LLM Processing Privacy Policy

Data flow, network boundaries & privacy protection

Summary

This policy describes where data sits, what crosses network boundaries and how privacy is protected when Context Is Everything uses Large Language Models and AI tools. A Large Language Model, or LLM, is an AI model that reads and generates text. The policy applies to all Context Is Everything LLM and AI tool usage.

LLM data flow

Data path overview

graph TD subgraph "Local Environment" A[Developer Workstation] B[Local Files & Code] C[Environment Variables] D[Configuration Files] E[Git Repository] end subgraph "Network Boundary" F[Corporate Firewall] G[VPN Gateway] H[TLS Encryption Layer] end subgraph "External LLM Services" I[Anthropic Claude Code] J[OpenAI API Services] K[Other AI Providers] end subgraph "Data Processing" L[AI Model Processing] M[Response Generation] N[Temporary Storage] O[Analytics & Logging] end A --> F B --> I C -.->|"Protected by Default"| A D --> I E --> I F --> H G --> H H --> I H --> J H --> K I --> L J --> L K --> L L --> M M --> N M --> O N -.->|"Temporary Only"| L style A fill:#f0fdf4,color:#000 style C fill:#fefce8,color:#000 style H fill:#fefce8,color:#000 style L fill:#fdf2f8,color:#000 style N fill:#fefce8,color:#000

Data location matrix

STAYS LOCAL

Protected

SSH keys and certificates
Database credentials
API keys and secrets
Personal identification data
Proprietary algorithms, unless you share them

Local Processing

File system metadata
Local configuration preferences
Cached responses
Development environment settings
Git history and branches

CROSSES NETWORK

Transmitted to LLM Services

Source code files, when read
Natural language prompts
Error messages and logs
File structure information
Development context data

May Be Sensitive

Business logic and algorithms
Custom implementations
Client-specific code
Internal processes
Architecture patterns

REMOTE PROCESSING

AI Provider Infrastructure

LLM model processing
Response generation
Temporary data storage
Usage analytics
Error reporting

Retention Periods

30-day standard retention
Zero retention options available
Processing memory only
No permanent model training

Network boundary

What crosses the corporate network

Network flow

Outbound Data Flows

sequenceDiagram participant Dev as Developer participant Local as Local Machine participant Corp as Corporate Network participant Internet as Internet participant LLM as LLM Provider Dev->>Local: Execute AI command Local->>Local: Read local files Local->>Corp: Encrypt data packet Corp->>Corp: Firewall & security checks Corp->>Internet: Forward through VPN Internet->>LLM: TLS encrypted transmission Note over Corp: Corporate security controls apply Note over Internet: Data encrypted in transit Note over LLM: Processed on remote servers LLM-->>Internet: Encrypted response Internet-->>Corp: Return through VPN Corp-->>Local: Security validated response Local-->>Dev: Display results

Network Security Layers

Layer	Protection	Data state	Controls
Local Machine	OS-level permissions	Plaintext files	File system access controls
Corporate Firewall	Network filtering	Encrypted packets	Traffic monitoring & filtering
VPN Gateway	Network tunneling	Encrypted tunnel	Corporate network policies
Internet Transit	TLS encryption	Encrypted in transit	Certificate validation
LLM Provider	Provider security	Processed remotely	Provider privacy policies

Network boundary risks and controls

Data exposure risks

Internet Transmission

All prompts and code travel over the internet
Network interception is possible
All AI features depend on an external service
A service provider can suffer a data breach

Corporate Visibility

Network logs may capture metadata
Firewall logs show connection patterns
VPN logs record data transfer volumes
Security teams can monitor AI tool usage

Service Provider Logging

LLM providers track usage patterns
Error logs may contain sensitive context
Providers collect analytics data

Protection measures

Encryption

TLS 1.3 encryption for all transmissions
Certificate pinning where supported
Regular security protocol updates

Access Controls

Multi-factor authentication
API key rotation and management
Network access restrictions
User permission management

Monitoring & Auditing

Usage logging
Regular security assessments
Compliance monitoring
Incident response procedures

Service provider data handling

Anthropic Claude Code

Anthropic data processing

Data Handling Practices

Default policy: No training on user code or conversations
Retention: Automatic deletion from backend systems after 30 days
Local storage: Up to 30 days on user devices for session resumption
Zero retention: Available for enterprise customers with special API keys

Security Measures

Encryption: TLS encryption for all data in transit
Access controls: Server-side access limitations
Processing: Temporary processing memory only, no persistent storage
Compliance: SOC 2 Type II compliance and regular security audits

Data Locations

Primary processing: United States. Specific regions may vary
Backup systems: Geographic redundancy for service reliability
Legal jurisdiction: Governed by Anthropic's terms of service
Data residency: Confirm with Anthropic for specific regulatory requirements

Other LLM providers

OpenAI services

Data Handling as of 2024

Training policy: API data is not used for model training by default
Retention: 30-day retention period for abuse monitoring
Zero retention: Available for enterprise customers
Location: US-based processing in most cases

Security Features

TLS encryption in transit
SOC 2 Type II compliance
Regular security assessments

Cloud provider LLMs

Enterprise Options

AWS Bedrock: Data stays within your AWS account
Google Vertex AI: Processed within Google Cloud infrastructure
Azure OpenAI: Data remains in your Azure tenant

Added Control

Customer-managed encryption keys
VPC or private network connectivity
Detailed audit logging
Regional data residency options

User rights & privacy controls

Individual privacy rights

Your data rights

Access and Control

Right to know: What data is collected and how it is used
Right to access: Review data that providers hold about you
Right to delete: Request deletion of your data from provider systems
Right to correct: Update or correct inaccurate information
Right to export: Download your data in portable formats

Opt-Out Mechanisms

Telemetry opt-out: Disable usage analytics and error reporting
Training opt-out: Confirm data is not used for model training
Retention opt-out: Use zero retention services where available
Service opt-out: Stop using AI services

Implementation controls

Technical controls

Environment Configuration

# Disable telemetry across all tools
export DISABLE_TELEMETRY=true
export DISABLE_ERROR_REPORTING=true
export DISABLE_BUG_COMMAND=true

# Use zero retention API keys
export ANTHROPIC_API_KEY="zero-retention-key"
export OPENAI_API_KEY="enterprise-zero-retention-key"

File Access

Run AI tools from the project directory you intend them to read. Review the files in that directory before you start a session.

