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AI-102 Practice Question: A company uses Azure Form Recognizer to extract…

A company uses Azure Form Recognizer to extract data from invoices. The extracted data contains many errors for a specific vendor's invoices. What should they do?

⚠ Common exam trap

Many exam-takers assume increasing the confidence threshold (Option C) will fix extraction errors, but it only filters results rather than improving the underlying model's accuracy for vendor-specific formats.

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

Custom train a model with labeled examples of that vendor's invoices.

Azure Form Recognizer's prebuilt invoice model may not generalize well to vendor-specific layouts or data formats. By custom training a model with labeled examples of that vendor's invoices, you adapt the extraction to the unique fields, tables, and formatting, significantly reducing errors. This leverages the service's supervised learning capability to improve accuracy for domain-specific documents.

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 a different prebuilt model.

    Why it's wrong here

    Other prebuilt models may not cover invoices.

  • Disable the OCR step.

    Why it's wrong here

    OCR is essential for text extraction.

  • Increase the confidence threshold.

    Why it's wrong here

    May reduce errors but not address format.

  • Custom train a model with labeled examples of that vendor's invoices.

    Why this is correct

    Custom model learns vendor-specific layouts.

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JA

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.