Collect and store Einstein generative AI audit and feedback data in Data 360 and enhance your generative AI applications with feedback analytics, prompt adjustments, and LLM tuning.
- About Generative AI Audit and Feedback Data
Use generative AI audit data (also known as audit trail) to track Einstein Trust Layer functionality such as data masking and toxicity detection that help ensure the safety and accuracy of the generated response. - Set Up Einstein Generative AI Audit and Feedback
To collect Einstein generative AI audit and feedback data, turn it on in Einstein Setup. For orgs with only one dataspace, it’s turned on by default when Agentforce is turned on. - Data Model for Generative AI Audit and Feedback
Understand and analyze your Einstein generative AI audit and feedback data by using the appropriate data model objects (DMOs). Einstein generative AI Audit and Feedback data is streamed to a data lake object (DLO) in Data 360 and mapped to data model objects (DMOs). - Share Insights from Einstein Generative AI Audit and Feedback Data
Share insights from your org’s Einstein generative AI audit and feedback data with your team. Use pre-built dashboards and reports, running queries, and building Data 360 reports. - Access Einstein Generative AI Audit and Feedback Data Reports and Dashboards
Access the Einstein generative AI audit and feedback reports and dashboards directly from Data 360, after turning on the Einstein generative AI data collection and storage. You can access the Einstein generative AI and feedback data dashboard. - Set Up Email Notifications for Specific Types of Audit and Feedback Data
Use pre-built flows to automate the process of sending email notifications for specific content quality issues or user feedback thresholds or conditions. For example, you can be alerted if the percentage of toxicity in the responses is over the specified threshold. - Billing Considerations for Audit and Feedback
Generative AI Audit and Feedback consumes Data 360 credits for storage used over the allocated amount. - Implement Data Governance Permissions for Audit and Feedback Objects
Audit and feedback data can contain sensitive information, such as personally identifying information (PII), that you want to redact or hide from unauthorized users. Use Data Cloud Data Governance to protect sensitive data by setting up dynamic data masking and field-specific data exclusion policies. Grant access to the impacted Data 360 objects according to an access policy.