UiPath UiPath-SAIv1 Exam
UiPath Certified Professional Specialized AI Professional v1.0 (Page 2 )

Updated On: 1-Feb-2026

When is it recommended to use Main-ActionCenter in the context of the Document Understanding Process?

  1. When implementing an attended process.
  2. When testing locally or implementing an attended process.
  3. When testing locally.
  4. When testing locally or implementing an unattended process.

Answer(s): B



What is the recommended number of documents per vendor to train the initial dataset?

  1. 5
  2. 10
  3. 15
  4. 20

Answer(s): B



What can be done in the Reports section of the dataset navigation bar in UiPath Communication Mining?

  1. Train models using unsupervised learning.
  2. View, save, and modify dataset model versions.
  3. Monitor model performance and receive recommendations.
  4. Access detailed, quervable charts, statistics, and customizable dashboards.

Answer(s): D



What is the difference between OCR (Optical Character Recognition) and IntelligentOCR?

  1. OCR (Optical Character Recognition) is a method that reads text from images, recognizing each character and its position, while IntelligentOCR is an enhanced version of it that can also work with noisier input data.
  2. IntelligentOCR is simply a rebranding of the OCR (Optical Character Recognition), both of them being methods that read text from images, recognizing each character and its position.
  3. OCR (Optical Character Recognition) is a UiPath Studio activity package that contains IntelligentOCR as an activity used to read text from images, recognizing each character and its position. OCR is widely used in Document Understanding processes.
  4. IntelligentOCR is a UiPath Studio activity package that contains all the activities needed to enable information extraction, while OCR (Optical Character Recognition) is a method that reads text from images, recognizing each character and its position.

Answer(s): D



Which UiPath Communications Mining model performance factor assesses the proportion of the entire dataset that has informative label predictions?

  1. Average label performance.
  2. Coverage.
  3. Balance.
  4. Underperforming labels.

Answer(s): B



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