Protect sensitive information in the UI while agents continue to work with actual data
Visual Data Masking is a Beta feature currently being rolled out. If you don’t have access yet, contact your sales representative.
The AI model used for PII detection can occasionally miss sensitive information. Do not rely on Visual Data Masking as your sole privacy control for highly sensitive data. This is a known limitation of the beta.
Visual Data Masking is a front-end privacy feature that automatically masks standard PII (Personally Identifiable Information) fields in conversation histories and task views. This protects confidential information when viewing agent interactions in the UI, during screen sharing, or when reviewing tasks with your team.
Visual Data Masking operates at the UI layer only. When enabled, sensitive information is masked in what you see on screen, but agents continue to access and process the actual, unmasked data.
What you see
Masked values like ***@***.com or ***-***-1234 in conversation histories
What agents see
Full, unmasked data for processing, reasoning, and tool execution
This approach ensures privacy during UI viewing while maintaining full agent functionality. The backend data remains completely unchanged—Visual Data Masking only affects the display layer.
Enable Visual Data Masking when you need to protect sensitive information from being visible in the UI:
Handling customer data
When agents process customer information like email addresses, phone numbers, or payment details, Visual Data Masking prevents this data from being visible to team members reviewing conversations.
Screen sharing and demos
During product demonstrations, training sessions, or customer calls where you’re sharing your screen, Visual Data Masking ensures sensitive information isn’t accidentally exposed.
Team reviews and QA
When multiple team members review agent conversations for quality assurance or training purposes, Visual Data Masking protects customer privacy while allowing evaluation of agent performance.
Compliance requirements
For organizations with regulatory requirements around data visibility, Visual Data Masking adds an extra layer of protection when viewing agent interactions. However, it should be used alongside other privacy controls, not as the sole protection mechanism.
Backend data storage - Data is stored unmasked in the database
Agent processing - Agents always work with unmasked, actual data
Tool execution - Tools receive and process unmasked data
LLM requests - Language models receive unmasked data for processing
API responses - Data returned via API is unmasked
Data exports - Exported data contains unmasked information
Backend logs - Internal system logs contain unmasked data
Event streaming - OTEL events exported to S3 contain unmasked data (unless PII Redaction is enabled)
Visual Data Masking is a UI-only feature. It does not modify, encrypt, or redact data at the storage or processing level. Backend data remains completely unchanged. For backend data protection, see PII Redaction.
Visual Data Masking and PII Redaction are complementary features that protect sensitive information at different stages. They serve different purposes and are designed to work together for comprehensive privacy protection.
As a Beta feature, Visual Data Masking has current limitations that users should understand:
AI detection can occasionally miss PII
The AI model used for PII detection can occasionally miss sensitive information. Detection accuracy varies based on data format, context, and PII type. This is a known limitation of the beta. Do not rely on Visual Data Masking as your sole privacy control for highly sensitive data.
No configuration options
Visual Data Masking is a simple toggle with no advanced configuration. You cannot choose which PII types to mask, customize the masking format, adjust detection sensitivity, or add custom PII patterns. All four supported PII types are automatically masked when enabled.
Fixed masking format
The masking format (e.g., ***@***.com) is fixed and cannot be customized. Future versions may offer configurable masking patterns, but currently all PII is masked using the same placeholder style.
Limited PII type support
Only four standard PII types are supported: email addresses, phone numbers, credit card numbers, and person names. Custom sensitive data types specific to your organization cannot be configured for masking.
Visual only - no data modification
Visual Data Masking only affects the UI display. Backend data storage, agent processing, API responses, and data exports all contain unmasked data. This is by design to ensure agents can function properly, but means the feature provides no backend data protection.
Performance impact on long conversations
On very long conversations with extensive PII, there may be a slight delay in rendering masked content. This is typically imperceptible but may be noticeable in extreme cases with thousands of messages.
We’re actively improving Visual Data Masking based on user feedback. If you encounter issues or have feature requests, contact your sales representative or reach out to support.
Does Visual Data Masking affect agent performance?
No. Visual Data Masking only affects what you see in the UI. Agents continue to process unmasked data with no performance impact. The masking happens during UI rendering, not during agent execution.
How reliable is the AI detection?
The AI model can occasionally miss PII, especially with non-standard formats, international data, or context-specific sensitive information. Detection accuracy is optimized for standard US formats. Do not rely on Visual Data Masking as your sole privacy control for highly sensitive data. Always test with your specific data formats to understand detection accuracy.
Can I customize which PII types are masked?
No. Visual Data Masking is a simple toggle feature with no configuration options. All four supported PII types (email, phone, credit card, person names) are automatically masked when enabled. You cannot select specific types or add custom patterns.
Can I customize the masking format?
No. The masking format is fixed (e.g., ***@***.com for emails). You cannot customize the placeholder text or masking pattern. This may be available in future releases.
Will masked data appear in API responses?
No. Visual Data Masking only applies to the UI. Data returned via API calls is unmasked. If you need to protect data in API responses, implement masking in your application layer.
Can I temporarily disable masking to see actual values?
Yes. You can toggle Visual Data Masking off in agent or workforce settings at any time. Changes take effect immediately for new page loads.
Does Visual Data Masking work with embedded chat?
Visual Data Masking applies to the Relevance AI platform UI only. If you’ve embedded agents on external websites, Visual Data Masking does not apply to those embedded interfaces.
How is this different from PII Redaction?
Visual Data Masking protects what you see in the UI (front-end only). PII Redaction protects what gets exported to your S3 bucket for audit logs and observability (backend data scrubbing). Visual Data Masking is a simple toggle available in Beta; PII Redaction is an Enterprise feature with advanced configuration. Use both together for comprehensive protection.
What happens to data that's already in conversation history?
When you enable Visual Data Masking, it applies to all conversation histories immediately, including past conversations. The masking is applied during rendering, so historical data is protected retroactively in the UI. However, the backend data remains unchanged.
Can I export unmasked data for analysis?
Yes. Visual Data Masking only affects the UI display. Data exports, API responses, and backend storage all contain unmasked data. If you need masked exports, you’ll need to implement masking in your export pipeline or use PII Redaction (Enterprise) for S3 event streaming.
Does this protect data sent to LLMs?
No. Visual Data Masking is UI-only. Agents send unmasked data to LLMs for processing. This is necessary for agents to function correctly. If you need to protect data sent to LLMs, you must implement pre-processing to scrub data before it reaches the agent.