PMLE Architecting Low-Code ML Solutions Practice Question
A media company wants to automatically transcribe and analyze customer support calls to identify common issues. They need a low-code solution that provides both transcription and sentiment analysis. Which Google Cloud service should they use?
⚠ Common exam trap
The trap here is assuming that combining Speech-to-Text and Natural Language API is low-code; it actually requires integration work, whereas Contact Center AI Insights provides an all-in-one managed solution.
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
✓
Contact Center AI Insights
Contact Center AI Insights is a purpose-built, low-code solution for analyzing customer calls. It automatically transcribes audio, performs sentiment analysis, and extracts topics, providing actionable insights without custom development. Other options either lack sentiment analysis or require integration with multiple services, increasing complexity and coding effort. Thus, Contact Center AI Insights is the correct choice.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Speech-to-Text API
Why it's wrong here
Speech-to-Text API provides transcription but does not include sentiment analysis. To analyze sentiment, you would need to integrate with Natural Language API separately, adding complexity. The requirement is for a solution that provides both transcription and sentiment analysis in a low-code manner. Thus, Speech-to-Text alone is insufficient and would require additional coding and service integration.
- ✓
Contact Center AI Insights
Why this is correct
Contact Center AI Insights is designed to analyze customer interactions, providing transcription, sentiment analysis, and topic detection out of the box. It is a low-code solution that integrates with various contact center platforms. It can automatically process calls and surface insights without custom model development. This directly meets the requirement for both transcription and sentiment analysis in a low-code manner.
- ✗
Dialogflow CX
Why it's wrong here
Dialogflow CX is for building conversational agents, not for analyzing recorded calls. It can handle intent recognition in real-time conversations but does not provide transcription or sentiment analysis for batch call recordings. Using it would require significant custom development and is not aligned with the low-code requirement for call analysis.
- ✗
Natural Language API
Why it's wrong here
Natural Language API provides sentiment analysis on text but does not transcribe audio. To transcribe calls, you would need Speech-to-Text API separately, requiring integration and additional code. This does not meet the low-code requirement for a single solution that handles both transcription and sentiment analysis. Therefore, it is not the best choice.
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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.