Overview
The Data Protection Filter safeguards personally identifiable information (PII) using advanced AI detection systems. It analyses both user inputs and AI responses in real-time to identify and protect sensitive data like names, addresses, and financial information.What the Guardrail Does
Purpose
The primary goal of the Data Protection Filter is to safeguard sensitive personal information by preventing unauthorised exposure of PII during AI interactions while maintaining high accuracy and minimal impact on legitimate business communications. By enabling this guardrail, organisations can ensure compliance with data protection regulations, protect user privacy, maintain trust, and uphold responsible data handling practices across all AI-powered interactions.Scope
Comprehensive PII Detection
The Data Protection Filter applies advanced content analysis to:- Input – Applies the selected behaviour to what users send to the model.
- Output – Applies the selected behaviour to what the model returns as a response.
- Both – Full bidirectional coverage
Operational Modes
- Monitor – Lets you review input or output content without taking any action—used for observation and diagnostics.
- Block – Automatically stops content from being processed if it violates the selected guardrail rules.
- Mask – Replaces detected sensitive information with anonymised placeholders while allowing content to proceed.
Detection Categories
The guardrail monitors multiple categories of PII:- General: Personal identification, contact information, and basic identifiers
- Finance: Financial account numbers, credit cards, and banking information
- Technology: Digital identifiers, network addresses, and technical credentials
- USA Specific: United States government and financial identifiers
- Canada Specific: Canadian government and healthcare identifiers
- UK Specific: United Kingdom government and healthcare identifiers
Key Features
Multi-Category Detection
Comprehensive coverage across all major PII types including personal, financial, and government identifiers.
Context-Aware Analysis
Advanced understanding of conversation context and data patterns for accurate PII detection.
Configurable Sensitivity
Adjustable detection thresholds for different use cases with Low, Medium, and High options.
Low Latency
High-performance detection that doesn’t impact response times or user experience.
Enterprise-Grade Accuracy
Minimises false positives while maintaining high detection rates across all data types.
Regulatory Compliance
Aligns with GDPR, HIPAA, and other data protection frameworks for compliance assurance.
Why Use This Guardrail?
Benefits
- Regulatory Compliance: Ensures adherence to data protection laws and industry standards
- Privacy Protection: Safeguards user privacy and prevents unauthorised data exposure
- Risk Mitigation: Reduces legal and reputational risks associated with data breaches
- Trust Building: Maintains user trust through responsible data handling
- Audit Trail: Provides comprehensive logging for compliance and investigation purposes
Use Case: Healthcare AI Assistant
Scenario
A healthcare organisation deploys an AI assistant to support patient enquiries and administrative tasks. The assistant must handle sensitive patient information while ensuring strict compliance with HIPAA regulations and maintaining patient privacy at all times.Challenge
The organisation must ensure that:- Patient PII is never exposed in AI responses
- User inputs containing sensitive data are properly handled
- All interactions comply with healthcare privacy regulations
- Detection works accurately across various data formats and contexts
Solution: Implementing Data Protection Filter
-
Comprehensive Entity Selection
- Selected General entities: Full Name, Phone Number, Email Address, Residential Address, Age
- Selected UK Specific entities: U.K. NHS Number for patient identification
- Applied to both Input and Output for full bidirectional protection
-
Appropriate Enforcement
- Set to Mask behaviour to anonymise PII while maintaining workflow continuity
- Replaces detected PII with appropriate placeholders (e.g., , , )
-
Optimised Configuration
- Used Medium sensitivity threshold for balanced accuracy
- Maintains detection effectiveness across diverse data types and formats
How to Use the Guardrail
Note: The steps below guide you through configuring the Data Protection Filter using the Guardrail Setup.
Step 1: Navigate to the Guardrail Setup
- From the Home Page, open the AI System Dashboard by selecting View to open your AI system from the AI System Table.
- In the guardrails section of the AI System Overview, click Edit Guardrails to launch the guardrail configuration workflow.
Step 2: Select and Enable the Data Protection Filter
- In the Configure Guardrails page, a list of available guardrails will be displayed.
- Click on Data Protection to open its configuration options on the right-hand side of the screen.
- Toggle the Enable Policy switch to ON to begin configuration.
Step 3: Select Entities
- Within the guardrail configuration, you’ll see a set of expandable groups. Click on any group to reveal its entities:
- General
- Finance
- Technology
- UK Specific
- USA Specific
- Canada Specific
- Within each expanded category, check the boxes for the specific entities you want to configure (e.g., Email Address, Name, IP Address).
- As entities are selected, they will appear as tags under the Selected Entities section for easy review and removal.
Step 4: Set Application Scope
- Under the Apply Guardrail To section, select where you want the guardrail enforced:
- Input – Applies the selected behaviour to what users send to the model.
- Output – Applies the selected behaviour to what the model returns as a response.
- Both – Full bidirectional coverage
Step 5: Configure Enforcement Behaviour
- Under Select Guardrail Behaviour, choose how the system should respond to detected PII:
- Monitor – Lets you review input or output content without taking any action—used for observation and diagnostics.
- Block – Automatically stops content from being processed if it violates the selected guardrail rules.
- Mask – Replaces detected sensitive information with anonymised placeholders while allowing content to proceed.
Step 6: Save, Test, and Apply the Guardrail
- Click Save & Continue to store your selected entities and configuration.
- Go to the Test Guardrails step to evaluate how the guardrail behaves in real time with a chatbot.
- After saving, you can proceed to the Summary section to review your configuration, save all changes, and view your AI System overview.
The Data Protection Filter provides enterprise-grade PII protection with comprehensive detection capabilities, ensuring your AI interactions remain compliant and secure while maintaining the highest standards of data privacy.