Quick Answer
The correct answer is Azure AI Language and Azure AI Search, which together form the backbone of a custom question-answering solution. Azure AI Language’s Custom Question Answering feature (formerly QnA Maker) handles the authoring of question-answer pairs and orchestrates the user query flow, while Azure AI Search provides the underlying indexing and retrieval engine that enables semantic ranking and scalable search across the knowledge base. On the Microsoft Azure AI Engineer Associate AI-102 exam, this pairing tests your understanding of how managed AI services compose a complete pipeline—a common trap is assuming Azure AI Language alone suffices, but without Azure AI Search the solution lacks the robust retrieval and ranking needed for production. To remember this, think of the “Q&A duo”: Custom Question Answering builds the brain (the knowledge base), and Azure AI Search provides the muscle (fast, relevant retrieval). A useful mnemonic is “Language learns, Search serves.”
This AI-102 practice question tests your understanding of plan and manage an azure ai solution. 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.
Which TWO Azure services are used together to build a custom question-answering solution?
Azure AI Language (Custom Question Answering)
Custom Question Answering builds a knowledge base from documents.
Azure AI Computer Vision
Why wrong: Computer Vision analyzes images.
Azure AI Speech
Why wrong: Speech is for audio processing, not Q&A.
Azure AI Search
Azure AI Search indexes the Q&A content for fast retrieval.
Azure AI Translator
Why wrong: Translator handles language translation.
Answer choices
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's Custom Question Answering (formerly QnA Maker) provides the core service for building a knowledge base of question-answer pairs and processing user queries. Azure AI Search acts as the underlying search index and retrieval engine, enabling the solution to scale, perform semantic ranking, and return relevant answers from the knowledge base. Together, they form a complete custom Q&A pipeline: Custom Question Answering for authoring and orchestration, and Azure AI Search for indexing and retrieval.
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.
Azure AI Language (Custom Question Answering)
Why this is correct
Custom Question Answering builds a knowledge base from documents.
Related concept
Read the scenario before looking for a memorised answer.
Azure AI Computer Vision
Why it's wrong here
Computer Vision analyzes images.
Azure AI Speech
Why it's wrong here
Speech is for audio processing, not Q&A.
Azure AI Search
Why this is correct
Azure AI Search indexes the Q&A content for fast retrieval.
Related concept
Read the scenario before looking for a memorised answer.
Azure AI Translator
Why it's wrong here
Translator handles language translation.
Common exam traps
The trap here is that 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.
Detailed technical explanation
Under the hood, Custom Question Answering uses a combination of a language model and a search index (Azure AI Search) to match user queries against a set of Q&A pairs. The service supports active learning, where it suggests alternative phrasings based on user feedback, and uses Azure AI Search's semantic ranking to improve answer relevance. In a real-world scenario, a company might ingest product documentation into Custom Question Answering, and Azure AI Search handles the indexing of thousands of documents, enabling fast, accurate responses even with large datasets.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
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FAQ
Plan and manage an Azure AI solution — This question tests Plan and manage an Azure AI solution — Read the scenario before looking for a memorised answer..
The correct answer is: Azure AI Language (Custom Question Answering) — Azure AI Language's Custom Question Answering (formerly QnA Maker) provides the core service for building a knowledge base of question-answer pairs and processing user queries. Azure AI Search acts as the underlying search index and retrieval engine, enabling the solution to scale, perform semantic ranking, and return relevant answers from the knowledge base. Together, they form a complete custom Q&A pipeline: Custom Question Answering for authoring and orchestration, and Azure AI Search for indexing and retrieval.
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 24, 2026
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.
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