Policy controls

Organizational Policies

AI tool usage guidelines
Data classification and handling procedures
Approval workflows for sensitive projects
Regular privacy impact assessments

User Training

Privacy awareness training
Data handling procedures
Incident reporting procedures
Policy updates and reviews

Compliance & regulation

Privacy regulations

GDPR in the European Union

graph TD A[EU Personal Data] --> B{GDPR Assessment} B -->|Personal Data Identified| C[GDPR Protections Required] B -->|No Personal Data| D[Standard Processing] C --> E[Lawful Basis Required] C --> F[Data Subject Rights] C --> G[Data Protection Impact Assessment] E --> H[Legitimate Interest/Consent] F --> I[Access, Rectification, Erasure] G --> J[Risk Mitigation Measures] style A fill:#f0f9ff,color:#000 style C fill:#fefce8,color:#000 style D fill:#f0fdf4,color:#000

GDPR Requirements for LLM Usage

Personal data: Any information relating to an identified or identifiable individual
Processing basis: AI processing needs a legitimate interest or explicit consent
Data subject rights: You must provide access, correction and deletion mechanisms
Cross-border transfers: Special requirements apply to data leaving the EU or EEA
Impact assessments: Required for high-risk AI processing activities

Industry-specific regulations

Healthcare HIPAA

High Risk

PHI cannot be sent to most LLM providers
Requires HIPAA-compliant AI services
Business Associate Agreements needed
Access controls and audit trails required

Mitigation

Use HIPAA-compliant AI services
Anonymize data before processing
Use private cloud deployments
Regular compliance audits

Financial SOX and PCI

Moderate Risk

Financial data requires special handling
Audit trail requirements
Access control documentation
Change management procedures

Controls

Separate environments for financial systems
Added logging and monitoring
Regular security assessments
Compliance documentation

Government and defense

Highest Risk

Classified data cannot use external LLMs
Data residency requirements apply
Security clearance implications
FedRAMP compliance needed

Requirements

On-premises or government cloud only
Security clearance for all personnel
Continuous monitoring
Regular security assessments

Security guidance

Implementation guidelines

Security framework

Organizational Level

Data classification: Identify and classify all data types before AI processing
Risk assessment: Regular evaluation of AI tool risks and benefits
Policy development: Set rules for AI tool usage and data handling
Training programs: Train staff on privacy and security
Incident response: Prepare procedures for privacy and security incidents

Individual Level

Data awareness: Know what data you share with AI tools
Tool configuration: Configure privacy and security settings
Access controls: Use strong authentication and limit tool access
Reviews: Review your AI tool usage and data exposure at regular intervals
Incident reporting: Report suspected privacy or security issues at once

Technical implementation

Recommended practices

Network Security

Use the corporate VPN for all AI tool access
Monitor and log network traffic
Apply security updates and patches
Use certificate pinning where possible

Data Management

Regular data classification reviews
Detect sensitive data with automated tools
Follow secure deletion procedures
Plan backup and recovery

Access Control

Multi-factor authentication
Role-based access controls
Regular access reviews
API key rotation

Practices to avoid

Security Risks

Using AI tools on unsecured networks
Sharing API keys between team members
Processing sensitive data without classification
Ignoring privacy settings and defaults

Compliance Issues

Lack of data processing documentation
Insufficient impact assessments
Missing consent mechanisms
Inadequate data subject rights implementation

Monitoring & audit

Continuous monitoring

What we monitor

Usage

AI tool access patterns and frequency
Data volume and type
User compliance
Service provider usage

Security

Network traffic to AI services
Anomalies in usage patterns
Security incidents
Regular vulnerability assessments

Compliance

Privacy policy adherence
Regulatory requirements
Data retention policy enforcement
User rights request handling

Audit requirements

Audit schedule

Quarterly Reviews

AI tool usage patterns
Privacy policy compliance
Security control effectiveness
User training completion

Annual Assessments

Privacy impact assessment
Security posture evaluation
Regulatory compliance review
Third-party service provider evaluation

Documentation

Required Records

Data processing activities
Privacy impact assessments
Security incident reports
User consent and opt-out records

Audit Trails

AI tool access logs
Data transfer records
Configuration changes
Policy updates and communications

Reporting

Reports

Monthly usage summaries
Quarterly compliance reports
Annual privacy assessments
Incident response summaries

Recipients

Executive dashboard
Team training reports
Client privacy notifications
Regulatory filings

Privacy support & contacts

Privacy questions & support

Context Is Everything Privacy Team
General Privacy Questions: hello@context-is-everything.com
Data Subject Rights Requests: hello@context-is-everything.com
Privacy Impact Assessments: hello@context-is-everything.com

Privacy Incident Reporting
Immediate Response: hello@context-is-everything.com
Security Breaches: hello@context-is-everything.com

External Resources
Anthropic Privacy Center: https://privacy.anthropic.com
OpenAI Privacy Policy: https://openai.com/privacy
GDPR Information: https://gdpr.eu

Related policies: IP Ownership Framework