Correct Answer: Custom neural model
Custom neural models in Document Intelligence are designed for unstructured or semi-structured documents, supporting complex tables and variable layouts, and can learn semantic rel...
Correct Answer
Custom neural model
Why This Answer Is Correct
Custom neural models in Document Intelligence are designed for unstructured or semi-structured documents, supporting complex tables and variable layouts, and can learn semantic relationships between fields to extract data accurately.
This question evaluates your knowledge of Azure AI Document Intelligence — a core concept tested in Microsoft Certified: Azure AI Engineer Associate (AI-102). Understanding Azure AI Document Intelligence is essential for designing scalable, secure, and cost-effective cloud architectures. Mastery of this topic will help you answer scenario-based questions confidently on exam day.
You need to extract structured data (such as item description, unit price, tax, and merchant name) from thousands of scanned receipts. Which model type in Azure AI Document Intelligence is pre-trained and optimized for this task?
You want to extract checkmarks and fillable forms selection marks from customer enrollment application forms. Which feature of Azure AI Document Intelligence is designed to identify these marks?
You need to extract data from a highly structured, fixed-layout form (like a standardized government tax form). You want to map specific coordinates on the document to specific fields. Which Custom Model type in Document Intelligence is best suited for this?