Services
Four practice areas built around the AI adoption challenges regulated industries face. Advisory and design engagements, with implementation available where it's needed.
Most regulated organizations have an AI governance gap, and most don't know how wide it is. AI tools are being adopted faster than procurement, IT, and security teams can review them. The result is a shadow AI environment where tools are integrated into critical workflows without formal risk assessment, vendor review, or documented controls.
Our AI Governance & Compliance engagement gives you a complete picture of your current state, what tools are in use, what risks they carry, where your policies fall short, mapped against the frameworks that actually matter: ISO 42001, the OWASP LLM Top 10, HIPAA, GDPR, SOC 2, and GxP. The output is a scored gap analysis you can defend to auditors, not a narrative report of opinions.
Clients who need ongoing support can extend into a governance retainer, monthly or quarterly, covering policy maintenance, regulatory monitoring, and audit prep support as the AI regulatory landscape continues to evolve.
The threat environment has changed fundamentally. AI enables attackers to develop exploits in hours, not days. Vulnerability research that once required a specialist team working a week can now be accelerated by an order of magnitude. A vulnerability management program built around a 30-day critical patch SLA was designed for a world that no longer exists.
The CISA Known Exploited Vulnerabilities catalog continues to grow at pace, and the window between publication and active exploitation has compressed. Meanwhile, AI introduces new attack vectors that most detection tooling wasn't built to catch: prompt injection, model poisoning, and adversarial inputs that bypass traditional signature-based detection.
This engagement assesses your current security program against the AI threat reality, identifies the specific gaps in your detection and response architecture, and produces a concrete roadmap for rebuilding your program to operate at AI speed. We reference the CSA AI Safety Initiative and relevant NIST guidance throughout.
The average engineering team has three to four AI development tools in active use. Most weren't approved by security. Most weren't assessed for data exposure risk. And the code they're generating, including hardcoded secrets, insecure patterns, and GPL-licensed suggestions, is already in your repositories.
Claude Code, GitHub Copilot, and Cursor are genuinely powerful tools. The risk isn't the tools themselves, it's deploying them without policy, without guardrails, and without a clear picture of what's being generated and where it's going. The OWASP LLM Top 10 covers the application-layer risks directly; this engagement applies that lens to your development environment specifically.
We inventory what your engineers are using (sanctioned and shadow), assess the exposure, and build the governance framework and CI/CD controls that let your team move fast without creating liability.
Advisory engagements produce a blueprint. Some clients want us to build it too. Implementation is scoped and priced separately from advisory work, the scope and timeline differ meaningfully from assessment and design, and bundling them doesn't serve either well.
If we've completed an assessment with you, we know the environment and the controls. The implementation scope reflects that, no ramp-up, no re-discovery, no redundant work. If you're engaging us with an existing blueprint from another firm, we'll scope accordingly after a discovery conversation.
We'll be direct about what's realistic, what it takes to embed durably, and what a clean handoff looks like when the engagement is complete.
Let's talk about your environment.
Every engagement starts with a direct conversation, no process, no pitch deck.
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