PMLE Architecting Low-Code ML Solutions Practice Question
A company needs to extract text from scanned invoices and parse key fields like invoice number and total amount. Which Document AI processor should they use?
⚠ Common exam trap
Watch out — candidates often confuse generic OCR with specialized parsing; candidates might think OCR is sufficient for extracting fields, but it only provides raw text without structure.
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
✓
Invoice Parser
The Invoice Parser is a specialized Document AI processor pre-trained to extract structured data from invoices, including fields like invoice number, total amount, due date, and line items. It goes beyond generic OCR by understanding the invoice layout and returning key-value pairs. OCR Processor only extracts raw text without parsing fields, while Form Parser and Contract Parser are for general forms and contracts, respectively.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
OCR Processor
Why it's wrong here
The OCR processor returns raw recognised text without identifying invoice number or total amount as structured fields, so downstream parsing logic would be needed. It suits digitising arbitrary scanned text. Extracting named fields from invoices requires a specialised invoice processor.
- ✗
Contract Parser
Why it's wrong here
Contract Parser targets legal agreements, extracting clauses, parties and terms from contracts, not invoice fields such as invoice number and total amount. It would be chosen for reviewing procurement or lease documents. Invoice parsing requires a processor trained on invoice schemas.
- ✗
Form Parser
Why it's wrong here
Form Parser extracts generic key-value pairs from forms, but invoice number and total amount are not reliably labelled as such on invoices, so accuracy suffers. It suits structured questionnaires and applications. Invoice-specific fields need a processor trained on invoice layouts.
- ✓
Invoice Parser
Why this is correct
Invoice Parser combines OCR with pre-trained extraction of invoice-specific fields such as invoice number and total amount, satisfying the requirement to parse key fields from scanned invoices. Unlike generic OCR, which returns raw text only, it maps recognised content directly to structured invoice schema, removing custom model training.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
This PMLE practice question is part of Courseiva's free Google Cloud 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 PMLE exam.