Securing the AI systems your org is shipping or running: red-teaming before they go live, monitoring once they do, governance for safe adoption. For traditional cybersecurity — pentesting, SOC, NIS2 readiness — our sister firm Baseline IT runs that stack.
// Scope this projectFour focused offerings under this practice. Scope as small as one delivery, as broad as end-to-end ownership.
Detection and response for AI in production: behavior monitoring on agents, prompt-injection signals, data-exfiltration patterns through model APIs. Agentic triage that augments your SOC, not replaces it.
// maps to Pattern 2 — agentic monitoringAdversarial testing of AI systems: prompt injection, agent tool-use abuse, ML pipeline tampering, training-data poisoning. Findings with verified reproduction — for the threat surface a traditional pentest can't reach.
// maps to Pattern 4 — shadow AIGovernance for the AI your org is already deploying: LLM guardrail testing, prompt-injection hardening, data-leak assessment, and policies that don't block the people shipping features.
// maps to Pattern 4 — unreviewed AIThe EU AI Act, ISO/IEC 42001, and your customers' procurement teams now ask whether your AI systems were tested adversarially, whether your training data has provenance, whether your models are monitored. The 'AI policy' role quietly became an operations role — whether the org chart caught up or not.