AI-900 Practice Question: Describe features of generative AI workloads on Azure
A company wants to build a chatbot that answers customer questions using only their internal knowledge base, which consists of several PDFs and Word documents. They do not want the chatbot to use any information from the model's pre-trained knowledge. Which Azure OpenAI feature should they use to achieve this?
⚠ Common exam trap
It's easy for candidates to confuse prompt engineering techniques (like setting temperature or using Prompt flow) with the data grounding mechanism provided by Azure OpenAI on your data, mistakenly thinking they can control knowledge sources through parameters or workflow tools.
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
✓
Azure OpenAI on your data
Azure OpenAI on your data allows you to connect Azure OpenAI models to your own data sources (such as PDFs and Word documents) and restrict the model to generate responses solely from that data, without using the model's pre-trained knowledge. This is achieved by indexing the documents into an Azure Cognitive Search index and using retrieval-augmented generation (RAG) to ground the model's responses in your specific content.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Content filtering
Why it's wrong here
Content filtering is a safety layer in Azure OpenAI that classifies prompts and completions to block harmful categories like hate, self-harm, or violence. It does not alter the underlying model's parametric knowledge or introduce a closed corpus. Thus it may block outputs, but it cannot force responses to originate solely from your company documents, so it fails the grounding requirement.
- ✗
Prompt flow
Why it's wrong here
Prompt flow is a visual development environment for designing, evaluating, and orchestrating LLM-based workflows, including connections to various tools. It helps you build and test a chatbot pipeline, but it is agnostic about data sources and does not inherently change the model's knowledge to be your data. A flow could use your data only if you explicitly add retrieval steps, so by itself it does not satisfy the only-your-data constraint.
- ✓
Azure OpenAI on your data
Why this is correct
Azure OpenAI on your data grounds the model by connecting it to your indexed corpus—such as PDFs, web pages, or databases—using Azure AI Search or similar retrieval. During inference, the service retrieves relevant chunks and supplies them to the model as augmented context, which the model uses to form answers, effectively overriding unsupported general knowledge. This is why it is the appropriate mechanism for a chatbot restricted to your company's data.
- ✗
Temperature parameter
Why it's wrong here
The temperature parameter is a sampling control that adjusts the probability distribution over the model's output tokens, affecting randomness, creativity, and repetitiveness. It has no bearing on the information source or the model's latent knowledge. Changing temperature cannot restrict answers to company data; it only changes how varied or conservative the generated responses are.
Go deeper
Related to this question
Learn chapter
Azure Machine Learning Studio
Key term
RAG
Retrieval-Augmented Generation (RAG) is a technique that combines information retrieval with text generation to produce more accurate and contextually relevant answers from large language models.
Key term
Search index
A search index is a data structure that stores a mapping of content to locations, enabling fast and efficient information retrieval in search systems.
About these practice questions
Courseiva writes every AI-900 question from scratch — 985 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-900 practice question is part of Courseiva's free Microsoft 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 AI-900 exam.