The situation
More and more organizations are integrating advanced AI models into their core processes. While these applications are often treated as low-risk, they introduce new attack surfaces, data risks, and dependencies that aren't always visible within existing security and governance structures.
AI-specific controls are genuinely different from standard IT security controls. Release governance for models, MLSecOps, runtime monitoring, incident response for AI-specific failures.
The earlier you put them in place, the cheaper it is. Mitigating problems after the fact is demonstrably more complex and more expensive than security-by-design.
What we can deliver
Our approach is defense-in-depth: layered controls across two distinct risk domains, plus the MLSecOps layer most security programs miss entirely.
Controls Analysis
We map what's missing, what's insufficient and what should be prioritized, with clear ownership and sequencing your team can act on directly.
Controls Implementation
We build the controls in your environment.
Secure & Safe by Design
For teams building new AI systems, we can cover security threats and safety failure modes in the system architecture from day one.
Good fit if …
You have risk findings but no clear plan for acting on them.
Your team lacks the capacity or expertise to implement AI-specific controls independently.
You're building new AI systems and want security taken care of from the start.
You need monitoring and incident response set up for AI-specific failure modes.
You want a controls framework your team can own and operate going forward.
