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Security & Governance for AI Systems
PII redaction, prompt-injection controls, and governance patterns suited to regulated and high-trust environments building with AI.

Introduction

AI systems introduce failure modes traditional application security doesn't cover: prompt injection, data leakage through model outputs, and the need to prove what a model was and wasn't allowed to see. We build governance and security controls into AI systems as a first-class concern: redaction before data reaches a model, guardrails on what a model can act on, and audit trails suited to regulated environments.

Our Approach
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We treat AI security as its own discipline rather than an extension of standard app security checklists. That means threat-modeling prompt injection and data exfiltration paths specific to your system, redacting or tokenizing sensitive data before it reaches a model, and building governance patterns (access controls, audit logs, approval steps) that satisfy compliance requirements without making the system unusable.
Key Features and Benefits
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PII Redaction: Sensitive data identified and redacted or tokenized before it reaches a model or third-party API.

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Prompt-Injection Controls: Guardrails against untrusted input steering a model into actions or disclosures it shouldn't make.

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Governance and Audit Trails: Access controls and logging patterns suited to regulated industries that need to prove what a system did and why.

Where We Are Today
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This is an active, growing part of our practice as more of our clients move AI systems into regulated and high-trust environments. We're happy to walk through the specific controls relevant to your compliance requirements on a call.

Get AI governance right before you scale it.
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