-of-box models, you can train your models based on your data.
In this task, we need to use the Category classification model to determine an email destination and forward an email to the appropriate department.
If the Category classification model detects that email is for the management and contains a report, the flow should use the Key Phrase extraction model to create a report summary.
Option C is correct because the Key Phrase Extraction model analyzes the text and extracts the most important phrases.
This model creates the text summaries.
Option E is correct because the Category classification model analyzes an email text, determines the text language, and classifies text according to the predefined or trained categories.
Option A is incorrect because the Entity extraction model analyzes an email text, determines the text language, and extracts specific entities defined in a model.
The standard model includes 28 such entities, like email address, date-time, phone number, etc.
You can add other entities by training your model.
But Entity extraction model does not extract key phrases from a report or provide a category classification of an email text.
Option B is incorrect because the Text recognition model extracts text from the images with printed or handwritten text.
But this model does not extract key phrases from a report or provide a category classification of an email text.
Option D is incorrect because the Sentiment Analysis model analyses text on positive, negative, or neutral sentiment.
But this model does not extract key phrases from a report or provide a category classification of an email text.
For more information about AI Builder models, please visit the below URLs:
In the given scenario, we need to create an automated Power Automate flow that monitors incoming emails and categorizes them based on their content, then performs specific actions accordingly. To accomplish this, we can leverage AI Builder models, which are pre-built machine learning models that can be easily integrated into Power Automate flows.
Out of the options provided, the two most relevant AI Builder models for this scenario are:
Category Classification: This model can be used to automatically categorize incoming emails based on their content. We can train the model to recognize patterns and keywords in the email body and subject, and assign them to specific categories such as sales, finance, or management. Once an email is categorized, we can use conditional logic in the Power Automate flow to perform specific actions based on its category, such as forwarding it to the appropriate department.
Key Phrase Extraction: This model can be used to extract important keywords and phrases from the email content. This can be useful for identifying specific topics or areas of interest mentioned in the email, which can then be used to trigger further actions in the flow. For example, if an email contains a management report, we can use the Key Phrase Extraction model to extract important keywords from the report, such as "revenue," "profits," or "growth," and then use these keywords to create a summary report that is sent to the management team.
In summary, Category Classification and Key Phrase Extraction are the two AI Builder models that are most relevant for this scenario. Category Classification can be used to categorize incoming emails, while Key Phrase Extraction can be used to extract important keywords and trigger further actions in the flow.