- A
Use the General Document model
The General Document model extracts key-value pairs and entities from documents without training, and for common invoice fields it provides reasonable accuracy without manual labeling.
- B
Use the Read API
Why wrong: The Read API extracts printed and handwritten text but does not extract structured fields.
- C
Use a custom neural model
Why wrong: Custom neural models require labeled training data, so they do not meet the requirement of no manual labeling.
- D
Use the Layout API
Why wrong: The Layout API extracts text, tables, and selection marks but not custom key-value pairs.
Question 89 of 993
AI-102 General Document model Practice Question
This AI-102 practice question tests your understanding of implement computer vision solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. A key principle to apply: general Document model. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are building an application that processes scanned invoices to extract key fields such as total amount, invoice date, and vendor name. The application uses Azure AI Document Intelligence. You need to ensure high accuracy for field extraction without manual labeling. Which feature should you use?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use the General Document model
The General Document model in Azure AI Document Intelligence can extract common fields like total amount, invoice date, and vendor name from invoices without requiring any labeled training data. While a custom neural model would offer higher accuracy, it requires manual labeling of sample documents, which contradicts the requirement of no manual labeling. Therefore, the General Document model is the appropriate choice.
Key principle: General Document model
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use the General Document model
Why this is correct
The General Document model extracts key-value pairs and entities from documents without training, and for common invoice fields it provides reasonable accuracy without manual labeling.
Related concept
General Document model
- ✗
Use the Read API
Why it's wrong here
The Read API extracts printed and handwritten text but does not extract structured fields.
- ✗
Use a custom neural model
Why it's wrong here
Custom neural models require labeled training data, so they do not meet the requirement of no manual labeling.
- ✗
Use the Layout API
Why it's wrong here
The Layout API extracts text, tables, and selection marks but not custom key-value pairs.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Candidates often think a custom neural model is needed for high accuracy on invoice fields, but custom models require manual labeling. The General Document model extracts common fields like total amount, invoice date, and vendor name without any labeling, meeting the requirement. Others may confuse the Read API (text) or Layout API (structure) as suitable for field extraction.
Detailed technical explanation
How to think about this question
Custom neural models use a transformer-based architecture that learns field semantics from as few as five labeled documents, enabling high accuracy even with varied invoice layouts. Under the hood, the model aligns visual features (e.g., text position, font) with textual context to predict field values, which is critical for invoices where fields appear in different locations. In real-world scenarios, this avoids the need for manual labeling of hundreds of documents, reducing deployment time while maintaining over 90% accuracy for key fields.
KKey Concepts to Remember
- General Document model
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
General Document model
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. General Document model Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
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Review general Document model, then practise related AI-102 questions on the same topic to reinforce the concept.
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FAQ
Questions learners often ask
What does this AI-102 question test?
Implement computer vision solutions — This question tests Implement computer vision solutions — General Document model.
What is the correct answer to this question?
The correct answer is: Use the General Document model — The General Document model in Azure AI Document Intelligence can extract common fields like total amount, invoice date, and vendor name from invoices without requiring any labeled training data. While a custom neural model would offer higher accuracy, it requires manual labeling of sample documents, which contradicts the requirement of no manual labeling. Therefore, the General Document model is the appropriate choice.
What should I do if I get this AI-102 question wrong?
Review general Document model, then practise related AI-102 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
General Document model
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Last reviewed: Jul 4, 2026
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