Before an autonomous agent reaches production, we red-team its tool access, permission boundaries, and failure modes — the same way you'd pen-test any system with real-world reach.
We help you build policy, documentation, and review processes aligned to NIST AI RMF and emerging regulation like the EU AI Act — before an auditor or regulator asks you to.
We assess RAG pipelines and model-serving infrastructure for prompt injection risk, data leakage paths, and access control gaps — and fix what we find.
Security-as-code and cloud security posture management for the multi-cloud (AWS/Azure) environments running your AI workloads — hardened from the ground up, not bolted on after.
Before you adopt a third-party AI tool or model provider, we score its risk exposure so procurement decisions are informed, not just hopeful.
We build secrets management, access controls, and continuous security monitoring directly into your model deployment pipeline from day one.
Agentic AI security is itself a new field — there is no twenty-year incumbent with a deep case-study library, because the risks these systems create didn't exist twenty years ago. What we bring instead is a real security background: hands-on DevSecOps experience across multi-cloud environments, security-as-code, and CI/CD pipeline security, applied directly to the new problems autonomous AI introduces.
You get direct access to that expertise on every engagement — not a junior team hidden behind a big-firm name.