The Einstein Trust Layer is designed with a robust auditing capability to ensure governance and transparency in AI interactions. It automatically captures all prompts sent to a Large Language Model (LLM) and the corresponding responses. This data, including details of any masking applied to sensitive information, is securely stored within Data Cloud. By leveraging Data Cloud, organizations can create reports and dashboards to audit, track, and analyze these interactions, providing a complete and verifiable record for compliance and governance purposes.

B: Prompt Builder is a tool for designing, testing, and managing AI prompts. It is not used for auditing or requesting historical masked data from the LLM.

C: While an audit trail is accessible, simply exporting prompts from Setup is a limited function. The full auditing and tracking capability is realized through Data Cloud, which provides advanced storage, analytics, and reporting on the captured data.

1. Salesforce Official Documentation

"Einstein Trust Layer": "All of this data [prompts

responses

masking] is logged in an audit trail

and you can see it in Data Cloud. You can use this data to create reports and dashboards to track usage and compliance." (Reference: Salesforce Help

Article 000392168

Section: "How the Einstein Trust Layer Works").

2. Salesforce Whitepaper

"The Einstein GPT Trust Layer" (2023): "The Trust Layer also includes an audit trail of all prompts and responses

which can be used for compliance and governance purposes. This audit trail is stored in the Salesforce Data Cloud

providing a secure and scalable repository for AI interaction data." (Reference: Section 3.2

"Auditing and Data Governance").

3. Salesforce Developer Documentation

"Einstein Generative AI": "Audit Trail: Capture prompts

responses

and feedback to enable auditing and analysis. This data is stored securely in Data Cloud." (Reference: Einstein Trust Layer API Overview).