- A
Document AI
Why wrong: Document AI is for document processing, not retrieval for GenAI.
- B
Vertex AI Studio
Why wrong: Studio is for prompt engineering, not the retrieval/agent system.
- C
Vertex AI RAG Engine
RAG Engine handles retrieval of relevant document chunks.
- D
Model Garden
Why wrong: Model Garden provides models but not retrieval or agent building.
- E
Vertex AI Agent Builder
Agent Builder enables creating the chatbot with integrated RAG.
Question 184 of 997
Generative AI Leader Applying Generative AI in Business Practice Question
This Generative AI Leader practice question tests your understanding of applying generative ai in business. 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 is implementing a GenAI-powered internal knowledge base chatbot. They need to ensure answers are based on company documents and the system should be easy to update as documents change. Which TWO components should they 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
✓
Vertex AI RAG Engine
Option C (Vertex AI RAG Engine) is correct because it provides a managed Retrieval-Augmented Generation (RAG) service that directly ingests company documents, indexes them into a vector database, and retrieves relevant chunks to ground the chatbot's answers. This ensures responses are based on the latest document content, and the system is easy to update by simply re-indexing or refreshing the document source without retraining the model.
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.
- ✗
Document AI
Why it's wrong here
Document AI is for document processing, not retrieval for GenAI.
- ✗
Vertex AI Studio
Why it's wrong here
Studio is for prompt engineering, not the retrieval/agent system.
- ✓
Vertex AI RAG Engine
Why this is correct
RAG Engine handles retrieval of relevant document chunks.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Model Garden
Why it's wrong here
Model Garden provides models but not retrieval or agent building.
- ✓
Vertex AI Agent Builder
Why this is correct
Agent Builder enables creating the chatbot with integrated RAG.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between general-purpose AI services (like Document AI or Model Garden) and specialized RAG/agent-building services, so candidates mistakenly pick Document AI thinking it handles document-based Q&A, but it lacks retrieval and grounding capabilities.
Detailed technical explanation
How to think about this question
Under the hood, Vertex AI RAG Engine uses a vector database (e.g., Vertex AI Vector Search) to store document embeddings and performs approximate nearest neighbor (ANN) search at query time to retrieve the most relevant text chunks. The retrieved chunks are then injected into the prompt context window of the LLM, enabling grounded generation without fine-tuning. In a real-world scenario, when a company updates a policy PDF, the RAG engine can re-ingest only the changed document, and subsequent queries automatically use the new content without any model retraining.
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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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Applying Generative AI in Business — study guide chapter
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FAQ
Questions learners often ask
What does this Generative AI Leader question test?
Applying Generative AI in Business — This question tests Applying Generative AI in Business — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Vertex AI RAG Engine — Option C (Vertex AI RAG Engine) is correct because it provides a managed Retrieval-Augmented Generation (RAG) service that directly ingests company documents, indexes them into a vector database, and retrieves relevant chunks to ground the chatbot's answers. This ensures responses are based on the latest document content, and the system is easy to update by simply re-indexing or refreshing the document source without retraining the model.
What should I do if I get this Generative AI Leader 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.
About these practice questions
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Last reviewed: Jul 4, 2026
This Generative AI Leader practice question is part of Courseiva's free Google Cloud 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 Generative AI Leader exam.
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