Make your AI deployments
defensible.
A modular advisory and technical engagement for regulated enterprises adopting AI. We build real-world security posture that aligns with your compliance requirements.
Securing AI is a cross-domain problem.
This programme exists because securing AI and agentic systems is genuinely hard. By definition, a large language model presents an effectively infinite attack surface. Securing an agentic system that reaches into tools and data demands exactly the cross-domain expertise we hold: applications and databases, operating systems, networks, hyperscaler clouds, and offensive tactics.
We understand systems in depth and we understand AI models in depth. That combination lets us threat model with high accuracy and build security controls that fit the way these systems actually run.
Six modules. Pick one, pick many, or sequence all.
Modules sequence naturally A → B → C → D → E → F. Customers can enter at any module if predecessors already exist.
AI asset inventory.
AIBOM-as-code held in Git with pull-request change control. Infrastructure mapping down to instance, IP, and datacentre. API-key telemetry with behavioural baselines. Shadow-AI discovery across DNS, egress, TLS SNI, and cloud audit logs.
Governance and policy.
Six baseline policies aligned to NIST AI RMF and ISO/IEC 42001, three SOPs for onboarding, periodic review, and vendor assessment. RACI, approval workflows, and escalation paths defined throughout. Every clause traces to a real system, so it holds up under audit.
Threat and fraud modelling.
Boundary threat surface mapped to OWASP LLM Top 10, OWASP Agentic Top 10, and MITRE ATLAS. Model-performance and fraud risk modelled alongside boundary threats. Attack-graph diagrams for multi-step exploitation chains and a quantified risk matrix.
Security testing and validation.
Adversarial robustness testing (FGSM, PGD) against deployed models. Prompt-injection and jailbreak red team across LLM endpoints. Output-handling and downstream-trust testing. Fraud-leakage measurement with reproducible test cases.
Mitigation and hardening.
Hardened-configuration recommendations for each system. Control implementation guidance written for engineers. Prioritised remediation roadmap with effort estimates. Hands-on support to land fixes in production.
Continuous monitoring.
Live AI compliance dashboard tracking current AIBOM state. Anomaly-detection cadence wired into your SOC. Runbooks for incident response and model change. Quarterly attestation cycle and knowledge transfer.
Grounded in the frameworks regulators recognise.
The programme is anchored to named, public standards your regulators already work with.
Scope
an engagement.
Engagement-based delivery. Per-module T&M or fixed-price. We work with your timeline and your AI footprint, not a packaged catalogue.