Security & Compliance
How we build AI systems that meet enterprise security requirements and comply with data protection regulations—including GDPR and the EU AI Act.
Security Architecture Principles
Every AI system we build follows defense-in-depth security principles. Security is not a layer added at the end—it's embedded in the architecture from the first design decision.
Input Guardrails
All user inputs are validated and sanitized before reaching the LLM. We implement prompt injection detection, PII scanning, input length limits, and content classification to prevent misuse.
Data Minimization
We apply the principle of least data: agents only receive the information they need to complete their specific task. PII is redacted or pseudonymized before processing where possible.
Immutable Audit Logs
Every agent decision is logged with full context: input hash, model version, retrieved sources, confidence score, and decision outcome. Logs are stored in append-only systems with configurable retention periods.
Role-Based Access Control
Access to agent capabilities, audit logs, prompt configurations, and model settings is controlled by explicit role assignments. Principle of least privilege applies to both human users and service accounts.
Data Handling
Data in Transit
- All API communications over TLS 1.2+
- Client-side secrets never logged
- API keys stored in secret management (Vault, AWS Secrets Manager)
Data at Rest
- Vector databases encrypted at rest
- Audit logs in encrypted, versioned storage
- No persistent storage of raw LLM prompts beyond audit TTL
Third-Party APIs
- LLM API provider data processing agreements (DPAs) reviewed
- On-premise LLM deployment available for sensitive data
- Zero-data retention options with supported providers
Access Logging
- All data access events logged
- Anomalous access patterns flagged
- Logs retained per regulatory requirements
Regulatory Compliance
General Data Protection Regulation
Our AI systems are designed with GDPR compliance as a baseline for European deployments:
- → Lawful basis for processing documented per use case
- → Data subject rights implemented (access, deletion, portability)
- → Right to explanation for automated decisions (Article 22)
- → Data Protection Impact Assessment (DPIA) support available
- → EU/EEA data residency options via on-premise deployment
EU AI Act Readiness
For clients in regulated sectors, we build systems aligned with EU AI Act requirements:
- → Risk classification assessment included in project scope
- → Technical documentation of AI system architecture and limitations
- → Human oversight mechanisms with documented procedures
- → Robustness and accuracy testing with documented results
- → Transparency obligations for AI interactions with end users
SOC 2 Alignment
AI systems we build can be scoped into client SOC 2 audits:
- → Security controls documented and testable
- → Change management for prompt and model updates
- → Monitoring and alerting for anomalous behavior
- → Incident response procedures for AI failures
Responsible AI Practices
Beyond regulatory compliance, we build AI systems that are safe and fair by design:
- ✓ Human oversight for consequential decisions. Automated decisions affecting individuals always include a human review pathway.
- ✓ Hallucination mitigation. RAG grounding, confidence scoring, and output validation reduce the risk of incorrect information being acted upon.
- ✓ Bias testing. We test AI outputs across demographic groups and edge case inputs to identify systematic biases before deployment.
- ✓ Transparency to users. Systems interacting with end users clearly identify themselves as AI and provide explanations for decisions when requested.
Security Questions
For security disclosures, compliance documentation requests, or specific security questionnaires for procurement, contact us directly.
contact@aixagent.io