AI Security & Governance
Your teams are shipping AI features and your vendors are embedding models into everything. We help you adopt AI without inheriting its failure modes — securing what you build, governing what you buy, and keeping you ahead of AI regulation.
Capabilities
LLM application security testing
Prompt injection, jailbreaks, data exfiltration, insecure output handling and agent/tool abuse — tested against OWASP LLM Top 10.
AI governance & ISO 42001
AI management systems, acceptable-use policy, model inventory and review boards sized to your organization.
NIST AI RMF alignment
Risk mapping and controls for AI systems using the framework enterprises and regulators reference.
Model & data-pipeline risk reviews
Training-data provenance, access to model artifacts, fine-tuning and RAG pipeline security.
Third-party AI risk
Assessment of vendor AI features and copilots before they touch your data.
Secure AI adoption advisory
Guardrails for internal GenAI use that enable teams instead of banning tools they'll use anyway.
Our approach
- Treat AI as a new attack surface on existing systems — identity, data and application security still decide most outcomes.
- Test AI features like an attacker: with tooling and creativity, not a compliance checklist.
- Govern by risk tier — a support-chat summarizer and a credit-decision model don't need the same controls.
- Track the regulatory horizon (EU AI Act, India's evolving guidance) so you're ready before it's mandatory.
Frameworks & references
Not sure where to start? A 30-minute scoping call is free, useful, and pressure-free.
Talk to a consultantCommon questions
We use GenAI via APIs — is that our risk or the provider's?
Yours. Providers secure the model infrastructure; prompt injection, data leakage through context, and what your app does with outputs remain your problem.
Is ISO 42001 worth pursuing now?
If AI is core to your product or your customers are asking about AI governance, yes — early adopters are using it as a differentiator the way SOC 2 was used a decade ago.