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Agentforce and Einstein Generative AI
Set Up Knowledge/RAG Quality Data and Metrics

Set Up Knowledge/RAG Quality Data and Metrics

Turn on Knowledge/RAG Quality Data and Metrics to collect and store, in Data 360, quality scores and other data about knowledge retrievals. For orgs with only one dataspace, it’s turned on by default when Agentforce is turned on.

Required Editions

Available in: Lightning Experience
Available in: Enterprise, Performance, Unlimited, and Developer Editions. Required add-on licenses vary by agent type.
User Permissions Needed
To turn on data collection: View Setup
  AND
  Customize Application
Note
Note Setup considerations:
  1. Confirm that Data Cloud is provisioned in your Salesforce org and that you’ve turned on Einstein. To learn more, see Set Up Einstein Generative AI.
  2. Verify that you have the latest version of the Salesforce Standard Data Model (version 1.130 or higher) in your org (sandbox or production). From Setup, go to Apps -> Packaging -> Installed Packages -> Salesforce Standard Data Model. To get the required version, click here and follow the instructions.
  3. From Setup, in the Quick Find box, enter Einstein Audit, Analytics, and Monitoring Setup, and then select Einstein Audit, Analytics, and Monitoring Setup.
  4. Confirm that Audit and Feedback is turned on. To learn more, see Set Up Einstein Generative AI Audit and Feedback.
  5. Scroll down to Knowledge/RAG Quality Data and Metrics.
    Toggle for Knowledge/RAG Quality Data and Metrics in Setup
  6. Turn Knowledge/RAG Quality Data and Metrics on or off.
    1. Turn on Knowledge/RAG Quality Data and Metrics to provision your data model (in just a few minutes) and start collecting data in Data 360. Data collection occurs every five minutes, data processing occurs every hour, and data reporting is aggregated daily.
      Turning on Knowledge/RAG Quality Data and Metrics increases your org’s Flex credit consumption rate for LLM calls (see Flex Credits Billable Usage Types).
    2. Turn off Knowledge/RAG Quality Data and Metrics to stop collecting data.
      Suspending data collection keeps your existing data so that you can resume later. Dashboards, queries, and reports show a gap during which data collection is turned off.
  7. If prompted (for example, if you turn on data collection on and your org has multiple data spaces), select a target data space to store the data.
  8. Optionally, adjust the sampling rate, which is the percentage of retrievals you want to score and analyze. The default sample rate is 0% (no scoring). To begin scoring retrievals, adjust the percentage upwards.
    An LLM scores retrieval quality, which consumes Flex credits. As RAG quality scores stabilize over time, consider lowering the sample rate to reduce the number of LLM calls and Flex credit consumption.
  9. Protect access to collected Agentforce Session Tracing data that is sensitive. Hide sensitive data from unauthorized users. Stored data can contain personally identifying information (PII), protected health information (PHI), payment card information (PCI), and other sensitive information.
    • Use dynamic data masking to redact, nullify, or round sensitive data. For instructions, see Dynamic Data Masking Policies in Data 360.
    • Apply permissions at the data space level. That way, only authorized users can view or query this data. By default, users with the Data Cloud Architect (formerly the Data Cloud Admin) permission set have access to all the data. For instructions, see Implement Data Governance Permissions for Agentforce Session Tracing Objects.
    • The Salesforce System Admin profile includes the Manage All Data Space definition permission, which grants users access to all Data Spaces. If the default Allow All policy is active in the org, users with the System Admin profile can query all Data 360 DMOs. To preserve data security, we recommend deleting the default Allow All policy or editing its scope to apply to specific users. For instructions, see Data Governance in Data 360.
 
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