Quick Answer
The correct answer is Azure Video Indexer. This service is purpose-built for analyzing videos stored in Azure Blob Storage, using pre-trained AI models to detect objects, generate timestamps, and extract rich metadata like scene segmentation and speech transcripts. On the Microsoft Azure AI Engineer Associate AI-102 exam, this scenario tests your ability to match video analysis workloads to the appropriate Azure AI service, often contrasting Video Indexer with Computer Vision or Custom Vision—a common trap is choosing Computer Vision, which handles images but lacks native video timeline generation. Remember that Video Indexer is the only service that directly ingests video from Blob Storage and outputs a structured timeline of detected objects and events. A helpful memory tip: think “Video Indexer = video + index + timeline,” linking its core function of indexing video content with precise timestamps for every detected object.
This AI-102 practice question tests your understanding of implement computer vision solutions. 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.
You need to analyze videos stored in Azure Blob Storage to detect objects and generate timestamps. Which Azure service should you use?
Azure Custom Vision
Why wrong: For custom image models.
Azure Form Recognizer
Why wrong: For document analysis.
Azure Computer Vision
Why wrong: Primarily for images.
Azure Video Indexer
Video analysis with object detection and timestamps.
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 Video Indexer
Azure Video Indexer (D) is the correct choice because it is specifically designed to analyze videos, extracting insights such as object detection, scene segmentation, and timestamps. It uses AI models to process video content stored in Azure Blob Storage and generates a timeline of detected objects, making it ideal for this scenario.
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 Custom Vision
Why it's wrong here
For custom image models.
Azure Form Recognizer
Why it's wrong here
For document analysis.
Azure Computer Vision
Why it's wrong here
Primarily for images.
Azure Video Indexer
Why this is correct
Video analysis with object detection and timestamps.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
The trap here is that candidates often confuse Azure Computer Vision (image analysis) with video analysis, overlooking that Computer Vision lacks native video processing and timestamp generation, while Video Indexer is the dedicated service for end-to-end video insights.
Detailed technical explanation
Azure Video Indexer leverages pre-built AI models for computer vision, speech, and natural language processing to analyze video streams. Under the hood, it decodes video into frames, applies object detection models (e.g., YOLO-based or ResNet-based), and outputs a JSON timeline with timestamps for each detected object. In a real-world scenario, you could upload surveillance footage to Blob Storage, index it with Video Indexer, and retrieve a list of objects (e.g., 'person', 'car') with exact timestamps for forensic analysis.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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FAQ
Implement computer vision solutions — This question tests Implement computer vision solutions — Read the scenario before looking for a memorised answer..
The correct answer is: Azure Video Indexer — Azure Video Indexer (D) is the correct choice because it is specifically designed to analyze videos, extracting insights such as object detection, scene segmentation, and timestamps. It uses AI models to process video content stored in Azure Blob Storage and generates a timeline of detected objects, making it ideal for this scenario.
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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