Offer a focused hardening engagement for companies running or launching AI/ML^? systems. The service audits existing AI workflows, identifies security and observability gaps, then implements baseline controls such as model/prompt logging, access boundaries, vulnerability testing, monitoring alerts, CI/CD policy checks, and incident runbooks. Over time, the business can productize reusable assessment templates, control libraries, and managed monitoring packages.

AI workloads are becoming operational systems rather than experiments, and enterprises are hiring specifically for AI platform operations, AI cybersecurity, and agentic AI reliability. The capability is new enough that many companies need outside implementation help before it becomes standardized internally.