Trusting generative AI with your company secrets and your customer data while balancing
the benefits of generative AI is still a challenge today. The Einstein Trust Layer is a secure
AI architecture, built into the Salesforce platform. It’s a set of agreements, security
technology, and data and privacy controls used to keep your company safe while you explore
generative AI solutions.
Watch the video for a quick overview of how the Einstein Trust Layer works. You can
also click this link to launch the video in full screen mode on
a different tab.
For a detailed walkthrough of the Einstein Trust Layer and its
capabilities, see Einstein Trust Layer: Designed for Trust.
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Zero-Data Retention Policy
Your data isn’t retained by third-party LLMs. We partner with all our external
model providers, such as OpenAI, to enforce the zero-data retention policy.
- No data is used for LLM model training or product improvements by third-party
LLMs.
- No data is retained by the third-party LLMs.
- No human being at the third-party provider looks at data sent to their LLM unless Salesforce grants view access in response to documented suspicion of illegal activity or significant violation of applicable usage policies.
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Dynamic Grounding with Secure Data Retrieval
- Relevant information from a Salesforce record is merged with the prompt to
provide context.
- Secure data retrieval of Salesforce data for grounding the prompt based on the
permissions of the user executing the prompt.
- Secure data retrieval preserves in place all standard Salesforce role-based
controls for user permissions and field-level security when merging grounding
data from your CRM instance or Data 360.
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Prompt Defense
- System policies help limit hallucinations and decrease the likelihood of
unintended or harmful outputs by the LLM.
- System policies can vary for different generative AI features and use
cases.
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Data Masking
- Sensitive data is detected and masked before sending the prompt to the
LLM.
- Data masking supports multiple regions and languages.
- You can select what must and must not be masked.
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Toxicity Scoring
- Einstein Trust Layer scores content on toxicity.
- Toxicity scores are logged and stored in Data 360 as part of the audit
trail.
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Audit
- Prompts, responses, and trust signals are logged and stored in Data 360.
- Feedback can be used for improving prompt templates.
- Provides pre-built reports and dashboards for analysis.
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