CybrHawk helps enterprises deploy AI with confidence establishing the policies, controls, and oversight needed to manage risk, meet regulatory obligations, and build trust at scale.
You can’t govern what you can’t see. We identify every AI system, model, and tool in use across your organization sanctioned and unsanctioned and classify each by risk tier based on use case, data sensitivity, autonomy level, and regulatory exposure.
We design governance frameworks tailored to your industry, risk appetite, and regulatory footprint not generic templates.
We translate complex, evolving AI regulation into practical compliance programs.
Regional & sector coverage includes:
EU AI Act : risk-tier classification, conformity assessments, technical documentation, and CE-marking readiness for high-risk systems.
U.S. federal & state landscape : NIST AI RMF, Colorado AI Act, California AI-related privacy rules, and sector guidance from the FTC, EEOC, and financial regulators.
ISO/IEC 42001 : full AI Management System (AIMS) gap assessments and certification-readiness support.
Financial services : model risk management alignment (SR 11-7 style expectations), fair lending and credit-decision AI review.
Healthcare & life sciences : clinical AI/ML validation support and alignment with FDA guidance on AI/ML-based medical devices.
Public sector : responsible AI procurement standards and algorithmic accountability requirements.
Governance doesn’t stop at deployment. We embed controls across the full AI lifecycle.
Most enterprise AI risk today arrives through vendors, not in-house models.
Governance frameworks only work when people follow them.
Independent validation that your controls hold up under pressure not just on paper.
For organizations that need continuous oversight without building an internal team from scratch.
CybrHawk gave us visibility into AI usage we didn't know existed, and a governance framework our board actually understood. What used to be a compliance headache is now a competitive advantage.
IT Director
The maturity assessment alone paid for the engagement. We walked in thinking we had a moderate governance posture and walked out with a clear, prioritized roadmap.
VP Engineering
CybrHawk's cybersecurity experts helped us achieve compliance faster while improving our overall security posture. The entire engagement was smooth and professional.
Compliance Manager
The penetration testing report was detailed, actionable, and easy for our engineering team to implement. We significantly strengthened our application security.
Head of Infrastructure
From security assessments to ongoing monitoring, CybrHawk has become an extension of our internal security team. Their response time and expertise have been exceptional.
Operations Director
AI governance is the set of policies, processes, and controls that ensure AI systems are developed and used safely, ethically, and in compliance with applicable regulations. As AI adoption accelerates, governance reduces legal, security, and reputational risk while enabling faster, more confident scaling.
Yes. Vendor and embedded AI tools carry the same often greater risk as in-house models, since visibility and control are typically lower. Third-party AI risk management is a core part of our governance approach.
We map your existing controls and gaps against these frameworks directly, then build or adjust your governance program to meet applicable requirements including risk classification, documentation, and ongoing monitoring obligations.
Timelines vary by organizational complexity, but most engagements move from initial assessment to a functioning governance framework within 8-12 weeks, with continuous refinement afterward.
AI security focuses on protecting AI systems from attacks data poisoning, model theft, adversarial inputs. AI governance is broader: it covers the policies, accountability structures, and lifecycle controls that determine how AI is developed, approved, deployed, and monitored across the organization. CybrHawk delivers both as a connected program rather than two disconnected efforts.
Yes. Our model risk and lifecycle controls cover in-house development, including validation, bias and fairness testing, explainability requirements, and monitoring standards for internally built and fine-tuned models.
Yes. Our AI Governance as a Service offering provides continuous monitoring, quarterly risk reviews, policy maintenance, and on-call advisory support so your program stays current as regulations and your AI footprint evolve.
Ownership varies sometimes legal, sometimes security, sometimes a dedicated AI/data governance lead. CybrHawk works alongside whoever owns the program internally, and can also help stand up or facilitate a cross-functional AI governance committee if one doesn’t yet exist.
Both. Our framework covers the full spectrum from custom-built and fine-tuned models to embedded generative AI features and everyday tools like copilots and chat assistants since each carries distinct risk profiles that need to be governed differently.
Whether you’re ready to speak with someone about pricing, want to dive deeper on a specific topic, or have a problem that you’re not sure we can address, we’ll connect you with someone who can help.
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