Universal Containers wants to allow its service agents to query the current fulfillment status of an order with natural language. There is an existing auto launched flow to query the information from Oracle ERP, which is the system of record for the order fulfillment process.
How should an AI Specialist apply the power of conversational AI to this use case?
To enable Universal Containers service agents to query the current fulfillment status of an order using natural language and leverage an existing auto-launched flow that queries Oracle ERP, the best solution is to create a custom copilot action that calls the flow. This action will allow Einstein Copilot to interact with the flow and retrieve the required order fulfillment information seamlessly. Custom copilot actions can be tailored to call various backend systems or flows in response to user requests.
Option B is correct because it enables integration between Einstein Copilot and the flow that connects to Oracle ERP.
Option A (Flex prompt template) is more suited for static responses and not for invoking flows.
Option C (Integration Flow Standard Action) is not directly related to creating a specific copilot action for this use case.
When a customer chat is initiated, which functionality in Salesforce provides generative AI replies or draft emails based on recommended Knowledge articles?
When a customer chat is initiated, Einstein Service Replies provides generative AI replies or draft emails based on recommended Knowledge articles. This feature uses the information from the Salesforce Knowledge base to generate responses that are relevant to the customer's query, improving the efficiency and accuracy of customer support interactions.
Option B is correct because Einstein Service Replies is responsible for generating AI-driven responses based on knowledge articles.
Option A (Einstein Reply Recommendations) is focused on recommending replies but does not generate them.
Option C (Einstein Grounding) refers to grounding responses in data but is not directly related to drafting replies.
An AI Specialist turned on Einstein Generative AI in Setup. Now, the AI Specialist would like to create custom prompt templates in Prompt Builder. However, they cannot access Prompt Builder in the Setup menu.
What is causing the problem?
In order to access and create custom prompt templates in Prompt Builder, the AI Specialist must have the Prompt Template Manager permission set assigned. Without this permission, they will not be able to access Prompt Builder in the Setup menu, even though Einstein Generative AI is enabled.
Option B is correct because the Prompt Template Manager permission set is required to use Prompt Builder.
Option A (Prompt Template User permission set) is incorrect because this permission allows users to use prompts, but not create or manage them.
Option C (LLM configuration in Data Cloud) is unrelated to the ability to access Prompt Builder.
Universal Containers is very concerned about security compliance and wants to understand:
Which prompt text is sent to the large language model (LLM)
* How it is masked
* The masked response
What should the AI Specialist recommend?
To address security compliance concerns and provide visibility into the prompt text sent to the LLM, how it is masked, and the masked response, the AI Specialist should recommend enabling the audit trail in the Einstein Trust Layer. This feature captures and logs the prompts sent to the large language model (LLM) along with the masking of sensitive information and the AI's response. This audit trail ensures full transparency and compliance with security requirements.
Option A (Einstein Shield Event logs) is focused on system events rather than specific AI prompt data.
Option B (debug logs) would not provide the necessary insight into AI prompt masking or responses.
For further details, refer to Salesforce's Einstein Trust Layer documentation about auditing and security measures.
Universal Containers is evaluating Einstein Generative AI features to improve the productivity of the service center operation.
Which features should the AI Specialist recommend?
To improve the productivity of the service center, the AI Specialist should recommend the Service Replies and Case Summaries features.
Service Replies helps agents by automatically generating suggested responses to customer inquiries, reducing response time and improving efficiency.
Case Summaries provide a quick overview of case details, allowing agents to get up to speed faster on customer issues.
Work Summaries are not as relevant for direct customer service operations, and Sales Summaries are focused on sales processes, not service center productivity.
For more information, see Salesforce's Einstein Service Cloud documentation on the use of generative AI to assist customer service teams.
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