2025 AGENTFORCE-SPECIALIST PDF CRAM EXAM | LATEST AGENTFORCE-SPECIALIST 100% FREE TEST FREE

2025 Agentforce-Specialist PDF Cram Exam | Latest Agentforce-Specialist 100% Free Test Free

2025 Agentforce-Specialist PDF Cram Exam | Latest Agentforce-Specialist 100% Free Test Free

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Tags: Agentforce-Specialist PDF Cram Exam, Agentforce-Specialist Test Free, Regualer Agentforce-Specialist Update, Agentforce-Specialist Practice Exam, New Agentforce-Specialist Practice Questions

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Salesforce Certified Agentforce Specialist Sample Questions (Q16-Q21):

NEW QUESTION # 16
Universal Containers (UC) wants to use Flow to bring data from unified Data Cloud objects to prompt templates.
Which type of flow should UC use?

  • A. Unified-object linking flow
  • B. Template-triggered prompt flow
  • C. Data Cloud-triggered flow

Answer: B

Explanation:
In this scenario,Universal Containerswants to bring data fromunified Data Cloud objectsinto prompt templates, and the best way to do that is through aData Cloud-triggered flow. This type of flow is specifically designed to trigger actions based on data changes within Salesforce Data Cloud objects.
Data Cloud-triggered flows can listen for changes in the unified data model and automatically bring relevant data into the system, making it available for prompt templates. This ensures that the data is both real-time and up-to-date when used in generative AI contexts.
For more detailed guidance, refer to Salesforce documentation onData Cloud-triggered flowsandData Cloud integrationswith generative AI solutions.


NEW QUESTION # 17
What is An Agentforce able to do when the "Enrich event logs with conversation data" setting in Einstein Copilot is enabled?

  • A. View the user click path that led to each copilot action.
  • B. Generate details reports on all Copilot conversations over any time period.
  • C. View session data including user Input and copilot responses for sessions over the past 7 days.

Answer: C

Explanation:
When the"Enrich event logs with conversation data"setting is enabled inEinstein Copilot, it allows An Agentforce or admin to view session data, including both theuser inputandcopilot responsesfrom interactions over the past 7 days. This data is crucial for monitoring how the copilot is being used, analyzing its performance, and improving future interactions based on past inputs.
* This setting enriches the event logs with detailed conversational data for better insights into the interaction history, helpingAgentforce Specialists track AI behavior and user engagement.
* Option A, viewing the user click path, focuses on navigation but is not part of the conversation data enrichment functionality.
* Option C, generating detailed reports over any time period, is incorrect because this specific feature is limited to data for the past 7 days.
SalesforceAgentforce SpecialistReferences:You can refer to this documentation for further insights:
https://help.salesforce.com/s/articleView?id=sf.einstein_copilot_event_logging.htm


NEW QUESTION # 18
A data science team has trained an XGBoost classification model for product recommendations on Databricks. TheAgentforce Specialistis tasked with bringing inferences for product recommendations from this model into Data Cloud as a stand-alone data model object (DMO).
How should theAgentforce Specialistset this up?

  • A. Create the serving endpoint in Databricks, then configure the model using Model Builder.
  • B. Create the serving endpoint in Databricks, then configure the model using a Python SDK connector.
  • C. Create the serving endpoint in Einstein Studio, then configure the model using Model Builder.

Answer: A

Explanation:
To integrate inferences from an XGBoost model into Salesforce's Data Cloud as a stand-alone Data Model Object (DMO):
* Create the Serving Endpoint in Databricks:
* The serving endpoint is necessary to make the trained model available for real-time inference.
Databricks provides tools to host and expose the model via an endpoint.
* Configure the Model Using Model Builder:
* After creating the endpoint, theAgentforce Specialistshould configure it within Einstein Studio's Model Builder, which integrates external endpoints with Salesforce Data Cloud for processing and storing inferences as DMOs.
* Option B: Serving endpoints are not created in Einstein Studio; they are set up in external platforms like Databricks before integration.
* Option C: A Python SDK connector is not used to bring model inferences into Salesforce Data Cloud; Model Builder is the correct tool.


NEW QUESTION # 19
Universal Containers Is Interested In Improving the sales operation efficiency by analyzing their data using Al-powered predictions in Einstein Studio.
Which use case works for this scenario?

  • A. Predict most popular products from new product catalog.
  • B. Predict customer lifetime value of an account.
  • C. Predict customer sentiment toward a promotion message.

Answer: B

Explanation:
For improvingsales operations efficiency,Einstein Studiois ideal for creating AI-powered models that can predict outcomes based on data. One of the most valuable use cases is predictingcustomer lifetime value, which helps sales teams focus on high-value accounts and make more informed decisions.Customer lifetime value (CLV)predictions can optimize strategies around customer retention, cross-selling, and long-term engagement.
* Option Bis the correct choice as predicting customer lifetime value is a well-established use case for AI in sales.
* Option A(customer sentiment) is typically handled through NLP models, whileOption C(product popularity) is more of a marketing analysis use case.
References:
Salesforce Einstein Studio Use Case Overview:https://help.salesforce.com/s/articleView?id=sf.
einstein_studio_overview


NEW QUESTION # 20
Which scenario best demonstrates when an Agentforce Data Library is most useful for improving an AI agent' s response accuracy?

  • A. When the AI agent must provide answers based on a curated set of policy documents that are stored, regularly updated, and indexed in the data library.
  • B. When data is being retrieved from Snowflake using zero-copy for vectorization and retrieval.
  • C. When the AI agent needs to combine data from disparate sources based on mutually common data, such as Customer Id and Product Id for grounding.

Answer: A

Explanation:
Comprehensive and Detailed In-Depth Explanation:The Agentforce Data Library enhances AI accuracy by grounding responses in curated, indexed data. Let's assess the scenarios.
* Option A: When the AI agent must provide answers based on a curated set of policy documents that are stored, regularly updated, and indexed in the data library.The Data Library is designed to store and index structured content (e.g., Knowledge articles, policy documents) for semantic search and grounding. It excels when an agent needs accurate, up-to-date responses from a managed corpus, like policy documents, ensuring relevance and reducing hallucinations. This is a prime use case per Salesforce documentation, making it the correct answer.
* Option B: When the AI agent needs to combine data from disparate sources based on mutually common data, such as Customer Id and Product Id for grounding.Combining disparate sources is more suited to Data Cloud's ingestion and harmonization capabilities, not the Data Library, which focuses on indexed content retrieval. This scenario is less aligned, making it incorrect.
* Option C: When data is being retrieved from Snowflake using zero-copy for vectorization and retrieval.Zero-copy integration with Snowflake is a Data Cloud feature, but the Data Library isn't specifically tied to this process-it's about indexed libraries, not direct external retrieval. This is a different context, making it incorrect.
Why Option A is Correct:The Data Library shines in curated, indexed content scenarios like policy documents, improving agent accuracy, as per Salesforce guidelines.
References:
* Salesforce Agentforce Documentation: Data Library > Use Cases- Highlights curated content grounding.
* Trailhead: Ground Your Agentforce Prompts- Describes Data Library accuracy benefits.
* Salesforce Help: Agentforce Data Library- Confirms policy document scenario.


NEW QUESTION # 21
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