The answer is Azure AI Document Intelligence (Form Recognizer) with a custom model trained on check images. This service is specifically designed for document intelligence check processing handwritten signature extraction, combining OCR for printed account numbers with specialized handwriting recognition for handwritten amounts and signature presence detection. On the Microsoft Azure AI Engineer Associate AI-102 exam, this question tests your ability to distinguish between Azure’s document-focused AI services versus general-purpose computer vision tools. A common trap is selecting Azure AI Vision OCR, which handles general text but lacks the custom model training and field-level extraction needed for structured documents like checks. Remember: Document Intelligence is purpose-built for forms and documents, while Custom Vision is for object detection in images. Memory tip: think “Doc Intel for docs, Custom Vision for objects” — if the task involves extracting fields from a structured document, always reach for Document Intelligence first.
AI-102 Implement computer vision solutions 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. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. 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.
A financial services company is building a computer vision solution to automatically extract data from scanned checks. The solution must recognize handwritten amounts, printed account numbers, and signature presence. The company has a large dataset of labeled check images. They need high accuracy and the ability to retrain with new data. Which Azure service should they use?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure AI Document Intelligence (Form Recognizer) with a custom model trained on check images
Azure AI Document Intelligence (Form Recognizer) is optimized for document extraction, supports custom models, and handles handwriting and printed text. Custom Vision is for object detection. Azure AI Vision OCR is for general text extraction. Azure AI Language is for text analytics.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Azure AI Vision OCR with a custom dataset using Custom Vision
Why it's wrong here
Custom Vision does not support text extraction natively.
✗
Azure AI Language with custom entity recognition
Why it's wrong here
Requires text input, not images.
✓
Azure AI Document Intelligence (Form Recognizer) with a custom model trained on check images
Why this is correct
Supports custom extraction models for documents like checks.
Related concept
Static NAT maps one inside address to one outside address.
✗
Azure AI Vision Image Analysis with a custom model
Why it's wrong here
Not designed for document structure extraction.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
Static NAT maps one inside address to one outside address.
PAT allows many inside hosts to share one public address using ports.
Inside local and inside global describe the private and translated addresses.
NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
→Identify inside and outside interfaces first.
→Check whether the scenario needs static NAT, dynamic NAT or PAT.
→Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related AI-102 NAT questions on configuration and troubleshooting.
Implement computer vision solutions — This question tests Implement computer vision solutions — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Azure AI Document Intelligence (Form Recognizer) with a custom model trained on check images — Azure AI Document Intelligence (Form Recognizer) is optimized for document extraction, supports custom models, and handles handwriting and printed text. Custom Vision is for object detection. Azure AI Vision OCR is for general text extraction. Azure AI Language is for text analytics.
What should I do if I get this AI-102 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related AI-102 NAT questions on configuration and troubleshooting.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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Question Discussion
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