UISAIV1 sample questions

Question 1

An automation architect needs to deploy a custom ML model for sentiment analysis, which was developed by an in-house data science team and packaged as a Docker container. The model is not part of the standard UiPath ML Packages. Which actions must be performed in AI Center to make this model available as an ML Skill? (Select TWO)

Accepted Answer

Upload the packaged model code and its dependencies as a .zip file to ML Packages.

Accepted Answer

Create a new ML Skill and select the uploaded package and its major/minor version.

Answer

Create a new Dataset in AI Center and upload the model's training data.

Answer

Create an ML Skill directly from the Docker container image URL.

Answer

Configure a Training Pipeline to build the model inside AI Center.

Question 2

True or False: In the UiPath Document Understanding Process template, the `ShouldStop` variable is exclusively used to gracefully stop the robot from Orchestrator and has no other function within the framework's logic.

Accepted Answer

False

Answer

True

Question 3

A project requires extracting data from scanned, historical engineering diagrams. The text is often hand-written, uses non-standard fonts, and is sometimes skewed. The primary goal is to achieve the highest possible accuracy in text recognition before classification and extraction. Which OCR engine should be prioritized for this use case?

Accepted Answer

UiPath Document OCR

Answer

Tesseract OCR

Answer

Microsoft OCR

Answer

OmniPage OCR

Question 4

A consultant is designing a Communications Mining taxonomy for an insurance company to analyze claims emails. The primary goal is to automate the initial routing and data entry for new claims. Which of the following represents the best-practice approach for designing the label hierarchy for this automation-focused use case?

Accepted Answer

A mutually exclusive, process-oriented structure where each label corresponds to a specific automation path (e.g., 'New Auto Claim', 'New Property Claim', 'Claim Status Inquiry').

Answer

A flat structure with many specific, granular labels (e.g., 'New Auto Claim - Windshield Damage', 'New Auto Claim - Fender Bender').

Answer

A deep, hierarchical structure that categorizes claims by region, then by policy type, then by damage type.

Answer

A broad structure focused on customer sentiment (e.g., 'Happy Customer', 'Angry Customer', 'Neutral Inquiry').

Question 5

## Case Study: Global Logistics Document Automation

**Company Background:**
Global Transport Inc. (GTI) is a multinational logistics company that processes thousands of shipping documents daily, including Bills of Lading (BOL), Commercial Invoices, and Packing Lists. These documents arrive from hundreds of different partners in various formats, ranging from high-quality structured PDFs to skewed, low-resolution scans. The data from these documents is manually entered into their Transportation Management System (TMS), leading to significant delays, data entry errors, and high operational costs.

**Current Situation:**
GTI has initiated a project to automate this process using UiPath Document Understanding. The project team has successfully created a taxonomy and is now in the process of designing the core DU workflow. A key challenge is the high variability in document quality and layout. The same partner might send a clear, machine-readable invoice one day and a poorly scanned, handwritten BOL the next. The system must be resilient and require minimal human intervention for standard documents but also robustly handle exceptions.

**Requirements:**
1. The solution must classify each incoming document as either a BOL, Commercial Invoice, or Packing List.
2. For documents that cannot be classified with high confidence, a human user must be prompted for manual classification.
3. The solution must use a combination of rule-based and model-based extractors to maximize accuracy across different document layouts.
4. All extracted data must be validated against a set of business rules (e.g., 'Total Amount' must equal the sum of line items). Data that fails validation must be sent to a human for correction in Action Center.
5. The final, validated data must be exported as a JSON file for ingestion into the TMS.

Which workflow design most effectively meets all of GTI's requirements?

Accepted Answer

Use a `Generative Classifier` for high accuracy on variable documents. For extraction, use an `ML Extractor` for variable layouts and a `Regex Based Extractor` for consistent formats like BOL numbers. Use the `Present Validation Station` for exceptions and business rule failures. Finally, use `Export Extraction Results` to create the JSON file.

Answer

Use a single `ML Classifier` for document type identification. Then, use a `Form Extractor` for all document types. Finally, use the `Export Extraction Results` activity and perform business rule validation within the TMS system after ingestion.

