AurvikAI

AI Governance Services

AI you can audit, explain, and stand behind.

Enterprise AI without governance isn't AI — it's liability. Compliance, explainability, and accountability built into every system from day one.

18 years of regulated industry delivery across healthcare, finance, and logistics. We understand what 'defensible AI' means in practice — EU AI Act, GDPR, HIPAA, SOC 2. Our clients don't get surprised by regulators.

18Years of regulated industry experience
5Major compliance frameworks navigated
ZeroRegulatory incidents across all deployments

The governance imperative

Regulation is here. Preparation is optional — compliance is not.

The EU AI Act is enforceable. GDPR penalties for AI decisions are escalating. Boards are asking questions about AI risk that most teams can't answer. Governance isn't a nice-to-have — it's the difference between an AI programme that scales and one that gets shut down.

€35M

Maximum EU AI Act penalty for non-compliance

EU AI Act Article 99

01

EU AI Act compliance

Risk classification, technical documentation, conformity assessment, and post-market monitoring for high-risk AI systems.

02

Explainability by design

Architecture decisions that make model behaviour interpretable — not a reporting layer bolted on after deployment.

03

Bias detection and mitigation

Structured evaluation pipelines that identify discriminatory patterns before they reach production users.

04

Audit-ready documentation

Complete records of data provenance, model decisions, and system behaviour that regulators can review.

The AurvikAI governance framework

Five phases that take you from unstructured AI usage to fully governed, compliant deployment.

Phase 1

Compliance landscape mapping

We identify every regulatory framework, internal policy, and stakeholder expectation that applies to your AI systems. Governance is designed to meet all of them simultaneously.

Regulatory requirements matrixStakeholder expectation registerRisk classification for existing AI systems

1-2 weeks

01
Phase 2

Explainability architecture

Explainability is an architecture decision, not a reporting layer. We select models and design pipelines that produce human-readable explanations for every material decision.

Explainability requirements per systemModel selection guidelinesExplanation generation architecture

2-3 weeks

02
Phase 3

Audit trail and access control implementation

Every AI decision is logged — input, model version, output, and who acted on it. Access to model outputs and training data is controlled and auditable.

Audit logging infrastructureRole-based access controlsData lineage documentation

2-4 weeks

03
Phase 4

Bias testing and adversarial evaluation

Structured bias evaluations, adversarial tests, and edge case analysis before deployment. Governance is a body of evidence that the system behaves as intended.

Bias evaluation reportAdversarial test resultsEdge case catalogue and mitigations

2-3 weeks

04
Phase 5

Ongoing monitoring and review

A governance framework that isn't monitored is a document. We set up model performance monitoring, drift detection, and a regular review cadence.

Monitoring dashboardDrift detection alertsQuarterly review process

Ongoing

05

Governance across every dimension

Comprehensive coverage from data ethics to model operations.

Navigating the regulatory landscape from EU AI Act to industry-specific requirements.

EU AI Act readinessRegulation

Risk classification, conformity assessment, and technical documentation for high-risk AI systems.

GDPR AI compliancePrivacy

Automated decision-making disclosure, right to explanation, and data protection impact assessments.

Industry frameworksSector

HIPAA for healthcare AI, SOX for financial AI, and sector-specific guidelines.

Cross-border complianceGlobal

Managing AI governance across jurisdictions with different regulatory requirements.

Built in — not bolted on

Governance designed into the architecture from sprint one.

Most governance failures happen because governance is treated as a documentation exercise that runs parallel to engineering. At AurvikAI, governance requirements are architectural constraints — they shape model selection, data pipeline design, and deployment infrastructure from the first decision.

A governance framework that isn't monitored is a document. We make governance a live practice, not a one-time audit.

Zero

Regulatory incidents across all deployments

100%

Audit pass rate for governed AI systems

AI governance monitoring dashboard showing compliance metrics
Compliance team reviewing AI governance documentation

AurvikAI governance review session with a European financial services client

Common questions about AI governance

From organisations navigating the intersection of AI innovation and regulatory compliance.

If you deploy or use AI systems that affect EU citizens — regardless of where your organisation is based — the EU AI Act likely applies. The Act classifies AI systems by risk level, with high-risk systems facing the strictest requirements. We help you classify your systems and determine exactly what's required.

AI governance assessment

How prepared is your AI for regulatory scrutiny?

Our governance assessment evaluates your existing AI systems against EU AI Act requirements, GDPR obligations, and industry best practices. You'll receive a clear gap analysis and remediation roadmap.

Ready to make your AI defensible?

Let's start with a conversation about your compliance requirements and governance challenges — we'll give you an honest assessment of where you stand.