AI-102 Practice Question: Implement knowledge mining and information extraction solutions
Which TWO Azure AI services can be used to extract text from images as part of a knowledge mining pipeline?
⚠ Common exam trap
A common mix-up: candidates confuse Azure AI Computer Vision's OCR capabilities with Azure AI Document Intelligence, but Document Intelligence is the dedicated service for structured document extraction in knowledge mining, while Computer Vision provides general-purpose image analysis and OCR without the same level of document-specific parsing.
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 Document Intelligence
Azure AI Document Intelligence (option B) is correct because its Read and Layout models perform OCR on documents and images, extracting printed and handwritten text along with structure for downstream knowledge mining enrichment. Azure AI Computer Vision (option C) is correct because its Read OCR feature (Image Analysis / Read API) extracts printed and handwritten text from images, a core skill in Azure AI Search cognitive skillsets. Azure AI Language (option A) is wrong because it handles text analytics such as entity recognition, sentiment, and key phrase extraction, not image OCR. Azure AI Video Indexer (option D) is wrong because it targets video and audio insights like transcription and face tracking, not still-image text extraction. Azure AI Custom Vision (option E) is wrong because it trains image classification and object detection models, not text recognition.
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
Why it's wrong here
Azure AI Language processes existing text for sentiment, entities, and key phrases; it accepts no image input and performs no optical character recognition. It belongs in a pipeline stage after text exists, not at the extraction step from scanned images.
- ✓
Azure AI Document Intelligence
Why this is correct
Document Intelligence's Read model performs OCR, returning printed and handwritten text from images and PDFs, and integrates into enrichment pipelines via the built-in Document Intelligence skill. It satisfies the requirement to extract text from images as part of knowledge mining.
- ✓
Azure AI Computer Vision
Why this is correct
Computer Vision's Read API performs OCR on images, extracting printed and handwritten text, and is exposed as a built-in Azure AI Search skill. It satisfies the requirement to extract text from images within a knowledge mining pipeline.
- ✗
Azure AI Video Indexer
Why it's wrong here
Video Indexer extracts speech transcripts, faces, and topics from video and audio streams, not characters from still images. It suits media archive enrichment; the pipeline's image OCR requirement is met by Azure AI Vision instead.
- ✗
Azure AI Custom Vision
Why it's wrong here
Custom Vision trains image classification and object detection models, returning labels and bounding boxes rather than recognised characters. It fits bespoke visual tagging tasks; OCR text extraction from images requires Azure AI Vision's Read capability instead.
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