AI Builder Models for New Customer Registration and Self-Service Car Rent

Correct Answers: A and D

RentMe mobile application should use Text recognition and Entity extraction models.

A Text recognition model extracts text from the images with printed or handwritten text.

Using this model, you can extract information from the pictures of the driver's license, credit card and car's plates.

An Entity extraction model analyzes a 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.

You can use this model with Text recognition output to extract the data points (entities) from driver's license, credit card, and car's plates.

Then you can present to a user the extracted information for the review and create a new account.

Option B is incorrect because the Key Phrase Extraction model analyzes the text and extracts the most important phrases.

This model creates text summaries.

But it does not read a text in images and extract the data points from the text.

Option C is incorrect because the Sentiment Analysis model analyzes a text on positive, negative, or neutral sentiment.

But this model does not read a text in images and extract the data points from the text.

Option E is incorrect because the Category classification model analyzes a text, determines the text language, and classifies text according to the predefined or trained categories.

But this model does not read a text in images and extract the data points from the text.

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For the RentMe Power Apps app, the following AI builder models could be used:

1. Entity Extraction: Entity Extraction can be used to extract important information from the customer registration form such as the customer's name, address, contact details, etc. This model can help to automate the process of capturing this information and ensure that it is accurately recorded in the database.

2. Key Phrase Extraction: Key Phrase Extraction can be used to identify important phrases and keywords from the customer's feedback or comments during the rental process. This model can help to identify common themes and areas of concern, allowing the RentMe team to address these issues and improve the overall customer experience.

3. Sentiment Analysis: Sentiment Analysis can be used to analyze customer feedback and determine whether it is positive, negative or neutral. This model can help the RentMe team to quickly identify and address any negative feedback, while also allowing them to identify areas where they are doing well and where they can improve.

4. Text Recognition: Text Recognition can be used to capture information from images or scanned documents, such as a driver's license or a rental agreement. This model can help to automate the process of capturing this information, saving time and reducing errors.

5. Category Classification: Category Classification can be used to automatically categorize customer feedback or requests, such as complaints, inquiries, or suggestions. This model can help the RentMe team to prioritize and address customer needs more efficiently, leading to improved customer satisfaction.

In summary, the best AI builder models to use for the RentMe Power Apps app for new customer registration and self-service car rental would be Entity Extraction, Key Phrase Extraction, Sentiment Analysis, Text Recognition, and Category Classification. These models can help to automate and streamline various processes, while also improving the overall customer experience.