Quick Answer
The answer is Amazon Bedrock. This service provides a managed API that gives developers access to a choice of high-performing foundation models from leading AI companies like AI21 Labs, Anthropic, and Amazon itself, making it the correct choice for using a pre-trained model for sentiment analysis without any customization. On the AWS Certified AI Practitioner AIF-C01 exam, this question tests your ability to distinguish between purpose-built AI services and the newer foundation model platform; a common trap is confusing Bedrock with Amazon Comprehend, which handles natural language processing but does not offer foundation model APIs. Remember the memory tip: Bedrock is the "base" for building with foundation models, while other services like Rekognition, Textract, and Comprehend are specialized tools for specific tasks.
This AIF-C01 practice question tests your understanding of applications of foundation models. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 company wants to use a pre-trained foundation model for sentiment analysis without any customization. Which Amazon Machine Learning service provides access to foundation models via API?
Amazon Textract
Why wrong: Textract extracts text from documents, not sentiment analysis.
Amazon Comprehend
Why wrong: Comprehend offers built-in sentiment analysis but is not a foundation model API.
Amazon Rekognition
Why wrong: Rekognition provides image and video analysis, not text foundation models.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Amazon Bedrock
Amazon Bedrock provides a managed API to access foundation models from providers like AI21 Labs, Anthropic, and Amazon. Amazon Rekognition is for images; Textract for document text; Comprehend for natural language processing (but not foundation models per se).
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
For each option: why learners choose it and why it is or isn't the right answer here.
Amazon Textract
Why it's wrong here
Textract extracts text from documents, not sentiment analysis.
Amazon Comprehend
Why it's wrong here
Comprehend offers built-in sentiment analysis but is not a foundation model API.
Amazon Rekognition
Why it's wrong here
Rekognition provides image and video analysis, not text foundation models.
Common exam traps
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
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.
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
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
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 AIF-C01 NAT questions on configuration and troubleshooting.
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FAQ
Applications of Foundation Models — This question tests Applications of Foundation Models — Static NAT maps one inside address to one outside address..
The correct answer is: Amazon Bedrock — Amazon Bedrock provides a managed API to access foundation models from providers like AI21 Labs, Anthropic, and Amazon. Amazon Rekognition is for images; Textract for document text; Comprehend for natural language processing (but not foundation models per se).
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 AIF-C01 NAT questions on configuration and troubleshooting.
Static NAT maps one inside address to one outside address.
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Last reviewed: Jun 23, 2026
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AIF-C01 exam.
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