What does AI compliance really require?

Clear accountability, risk-based controls, documented decisions, human oversight, and ongoing monitoring of model behavior, incidents, and emerging risks.

Which regulations and frameworks do you cover?

The EU AI Act, NIST AI RMF, ISO/IEC 42001, GDPR, HIPAA, and CCPA, plus sector rules such as DORA and SR 11-7 where they apply.

Can you prepare us for an audit?

Yes. We document and risk-classify models, map controls to the relevant requirements, and build audit-ready documentation and governance workflows.

How do you handle shadow AI?

Through enforceable acceptable-use policies, approved-tool guidance, intake processes, and monitoring, so unapproved tools become easier to find and less necessary.

What services do you offer?

Governance strategy and roadmap, policy and framework design, regulatory compliance advisory, risk assessment and model auditing, program operationalization, and ongoing governance as a service.

Do you only write policies?

No. Policies are written to be operationalized across real workflows, with tooling, model registries, KRI dashboards, and cross-functional governance councils that actually meet and decide.

Are your frameworks off the shelf?

No. Every program is built around your risk profile, industry obligations, AI maturity, and existing governance infrastructure.

Who is involved on our side?

Legal, risk, compliance, engineering, and business stakeholders. We unify them in one governance program so policy, controls, and enforcement are aligned.

How do you manage third-party and vendor AI risk?

Structured vendor due diligence, residual risk ratings, and ongoing monitoring across all third-party AI embedded in your technology stack.

Do you govern agentic AI systems?

Yes. Controls are purpose-built for autonomous agents and multi-model orchestration, including use policies, action logging, registry coverage, and human-in-the-loop controls.

Can governance keep pace with fast AI adoption?

Yes, when it is built into intake, approvals, and monitoring from the start, so risk triage happens before development rather than after deployment.

Which industries do you serve?

Financial services, healthcare and life sciences, manufacturing and supply chain, retail and e-commerce, government and public sector, and SaaS and technology.

Do you support regulated sectors?

Yes. Programs address sector rules such as SR 11-7 model risk management, HIPAA-aligned governance, FDA guidance for medical software, and public sector accountability obligations.

Why choose Aarvexa for AI governance?

Engineering-backed governance, agentic AI expertise, regulation-mapped delivery, cross-functional integration, and no boilerplate frameworks.

Can you build on our existing governance work?

Yes. We assess your current governance posture first and build on what already works instead of replacing it.

How do I book a consultation?

Use any Book a Consultation button. An Aarvexa AI governance specialist will contact you to scope your systems, obligations, and goals.

Governance audit scan live

AI Governance Consulting Services For Audit And Compliance

Build practical AI governance frameworks that help your business manage risk, meet compliance requirements, and use AI responsibly across teams and workflows.

Book a Discovery Call View How We Work

Regulation-mapped delivery

NIST AI RMFEU AI ActISO/IEC 42001GDPRHIPAACCPA

AI MODEL REGISTRY · 6 SYSTEMSAUDIT SCAN

Credit scoringHIGHOPEN

Support chatbotLIMITEDOPEN

Claims triageHIGHOPEN

Demand forecastMINIMALOPEN

Resume screenerHIGHOPEN

Fraud detectionHIGHOPEN

AUDITING CREDIT SCORING

Audit readinessframework coverage

20/ 100

NIST AI RMF0%

EU AI Act0%

ISO/IEC 420010%

Open findings14

Inventory

Classify

Control

Monitor

Audit

InventoriedAI systems

Risk-tieredEU AI Act

ControlledNIST AI RMF

Audit-readyISO/IEC 42001

Blind spots

AI Governance Risks Business Leaders Often Miss

AI risks often develop when tools are adopted without clear ownership, approved-use policies, monitoring, documentation, or human oversight.

Unapproved AI Use

Employees may use unauthorized AI tools without clear safeguards for sensitive data, intellectual property, or business information.

Limited Human Oversight

AI-generated decisions and outputs can create operational, legal, or reputational risks when review responsibilities are unclear.

Regulatory Exposure

Poor documentation, inadequate controls, and unmonitored AI use can make it difficult to demonstrate compliance when requirements apply.

Inconsistent Data Use

AI systems may process inaccurate, biased, confidential, or poorly governed data without defined quality and access controls.

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What we do

Our AI Governance Consulting Services

From roadmap to running program, every service is built to be operationalized across real workflows and stand up to an audit.

AI Governance Strategy & Roadmap

We assess your current governance posture and build a prioritized roadmap aligned to your risk profile, regulatory obligations, and AI maturity level, with full alignment baked in from the start.

AI Policy & Framework Design

We design enforceable AI policies covering acceptable use, model lifecycle decisions, accountability structures, and shadow AI mitigation, written to be operationalized across real workflows, not archived after the kickoff call.

Regulatory Compliance Advisory

We map your AI systems to the specific obligations of the EU AI Act, NIST AI RMF, ISO/IEC 42001, GDPR, HIPAA, and CCPA, giving compliance and legal teams a clear, documented, auditable path to regulatory readiness.

AI Risk Assessment & Model Auditing

We score and tier your deployed AI use cases by risk level, audit for bias and explainability gaps, and evaluate every third-party or vendor AI system embedded across your technology stack.

AI Governance Program Operationalization

We move governance from policy documents into operational infrastructure, selecting tooling, standing up model registries, building board-level KRI dashboards, and establishing cross-functional governance councils that actually meet and decide.

