Quick Answer
The answer is Amazon Bedrock. This is the correct choice because Bedrock is a fully managed serverless generative AI service that provides access to foundation models from providers like Anthropic and Stability AI through a simple API, enabling you to generate product descriptions from keywords without provisioning any underlying infrastructure. On the AWS Certified AI Practitioner AIF-C01 exam, this question tests your understanding of which service is purpose-built for serverless generative AI tasks versus services like SageMaker, which requires managing endpoints, or Lambda, which is for custom code execution rather than direct foundation model access. A common trap is confusing Lambda’s serverless compute with Bedrock’s serverless AI service—remember, Bedrock is the only one that gives you pre-trained FMs via API with zero infrastructure. Memory tip: Bedrock is the “bedrock” for serverless generative AI—just call the API and go.
This AIF-C01 practice question tests your understanding of fundamentals of generative ai. 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 startup wants to generate product descriptions from a few keywords using a foundation model. They need a fully managed serverless solution that requires no infrastructure setup. Which AWS service should they use?
Amazon SageMaker
Why wrong: SageMaker is not serverless for generative AI; it requires provisioning instances.
Amazon Comprehend
Why wrong: Comprehend is for NLP tasks like sentiment analysis, not generative text.
AWS Lambda
Why wrong: Lambda is compute, not a generative AI service.
Amazon Bedrock
Bedrock is a serverless service offering foundation models via API.
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 is a fully managed serverless service that provides access to foundation models (FMs) from leading AI providers via a simple API, making it ideal for generating product descriptions from keywords without any infrastructure management. It directly supports generative AI tasks like text generation, unlike other AWS services that focus on different ML or NLP capabilities.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Amazon SageMaker
Why it's wrong here
SageMaker is not serverless for generative AI; it requires provisioning instances.
Amazon Comprehend
Why it's wrong here
Comprehend is for NLP tasks like sentiment analysis, not generative text.
AWS Lambda
Why it's wrong here
Lambda is compute, not a generative AI service.
Amazon Bedrock
Why this is correct
Bedrock is a serverless service offering foundation models via API.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
The trap here is that candidates may confuse Amazon SageMaker's managed ML capabilities with a serverless generative AI service, overlooking that SageMaker requires explicit infrastructure setup for model hosting, while Bedrock is purpose-built for serverless access to foundation models.
Detailed technical explanation
Amazon Bedrock exposes foundation models via a unified API using the InvokeModel or InvokeModelWithResponseStream operations, handling model hosting, scaling, and security automatically. Under the hood, it leverages model inference endpoints that are optimized for low latency and high throughput, and it supports features like model customization through fine-tuning and retrieval-augmented generation (RAG) with knowledge bases. In a real-world scenario, a startup could use Bedrock with a prompt like 'Generate a product description for a wireless mouse with keywords: ergonomic, rechargeable, silent clicks' and receive a coherent paragraph without provisioning any servers.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Fundamentals of Generative AI — This question tests Fundamentals of Generative AI — Read the scenario before looking for a memorised answer..
The correct answer is: Amazon Bedrock — Amazon Bedrock is a fully managed serverless service that provides access to foundation models (FMs) from leading AI providers via a simple API, making it ideal for generating product descriptions from keywords without any infrastructure management. It directly supports generative AI tasks like text generation, unlike other AWS services that focus on different ML or NLP capabilities.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 25, 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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