Responsible AI. Secure Systems. Production Engineering.
AI systems in production carry real consequences. This page describes the security engineering practices and responsible AI considerations that inform how we work.
Important: Axioprax does not claim certifications it does not hold. This page describes our engineering practices and the frameworks that inform them. Any certification claim in a specific engagement will be stated explicitly and verifiably.
Engineering Practices
Security and responsible AI are addressed at the design stage — not added as afterthoughts before deployment.
Security by Design
- Authentication and authorisation on all endpoints and agent interfaces
- Role-based access control — least privilege by default
- Data access controls and isolation between tenants
- Encryption at rest and in transit
- Secrets management via environment configuration — never hardcoded in source code
- Audit logging for agent actions and data access events
AI-Specific Considerations
- Model output validation and guardrails before downstream action
- Human approval gates for critical or irreversible actions
- Agent permissions and sandboxed execution environments
- Prompt injection risk assessment in input handling
- Structured output validation and schema enforcement
- Failure handling — graceful degradation rather than silent corruption
- Model and provider evaluation against task requirements before selection
Data Practices
- PII identification and appropriate handling at ingestion
- Data retention policies defined per project and client requirement
- Data isolation between tenants in multi-tenant systems
- Customer data is not used to train or fine-tune models without explicit written consent
Monitoring and Observability
- Agent observability — logging of reasoning steps, tool calls and outputs
- Output quality monitoring with alerting thresholds
- Anomaly detection for unusual agent behaviour or output patterns
- Performance and cost monitoring per model and workflow
Frameworks That Inform Our Practice
Our practices are informed by OWASP security guidelines, NIST AI Risk Management Framework principles, and enterprise security engineering standards.
We do not claim SOC 2, ISO 27001, HIPAA or other certifications unless explicitly verified and stated in writing for a specific engagement. If your project requires specific compliance frameworks, raise this at the start of the engagement so we can scope accordingly.
Security requirements for your project?
Discuss your compliance context, data sensitivity and infrastructure requirements at the start of your engagement — we can scope the right approach.
Discuss Security Requirements