AI-102 Plan and manage an Azure AI solution Practice Question
Which TWO Azure services are used together to build a custom question-answering solution?
⚠ Common exam trap
Candidates often assume Azure AI Speech or Azure AI Translator are needed for a 'custom' solution, but the core requirement is a searchable knowledge base, which is provided by Azure AI Search, not by speech or translation services.
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 AI Language (Custom Question Answering)
Azure AI Language (Custom Question Answering) is correct because it provides the natural-language processing layer that ingests FAQ documents, URLs, and structured sources to create a knowledge base and returns precise answers to user questions. Azure AI Search is correct because it is the underlying retrieval engine that indexes the knowledge base content and performs the semantic/keyword search that Custom Question Answering relies on to match questions to answers. Together they form the standard architecture for a custom question-answering solution: AI Language builds and manages the knowledge base, while AI Search stores and queries the indexed content. Azure AI Computer Vision is for image analysis (OCR, object detection), Azure AI Speech handles speech-to-text/text-to-speech, and Azure AI Translator performs language translation, none of which are required components for building the question-answering knowledge base and retrieval pipeline.
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 (Custom Question Answering)
Why this is correct
Azure AI Language's Custom Question Answering feature holds the question-and-answer knowledge base, project, and trained model that matches user queries to answers. It satisfies the scenario by supplying the language understanding and answer-generation component of the custom question-answering solution.
- ✗
Azure AI Computer Vision
Why it's wrong here
Azure AI Computer Vision performs image classification, OCR and spatial analysis; it processes pixels, not text corpora, so it cannot supply question-answering knowledge. It would be correct for extracting text from scanned documents, but custom question answering needs Language service and Azure AI Search.
- ✗
Azure AI Speech
Why it's wrong here
Speech performs speech-to-text and text-to-speech; it produces no indexed question-and-answer store, so it cannot pair with Language service to answer queries. It is tempting as another Azure AI Service handling natural language, and it would be correct when the solution must transcribe audio or synthesise spoken responses.
- ✓
Azure AI Search
Why this is correct
Azure AI Search indexes the knowledge base content and performs the retrieval that surfaces candidate answers for a query. It satisfies the scenario by providing the search and ranking layer that Custom Question Answering queries, forming the retrieval half of the combined solution.
- ✗
Azure AI Translator
Why it's wrong here
Azure AI Translator performs text translation between languages; it plays no part in question-answering, which pairs Azure AI Search with Azure AI Language's question-answering capability. Translator is tempting when a solution must handle multilingual content, but translation alone cannot index or answer questions.
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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.