The Enterprise AI Security Challenge
Enterprises face a dilemma: they need AI models to access internal data to be useful, but sharing sensitive information with external AI providers creates risk. How do you get the benefits of AI without compromising security?
Common Concerns
- Data leakage to model providers
- Unauthorized access to sensitive information
- Compliance violations (GDPR, HIPAA, SOC 2)
- Lack of audit trails
Kolossus Security Architecture
Data Never Leaves Your Control
Kolossus processes your data within your security boundary. We send only the minimum necessary context to AI models, and sensitive data can be masked or excluded entirely.
Permission-Aware Retrieval
When AI retrieves information, it respects your existing access controls. Users only get information they're authorized to see -the AI can't bypass permissions.
Encryption Everywhere
Data is encrypted at rest and in transit. API calls to model providers use enterprise-grade TLS. Customer-managed encryption keys available for maximum control.
Data Governance Controls
- Data Classification: Automatically detect and handle sensitive data types
- Redaction Rules: Mask PII, financial data, or custom patterns before model access
- Retention Policies: Control how long AI interactions are stored
- Geographic Controls: Ensure data stays in approved regions
Compliance Framework
Kolossus maintains certifications and supports compliance requirements:
- SOC 2 Type II: Annual audits of security controls
- GDPR: Data processing agreements, right to deletion
- HIPAA: BAA available, PHI handling controls
- Industry Standards: Support for financial services, government requirements
Best Practices
- Start with least-privilege access and expand as needed
- Use dedicated model endpoints for sensitive workloads
- Implement regular access reviews
- Monitor AI usage patterns for anomalies
- Train users on responsible AI data handling