Universal Containers (UC) is implementing Einstein Generative AI to improve customer insights and interactions. UC needs audit and feedback data to be accessible for reporting purposes. What is a cons

The correct answer is A. Storing this data requires Data Cloud to be provisioned.. Salesforce's Einstein Trust Layer captures audit data - including LLM prompts, responses, masked PII, and user feedback - and stores this data in Data Cloud. Therefore, to make this audit and feedback data available for reporting, Data Cloud must be provisioned in the org. This i

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Question

Universal Containers (UC) is implementing Einstein Generative AI to improve customer insights and interactions. UC needs audit and feedback data to be accessible for reporting purposes. What is a consideration for this requirement?

Options

AStoring this data requires Data Cloud to be provisioned.
BStoring this data requires a custom object for data to be configured.
CStoring this data requires Salesforce big objects.

How the community answered

(38 responses)

A
84% (32)
B
11% (4)
C
5% (2)

Explanation

Salesforce's Einstein Trust Layer captures audit data - including LLM prompts, responses, masked PII, and user feedback - and stores this data in Data Cloud. Therefore, to make this audit and feedback data available for reporting, Data Cloud must be provisioned in the org. This is a deliberate architectural decision by Salesforce: Data Cloud acts as the persistence and analytics layer for Trust Layer telemetry. Option B ('custom object for data') is incorrect because Salesforce does not store Trust Layer audit data in custom objects. Option C ('Salesforce big objects') are designed for high-volume archival data, not for generative AI audit storage - the platform uses Data Cloud for this purpose.

Topics

#Einstein Generative AI#Data Cloud#Audit Data#Reporting Data Storage

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