The correct answer is to create a composed model that includes the existing model and a new model trained on 5 contracts with the new layout. This works because a composed model in Azure Document Intelligence intelligently routes each incoming document to the best-matching sub-model based on layout similarity, allowing you to handle multiple document formats without retraining from scratch. On the AI-102 exam, this scenario tests your understanding of how composed models minimize manual labeling effort and cost while improving accuracy across varied layouts—a common trap is assuming you must retrain the entire model or use a prebuilt model. Remember, composed models are ideal when you have distinct layout variations but limited labeled data for each. Memory tip: think of a composed model as a “smart switchboard” that directs each document to its best-trained expert.
AI-102 Practice Question: Implement knowledge mining and document intelligence solutions
This AI-102 practice question tests your understanding of implement knowledge mining and document intelligence solutions. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
A law firm uses Azure Document Intelligence to extract clauses from legal contracts. They have a custom model trained on 15 labeled contracts. The model extracts clauses with high confidence on similar documents but fails to extract correct clauses from a new batch of contracts that have a different font and layout. The firm needs to improve extraction accuracy without retraining the model from scratch. The solution must minimize manual effort and cost. What should they do?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Create a composed model that includes the existing model and a new model trained on 5 contracts with the new layout
Option D is correct because creating a composed model in Azure Document Intelligence allows you to combine the existing model (trained on the original layout) with a new model trained on just 5 labeled contracts from the new layout. This approach improves accuracy on the new layout without retraining from scratch, minimizing manual effort and cost by leveraging the composed model's ability to route documents to the appropriate sub-model based on layout similarity.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Use the prebuilt-layout model to extract clauses instead
Why it's wrong here
Prebuilt models do not extract custom clauses.
✗
Increase the OCR confidence threshold in the analysis request
Why it's wrong here
OCR confidence threshold does not affect layout adaptation.
✗
Label 15 more contracts with the original layout and retrain the model
Why it's wrong here
This does not address the new layout variation.
✓
Create a composed model that includes the existing model and a new model trained on 5 contracts with the new layout
Why this is correct
A composed model can handle multiple layouts by combining models.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume retraining with more data (Option C) is always the best solution, but they overlook the composed model feature which is specifically designed to handle layout variations with minimal additional labeling and cost.
Detailed technical explanation
How to think about this question
A composed model in Azure Document Intelligence works by analyzing the input document's layout and automatically selecting the best-matching sub-model from the composition. This is particularly useful when documents have distinct layouts (e.g., different fonts, spacing, or clause positions) because each sub-model is trained on a specific layout, and the composition avoids the need for a single model to generalize across all variations. In practice, training a new sub-model on as few as 5 labeled examples from the new layout can be sufficient if the new layout is consistent, as the composed model leverages the existing model's feature extraction for common clause patterns.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Implement knowledge mining and document intelligence solutions — This question tests Implement knowledge mining and document intelligence solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create a composed model that includes the existing model and a new model trained on 5 contracts with the new layout — Option D is correct because creating a composed model in Azure Document Intelligence allows you to combine the existing model (trained on the original layout) with a new model trained on just 5 labeled contracts from the new layout. This approach improves accuracy on the new layout without retraining from scratch, minimizing manual effort and cost by leveraging the composed model's ability to route documents to the appropriate sub-model based on layout similarity.
What should I do if I get this AI-102 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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