Risk-led engineering
Security measures are selected according to product risk, data sensitivity, compliance context and deployment architecture.
Access and environments
Projects can use role-based access, separate environments, protected secrets, code review and controlled releases. Exact controls are defined during discovery.
AI safeguards
AI systems can include approved data boundaries, evaluations, prompt-injection defenses, human approvals, logging and exception handling according to use case.
Continuity and handover
Where included in scope, delivery can cover monitoring, backups, recovery planning, technical documentation and knowledge transfer.
Responsible disclosure
Potential security concerns should be reported privately through the company contact channel with enough detail to reproduce and evaluate the issue.