Move fast with AI, and prove it is safe.
Boards and regulators now expect evidence, not intentions. We help you stand up practical AI governance, secure LLM and agent applications against new attack classes, and continuously evaluate quality, bias and risk.
OWASP LLM Top 10
Threat model coverage
Risk-tiered
Controls proportional to impact
Continuous
Evals in CI and in production
What is AI governance?
AI governance is the set of policies, roles, processes and technical controls an organisation uses to make sure its AI systems are lawful, safe, fair, secure and accountable throughout their lifecycle. It covers inventorying AI use, classifying risk, approving deployments, monitoring performance and responding to incidents, in line with frameworks such as the EU AI Act, ISO/IEC 42001 and the NIST AI Risk Management Framework.
Adopt AI with confidence: governance frameworks, risk assessments, red-teaming and continuous evaluation aligned to emerging regulation.
Our AI Governance & Security capabilities.
AI governance operating model
Policies, AI inventory, risk tiers, approval boards and accountable owners.
Regulatory readiness
Gap assessments against the EU AI Act, ISO/IEC 42001 and NIST AI RMF.
LLM & agent security
Threat modelling, prompt-injection defences, tool permissioning and data-leakage controls.
AI red-teaming
Adversarial testing of models, RAG pipelines and agents before and after launch.
Evaluation frameworks
Accuracy, faithfulness, bias and safety evals integrated with release pipelines.
Monitoring & incident response
Production quality monitoring, alerting and AI-specific incident playbooks.
Where it pays back first.
High-value starting points we see across industries. We will help you rank them against your own data, systems and risk appetite.
01
Board-level AI policy
A clear, enforceable policy and risk appetite for AI.
02
High-risk AI systems
Documentation and controls for regulated use cases.
03
Secure agent launch
Pre-launch security review of agentic applications.
04
Vendor AI due diligence
Assess third-party AI tools before they touch your data.
A clear path to production.
Inventory
Discover AI systems and shadow AI across the organisation.
Assess
Classify risk and map gaps against target frameworks.
Control
Implement policies, guardrails and evaluation gates.
Assure
Monitor, audit and report to leadership and regulators.
Tools we ship with.
Selected on merit for your context. We are model-, cloud- and vendor-agnostic.
- EU AI Act
- ISO/IEC 42001
- NIST AI RMF
- OWASP Top 10 for LLMs
- MITRE ATLAS
- Guardrails
- Llama Guard
- Promptfoo
- Garak
- Langfuse
- Microsoft Purview
- OPA
AI Governance & Security: your questions answered.
AI red-teaming is structured adversarial testing of AI systems to find failures before attackers or users do. That includes prompt injection, jailbreaks, data leakage, harmful outputs and unsafe agent actions. Findings feed directly into guardrails and evals.
Use risk-tiered governance: lightweight approval for low-risk internal tools, stronger controls for customer-facing or high-impact systems. Automated evals and pre-approved patterns let teams ship quickly inside clear boundaries.
Ready to put AI Governance & Security to work? Start with one workflow.
Book a 45-minute strategy session with a Vidura principal. You'll leave with a shortlist of high-ROI AI use cases, the risks to manage, and a realistic path to production.