This AI Privacy Policy specifically addresses how Kairos IQ LLC (“Kairos IQ,” “we,” “our,” or “us”) handles data in relation to our artificial intelligence features and services. This policy supplements our main Privacy Policy and focuses on AI-specific data processing, inference operations, and machine learning activities.

1.1 Types of AI Processing

Our platform employs AI for various real estate functions:

• Natural language conversation processing and response generation
• Lead analysis and buyer preference modeling
• Market intelligence and property valuation insights
• Deal intelligence and transaction optimization
• Content generation and listing optimization
• Automated task creation and workflow management

2.1 Model Training Data

Our AI systems are trained on anonymized and aggregated data to improve performance:

• De-identified conversation patterns and interaction flows
• Anonymized real estate market data and transaction patterns
• General language patterns for real estate terminology
• User interface interaction patterns (without personal data)
• System performance metrics and response optimization data

2.2 Real-Time Learning

Our AI systems continuously learn from:

• Aggregated usage patterns across all users (anonymized)
• System performance and response quality metrics
• Feature effectiveness and user engagement patterns
• Error patterns and system improvement opportunities
• Market trend analysis for algorithm optimization

2.3 Data Minimization for AI

We implement strict data minimization for AI processing:

• Only contextually relevant data is sent to AI systems
• Personally identifiable information is redacted from AI prompts
• Sensitive data is replaced with placeholder values
• AI responses are filtered for sensitive information leakage
• Conversation summaries prioritize business context over personal details

3.1 Real-Time AI Processing

Our AI systems process data in real-time to:

• Generate contextually appropriate responses to user queries
• Analyze lead information and provide actionable insights
• Create personalized recommendations based on user role and data
• Process natural language queries and convert them to system actions
• Maintain conversation state and context across interactions
• Apply business logic and real estate expertise to AI responses

3.2 AI Personalization

AI personalization is achieved through:

• Role-based prompt engineering (Agent, Broker, Lender perspectives)
• Subscription-tier appropriate feature access and AI capabilities
• Context-aware entity loading based on current conversation needs
• Preference-driven response style and engagement levels
• Historical interaction patterns to improve response relevance

3.3 AI Cost & Resource Management

We monitor AI resource usage to:

• Track computational costs and token consumption per user and feature
• Implement dynamic cost controls to prevent budget overruns
• Optimize AI model selection based on query complexity and user tier
• Detect and prevent abuse of AI resources through usage pattern analysis
• Provide transparent usage reporting and cost projections
• Balance system performance with operational cost management

3.4 Privacy-First AI Processing

We implement privacy-by-design in all AI operations:

• Automatic redaction of personally identifiable information before AI processing
• Context filtering to include only business-relevant data in AI prompts
• Response filtering to prevent AI systems from revealing sensitive information
• Conversation summarization that prioritizes business insights over personal details
• Role-based data access controls for AI context generation
• Subscription-tier appropriate privacy controls and data exposure limits

4.1 AWS Bedrock & Claude AI Integration

We use AWS Bedrock to access Anthropic’s Claude AI models with strict privacy controls:

• Data Transmission: Only privacy-filtered conversation context is sent to AI services
• PII Protection: All personally identifiable information is redacted before transmission
• Ephemeral Processing: Data is processed in real-time and not stored by AI providers
• Regional Compliance: Data processing occurs within specified geographic regions
• Contractual Protections: Our agreements with AI providers include strict data protection clauses

4.2 AI Infrastructure Providers

AI-specific service providers include:

• AWS Bedrock: AI model hosting and inference processing
• Anthropic: Claude AI model development and maintenance
• Cloud Infrastructure: Secure compute environments for AI processing
• Monitoring Services: AI performance and cost monitoring tools
• Security Providers: AI-specific security and compliance monitoring

4.3 AI Data Restrictions

We contractually restrict third-party AI providers from:

• Using your data to train their general AI models
• Storing or caching conversation data beyond processing requirements
• Sharing data with other customers or third parties
• Using data for any purpose other than generating responses to your queries
• Analyzing or mining your data for business intelligence purposes

4.4 Data Isolation & Security

5.1 AI Feature Security

AI features are secured through multiple layers:

• Model Access Controls: Different AI models and capabilities by subscription tier
• Context Filtering: Subscription-appropriate data access for AI processing
• Response Filtering: AI responses filtered based on user permissions
• Usage Quotas: AI resource limits prevent abuse and control costs
• Rate Limiting: Request throttling to prevent system overload

5.2 Role-Based AI Security

AI security adapts to user roles:

• Role-Specific Prompts: AI system prompts tailored to professional role and permissions
• Data Scope Limiting: AI context restricted to role-appropriate data visibility
• Response Tailoring: AI responses adapted to user’s professional responsibilities
• Compliance Integration: Role-based fair housing and legal compliance in AI responses

5.3 AI Data Minimization

Privacy-by-design for AI operations:

