We helped write the global AI standards. Now we engineer the controls that meet them.

Sets a board-approved AI risk appetite, assesses every AI use case proportionately, and gives every risk a named owner, so responsibility is never ambiguous.

Hardens the configuration of models, platforms, and agents, limits exactly who, and which systems, can reach them, then red teams each system and re-tests every fix.

Takes AI from use case to production with risk, security and compliance built into the design, so pilots clear the production gate first time instead of stalling after the demo.

Maps every agent and the tools it can reach, gives each its own scoped identity, places deterministic guardrails at the tool boundary, and proves they hold under attack, with trace-level evidence of every run.

Keeps models fit, fair, and monitored across their life, with model cards, competitive benchmarks, fairness testing, red-teaming, and drift detection.

Proves alignment with law, regulation, and internal policy, and keeps the mappings, literacy, incident records, and audit trails regulators expect.