Answer

Use a `Keyword Based Classifier` followed by an `Intelligent Keyword Classifier`. For extraction, use only the `ML Extractor`. For validation, create a custom input form in UiPath Apps and bypass Action Center.

Answer

Digitize all documents with Tesseract OCR. Use the `Intelligent Form Extractor` which performs classification and extraction in one step. All validation logic should be handled by a separate robot that reads the exported data and creates Action Center tasks manually.

Question 6

A developer is using the `UiPath Communications Mining` activities package in Studio. They need to process emails from a stream, but only those that have a predicted label of 'Urgent Inquiry' with a confidence score of 85% or higher. Which activity and property combination should be used to achieve this?

Accepted Answer

The `Create Stream` activity, defining the label and confidence threshold during stream creation.

Answer

The `Get Stream Items` activity with the `Filter` property set to "Label = 'Urgent Inquiry' AND Confidence >= 0.85".

Answer

The `Get Stream Items` activity, retrieving all items and then using an `If` activity inside a `For Each` loop to check the label and confidence.

Answer

The `Get Label Predictions` activity, which allows filtering by confidence score before processing.

Question 7

During the 'Refine' phase of Communications Mining model training, an analysis of the 'Validation' page reveals the following metrics for a label named 'Address_Change':
- Precision: 95%
- Recall: 40%
- F1 Score: 57%

What does this combination of metrics indicate about the model's performance for this label, and what is the recommended training action?

Accepted Answer

The model is too cautious and misses many true positives. Use 'Missed Label' to find and apply the correct label to communications the model failed to identify.

Answer

The model generates many false positives. Use 'Check Label' to find and correct mislabeled items.

Answer

The model is confused and predicts randomly. The label should be deleted and redesigned.

Answer

The model correctly identifies the label but struggles with other labels. Focus on training different labels.

Question 8

A developer has configured a Document Understanding solution where extracted data is sent to Action Center for validation. A business requirement is to add a note for the human validator, explaining a specific business rule for the 'Invoice_Total' field. How can this be achieved?

Accepted Answer

By using the 'Validator notes' property for the 'Invoice_Total' field within the Taxonomy Manager.

Answer

By passing the note as a string argument to the 'Create Document Validation Action' activity.

Answer

By adding the note to the 'Action Title' property of the validation action.

Answer

By creating a separate 'Comment' in Orchestrator and linking it to the validation task.

Question 9

What is the primary purpose of the `Main-ActionCenter.xaml` file within the standard UiPath Document Understanding Process template?

Accepted Answer

To provide an entry point for attended automation scenarios or for local testing of the DU process.

Answer

To define the business rules for data validation before exporting results.

Answer

To contain the logic for unattended document processing that does not require human validation.

Answer

To handle the creation and monitoring of tasks within the Action Center.

Question 10

A team is using AI Center to retrain a Document Understanding model. They have a dataset of 10,000 documents. They create a Data Labeling session and label 500 documents. After exporting the labeled data, they create a new Training Pipeline. What will the Training Pipeline use as its input dataset?

Accepted Answer

The entire original dataset of 10,000 documents.

Answer

Only the 500 labeled documents.

Answer

The remaining 9,500 unlabeled documents.

Answer

The pipeline will fail because the entire dataset must be labeled first.

Free UISAIV1 sample questions

True or False: In the UiPath Document Understanding Process template, the `ShouldStop` variable is exclusively used to gracefully stop the robot from Orchestrator and has no other function within the framework's logic.

A developer has configured a Document Understanding solution where extracted data is sent to Action Center for validation. A business requirement is to add a note for the human validator, explaining a specific business rule for the 'Invoice_Total' field. How can this be achieved?

What is the primary purpose of the `Main-ActionCenter.xaml` file within the standard UiPath Document Understanding Process template?

A team is using AI Center to retrain a Document Understanding model. They have a dataset of 10,000 documents. They create a Data Labeling session and label 500 documents. After exporting the labeled data, they create a new Training Pipeline. What will the Training Pipeline use as its input dataset?

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