• Smart Context Loading: Only conversation-relevant data included in AI prompts
• PII Redaction: Automatic removal of personally identifiable information
• Relevance Filtering: AI context limited to business-relevant information
• Prompt Optimization: Minimized data transmission while maintaining AI effectiveness
• Session Isolation: AI context cleared between conversations and sessions

6.1 AI Decision Process

Our AI systems make decisions through:

• Rule-Based Logic: Predefined business rules and real estate expertise
• Context Analysis: Current conversation state and user intent recognition
• Role Adaptation: Professional role-based response generation
• Compliance Checking: Automatic fair housing and legal compliance review
• Quality Filtering: Response accuracy and appropriateness validation

6.2 AI Transparency

We provide transparency into AI operations:

• Decision Explanations: Clear indication when AI is making recommendations
• Confidence Levels: AI confidence indicators for analysis and recommendations
• Data Sources: Transparency about what data informed AI responses
• Human Oversight: Clear identification of AI vs. human-generated content
• Limitation Disclosure: Honest communication about AI capabilities and limitations

6.3 AI Bias Prevention

We actively work to prevent AI bias through:

• Fair Housing Integration: Built-in fair housing compliance in all AI responses
• Bias Testing: Regular testing for discriminatory patterns in AI outputs
• Diverse Training: AI training on diverse, representative real estate scenarios
• Human Review: Human oversight of AI decision-making processes
• Feedback Loops: User feedback integration to identify and correct bias

7.1 AI Model Protection

We protect AI models and processing through:

• Model Isolation: Customer data isolated during AI inference operations
• Encrypted Communication: All AI service communications encrypted in transit
• Access Controls: Strict API key management and authentication
• Audit Logging: Comprehensive logging of all AI interactions and decisions
• Model Versioning: Secure model deployment and update processes

7.2 AI Communication Security

AI service communications are secured through:

• TLS Encryption: All AI API communications encrypted with TLS 1.3
• API Authentication: Secure token-based authentication for AI services
• Request Signing: Cryptographic signing of AI service requests
• Response Validation: Verification of AI service response integrity
• Connection Pooling: Secure, reusable connections to AI providers

7.3 AI Access Controls

AI system access is controlled through:

• Multi-Factor Authentication: Secure access to AI management systems
• Role-Based Permissions: Granular control over AI feature access
• Session Management: Automatic timeout and session invalidation
• Audit Trails: Complete logging of AI system access and usage
• Anomaly Detection: Automated detection of unusual AI usage patterns

8.1 AI Interaction Controls

You have control over AI interactions through:

• AI Feature Toggle: Enable or disable specific AI features
• Context Preferences: Control what data AI can access for responses
• Response Style: Adjust AI response length and technical level
• Usage Monitoring: View real-time AI usage and quota consumption
• Conversation Management: Delete, archive, or export AI conversations

8.2 AI Opt-Out Rights

You can opt out of AI processing by:

• Feature Disabling: Turn off specific AI features while retaining others
• Manual Mode: Use platform features without AI assistance
• Data Exclusion: Exclude specific data types from AI processing
• Limited Processing: Restrict AI to basic functions only
• Complete Opt-Out: Disable all AI features and processing

8.3 AI-Specific Rights

Regarding AI processing, you have the right to:

• Explanation Rights: Understand how AI decisions affect you
• Human Review: Request human review of AI-generated recommendations
• AI Data Access: View what data was used for AI processing
• Processing Restriction: Limit or restrict AI processing of your data
• AI Deletion: Remove your data from AI training or processing
• Bias Reporting: Report suspected bias in AI responses or decisions

9.1 Fair Housing AI Compliance

Our AI systems enforce fair housing principles through:

• Built-in Compliance: Fair housing rules integrated into all AI responses
• Bias Detection: Automated screening for discriminatory language or recommendations
• Inclusive Training: AI models trained on diverse, representative datasets
• Regular Auditing: Third-party audits of AI decision-making for bias
• Response Filtering: Real-time filtering of potentially discriminatory content

9.2 Algorithm Performance Monitoring

We continuously monitor AI algorithm performance through:

• Accuracy Metrics: Regular evaluation of AI prediction and recommendation accuracy
• Fairness Testing: Ongoing testing for equitable outcomes across demographic groups
• User Feedback: Collection and analysis of user feedback on AI performance
• External Audits: Independent audits of AI systems and decision-making processes
• Performance Reporting: Regular transparency reports on AI system performance

9.3 AI Limitations Disclosure

We transparently communicate AI limitations:

• Capability Boundaries: Clear disclosure of what our AI can and cannot do
• Confidence Levels: AI confidence indicators for all recommendations
• Data Dependencies: Explanation of how data quality affects AI performance
• Human Verification: Recommendations for when human oversight is needed
• Error Reporting: Easy mechanisms to report AI errors or inappropriate responses

This AI Privacy Policy addresses the unique considerations of artificial intelligence in real estate technology. We are committed to responsible AI development and transparent data practices that respect your privacy while delivering powerful AI capabilities.