AI-102 Practice Question: Implement natural language processing solutions
Which TWO Azure AI services can be used to build a multilingual question-answering bot that retrieves answers from a knowledge base of documents?
⚠ Common exam trap
The AI-102 exam often tests the distinction between services that process language (like LUIS or Translator) versus services that combine retrieval with generation (like Azure OpenAI with RAG) to answer questions from documents, leading candidates to mistakenly choose LUIS or Translator for a task that requires document-based Q&A.
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 Service with a RAG pattern
Azure OpenAI Service with a RAG (Retrieval-Augmented Generation) pattern is correct because it combines a large language model with a retrieval layer that fetches relevant passages from a document knowledge base (e.g., via Azure AI Search) and generates grounded, multilingual answers. Azure AI Language - Custom Question Answering is correct because it is purpose-built to create a knowledge base from documents and FAQs and return precise answers to natural-language questions, including multilingual support. Azure AI Language Understanding (LUIS) is not correct because it only performs intent and entity extraction, not document retrieval or answer generation. Azure AI Translator is not correct because it only translates text between languages and does not retrieve or answer from a knowledge base. Azure AI Document Intelligence is not correct because it only extracts structured data (text, tables, key-value pairs) from documents and does not provide question-answering retrieval.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure AI Language Understanding (LUIS)
Why it's wrong here
LUIS maps utterances to intents and entities; it performs no document retrieval or answer extraction, so it cannot serve answers from a knowledge base. It would be correct for routing a user's phrasing to the right intent before a separate search service returns the passage.
- ✓
Azure OpenAI Service with a RAG pattern
Why this is correct
Azure OpenAI Service with retrieval-augmented generation embeds documents in a search index, retrieves relevant chunks per query, and prompts the model to answer in the user's language. This satisfies the multilingual requirement because the underlying model handles translation and generation natively.
- ✗
Azure AI Translator
Why it's wrong here
Azure AI Translator performs text and document translation between languages; it holds no knowledge base, indexing or answer-retrieval capability. It tempts because multilingual bots need translation, but the retrieval component must come from Azure AI Search paired with question answering, not Translator alone.
- ✗
Azure AI Document Intelligence
Why it's wrong here
Document Intelligence extracts structured fields, tables and text from forms via OCR and layout models; it holds no answer index or ranking engine, so it cannot retrieve passages from a knowledge base. It would be correct for parsing uploaded invoices or PDFs into JSON before that content is indexed elsewhere.
- ✓
Azure AI Language - Custom Question Answering
Why this is correct
Custom Question Answering stores document-derived question-and-answer pairs and matches user queries against them, with multilingual support for both ingestion and querying. It directly satisfies the requirement to retrieve answers from a knowledge base of documents.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-102 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-102 exam.