- A
Amazon Transcribe and Amazon Polly
Why wrong: Transcribe converts speech to text, Polly converts text to speech — neither extracts text from documents.
- B
Amazon Kendra and Amazon Lex
Why wrong: Kendra is an enterprise search service; Lex is for conversational interfaces.
- C
Amazon Textract and Amazon Translate
Textract extracts text from scanned documents, and Translate handles multilingual translation.
- D
Amazon Rekognition and Amazon Comprehend
Why wrong: Rekognition is for image analysis, not document text extraction; Comprehend is for NLP but doesn't extract text from images.
Question 48 of 1,000
AIF-C01 AI and ML Fundamentals Practice Question
This AIF-C01 practice question tests your understanding of ai and ml fundamentals. 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 firm must extract text from scanned loan application forms to automate data entry. The forms are in various languages. Which combination of AWS AI services should be used?
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
✓
Amazon Textract and Amazon Translate
Amazon Textract is designed to extract text and data from scanned documents, including forms, using OCR (Optical Character Recognition). Amazon Translate then converts the extracted text from various languages into a target language, enabling automated data entry across multilingual loan applications. Together, they directly address the requirement of extracting text from scanned forms in multiple languages.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon Transcribe and Amazon Polly
Why it's wrong here
Transcribe converts speech to text, Polly converts text to speech — neither extracts text from documents.
- ✗
Amazon Kendra and Amazon Lex
Why it's wrong here
Kendra is an enterprise search service; Lex is for conversational interfaces.
- ✓
Amazon Textract and Amazon Translate
Why this is correct
Textract extracts text from scanned documents, and Translate handles multilingual translation.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon Rekognition and Amazon Comprehend
Why it's wrong here
Rekognition is for image analysis, not document text extraction; Comprehend is for NLP but doesn't extract text from images.
Common exam traps
Common exam trap: answer the scenario, not the keyword
AWS often tests the distinction between OCR-based extraction (Textract) and image analysis (Rekognition), leading candidates to mistakenly choose Rekognition for document text extraction when it is designed for object/face detection, not form data extraction.
Detailed technical explanation
How to think about this question
Amazon Textract uses deep learning models to detect and extract text, tables, and key-value pairs from scanned documents, supporting both printed and handwritten text. Amazon Translate uses neural machine translation (NMT) models to translate text between 75+ languages, preserving context and structure. In a real-world scenario, a loan application in Spanish would be processed by Textract to extract fields like 'Name' and 'Income', then Translate converts the extracted text to English for downstream processing.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
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
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. 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
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this AIF-C01 question test?
AI and ML Fundamentals — This question tests AI and ML Fundamentals — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Amazon Textract and Amazon Translate — Amazon Textract is designed to extract text and data from scanned documents, including forms, using OCR (Optical Character Recognition). Amazon Translate then converts the extracted text from various languages into a target language, enabling automated data entry across multilingual loan applications. Together, they directly address the requirement of extracting text from scanned forms in multiple languages.
What should I do if I get this AIF-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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