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Move Fast, Stay Governed & Compliant
AI Security & Resilience
AI expands the attack surface and the compliance burden. AI Security & Resilience gives CISOs an AI inventory, EU AI Act and ISO 42001 readiness, governance by design, and audit-ready assurance to scale safely.
The governance and assurance program that lets you scale AI fast without uncontrolled risk.
Most organizations are already moving on AI. Systems are being built, vendors are being onboarded, and few leaders would argue with the urgency. The harder question is which AI systems count as high-risk, and whether governance and controls can keep pace with the rollout. That answer tends to get deferred.
That gap between moving fast and staying governed is expensive. It’s also where most AI security efforts quietly lose momentum.
AI Security & Resilience is valantic’s AI governance and assurance program for CISOs, CROs, and compliance leaders in regulated and high-stakes sectors. We work with you to inventory AI systems, classify risk against the EU AI Act, design governance and controls by design, and put the resilience and assurance in place to scale AI at speed without uncontrolled exposure.
Where most AI security efforts stall
The same four patterns come up in almost every organization we work with. A credible AI governance approach has to address all of them:
How we help: three modules, one governance journey
The program runs across three modules. Each one produces specific deliverables on its own. Together, they take you from an unclear AI risk picture to governance and assurance built for scale.
AI Readiness & Risk Check
We assess four areas, calibrated to your regulatory context:
- AI inventory: which AI systems exist across the organization, and which of them count as high-risk under the EU AI Act?
- Compliance gaps: where do you stand against the EU AI Act, ISO 42001, and the NIST AI RMF, and what is missing?
- Attack surface: where do prompt injection, data leakage, and supply-chain risks expand your exposure?
- Governance and oversight: is there an operating model for AI governance, controls, and accountability, or gaps where ownership should be?
In the process, we surface the blockers that most commonly keep AI governance behind the rollout:
- An unclear AI inventory, with no agreed view of which systems count as high-risk
- EU AI Act, ISO 42001, and NIST AI RMF compliance gaps that remain open as deadlines approach
- An expanded attack surface, with prompt injection and data leakage inadequately controlled
- No operating model for AI governance, controls, and oversight, so accountability is diffuse
What comes out is a clear AI inventory and risk classification your leadership can agree on, and a prioritized view of the gaps to close first.
Governance & Controls by Design
We turn the risk picture into governance your organization can actually operate:
- A governance model and policies: clear roles, decision rights, and policies that make AI accountability explicit rather than assumed
- Quality gates and security controls: controls for LLM and agent risks, including prompt injection, data leakage, and supply chain
- A phased path to compliant scale built around three horizons:
Quick wins
Readiness checks and priority controls that close the most exposed gaps within weeks, ahead of regulatory deadlines.
Scale controls
Reusable policies, quality gates and control patterns that apply consistently as more AI systems come online.
Foundational governance
The operating model, roles and oversight structures that keep AI governed by design rather than bolted on later.
The result is governance with enough structure to let AI scale compliantly, without slowing every initiative to a stop at review.
Resilience & Assurance
Governance without assurance doesn’t hold under audit. Most efforts leave a set of security and oversight questions unanswered, and those gaps are exactly where risk concentrates. We work through them directly:
- How are threat modeling and red-teaming run in practice? Who owns monitoring of AI systems after go-live, and how are incidents detected and handled?
- How is compliance kept continuous and audit-ready, rather than reconstructed in a scramble before each review?
- What decision rights, controls, and evidence let AI scale at speed while staying liable-safe and defensible to regulators?
The goal is an organization that can scale AI at speed and prove it is governed, not one that hopes its controls hold when the auditor arrives.
What you take away
Five concrete results your leadership team walks away with:
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1
An AI inventory & risk classification
A clear, leadership-aligned view of AI systems and which count as high-risk under the EU AI Act.
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2
A compliance gap assessment
A prioritized view of gaps against the EU AI Act, ISO 42001, and the NIST AI RMF, with what to close first.
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3
A governance operating model
The roles, policies, and oversight your organization needs to govern AI by design.
-
4
LLM & agent security controls
Controls for prompt injection, data leakage, and supply-chain risk across your AI systems.
-
5
Audit-ready assurance
The threat modeling, monitoring, and continuous-compliance evidence that keep AI defensible under audit.
Proven in practice
See all valantic case studies for more examples across industries.
First step: the AI Readiness & Risk Check
The AI Readiness & Risk Check is the right starting point. A focused review, one leadership-ready read-out, and a clear picture of what your AI governance journey should look like.
AI inventory & risk scan
A structured inventory of AI systems, an EU AI Act risk classification, and a first view of where exposure concentrates.
Governance & controls workshop
A facilitated session with security and compliance leaders to shape the governance model, policies, and priority controls.
Readiness read-out
A clear articulation of compliance gaps, priority controls, and recommended next steps you can act on immediately.
Format: Readiness check in 2–4 weeks + risk read-out
Investment: On request
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Plenty of organizations are moving fast on AI. Fewer can prove it is governed. AI Security & Resilience is for leadership teams that want to close that gap, with governance by design and audit-ready assurance, not controls bolted on after the fact.