Ongoing AI Governance as a Service

Governance is not a one-time engagement. We provide continuous monitoring, quarterly reviews, incident response support, and program evolution as your AI systems scale and regulatory requirements shift.

How we work

AI Governance Across The Lifecycle

Apply governance controls throughout the AI lifecycle, from initial planning and data preparation to deployment, monitoring, and retirement.

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Use Case Intake Governance

Every AI initiative enters through a structured intake process with risk triage and approval workflows before any development begins.

Model Lifecycle Governance

Formal controls govern model development, validation, deployment approvals, performance monitoring, and decommission decisions throughout the full lifecycle.

Data Governance Integration

AI-specific data controls address lineage, privacy classification, bias in training data, and quality standards for every AI input pipeline.

Third-Party & Vendor AI Risk

Structured vendor due diligence processes, residual risk ratings, and ongoing monitoring cover all third-party AI embedded in your technology stack.

At-Scale & Agentic Governance

Purpose-built guardrails govern autonomous agents, multi-model orchestration systems, and human-in-the-loop controls for agentic AI deployments.

Compliance basics

What AI Compliance Really Requires?

Compliance posture20%

Clear Accountability

Define who approves, owns, monitors, and reviews AI systems, tools, vendors, and high-impact use cases.

Risk-Based Controls

Apply stronger controls to AI applications with greater legal, operational, financial, privacy, or customer impact.

Documented Decisions

Maintain records of intended use, data sources, testing, approvals, limitations, incidents, and changes.

Human Oversight

Specify when AI outputs require employee review, approval, correction, escalation, or intervention.

Ongoing Monitoring

Track model behavior, compliance requirements, performance changes, incidents, complaints, and emerging risks.

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Industries

AI Governance For Your Industry

Governance obligations differ by sector. Programs are built around the regulations, systems, and risk exposure of your industry.

Financial Services

Our governance programs address DORA, SR 11-7 model risk management requirements, AML AI controls, fair lending compliance, and explainability obligations for automated credit decisions.

Healthcare & Life Sciences

We design HIPAA-aligned AI governance, support FDA Software as a Medical Device guidance, and build audit frameworks for diagnostic AI and clinical decision support systems.

Manufacturing & Supply Chain

Governance coverage spans predictive maintenance model oversight, supply chain AI risk classification, and ISO/IEC 42001 alignment for industrial AI environments.

Retail & E-Commerce

We audit personalization AI for fairness issues, review recommendation engine bias exposure, and build consumer data AI compliance controls aligned to GDPR and CCPA requirements.

Government & Public Sector

Our frameworks address responsible AI mandates, procurement AI risk evaluation, and the transparency and accountability obligations that apply to public sector AI deployments.

SaaS & Technology

We govern AI product liability exposure, embedded LLM governance in software products, API risk controls, and EU AI Act compliance obligations for software companies deploying AI to end users.

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Case studies

AI Governance In Action

Model risk register0 / 14 audit-ready

11 weeksSR 11-7 tieringExam cleared

Making Bank AI Models Audit-Ready

A regional bank lacked model documentation, risk classification, and governance controls before an exam. Aarvexa audited models, applied SR 11-7 tiering, and built board-ready governance workflows.

Outcomes:

Audit Readiness: All 14 AI models were documented, risk-classified, and audit-ready within 11 weeks.
Regulatory Confidence: Regulatory exam completed without material findings related to model risk management.
Faster Approvals: Governance council reduced approval time for new AI deployments by 44%.

Track record

AI Governance Built On Practical Experience

0+Governance Engagements Delivered

0+Regulated Industries Served

0Regulatory Frameworks Supported / Engagement

Connect With Our Experts

Our Tech Stack

Technical stack & expertise

ChatGPTClaudeLlamaGeminiDALL·EWhisperStable DiffusionHugging FacePyTorchTensorFlowLangChainNVIDIAOpenAIRay

···

Aarvexa leverages the world's most powerful AI frameworks, models, and acceleration platforms to build secure, scalable, and production-ready AI solutions. Our expertise spans generative AI, deep learning, MLOps, and high-performance inference.

Why Aarvexa

Why Businesses Choose Aarvexa AI As Their AI Governance Partner

Engineering-Backed Governance

Our governance consultants build AI systems in production, so every framework we design accounts for the technical realities of how models behave at scale.

Agentic AI Expertise

We design governance controls purpose-built for autonomous agents and multi-model systems, not retrofitted from static model governance frameworks written before agentic AI existed.

Regulation-Mapped Delivery

Every deliverable we produce maps directly to NIST AI RMF, EU AI Act, or ISO/IEC 42001 requirements, giving your compliance team audit-ready documentation from day one.

Cross-Functional Integration

We unify legal, risk, engineering, and compliance stakeholders inside a single governance program so policy, controls, and enforcement are aligned rather than siloed.

Governance-as-a-Service Option

Our ongoing oversight model provides continuous monitoring, quarterly reviews, and regulatory update integration so governance evolves as your AI stack grows.

No Boilerplate Frameworks

Every governance program is built to your organization's specific risk profile, industry obligations, AI maturity level, and internal governance infrastructure.

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Turn AI Governance Into An Advantage

Build trust, reduce uncertainty, and adopt AI more confidently with governance that supports innovation instead of slowing it down.

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FAQ

Frequently Asked Questions

Straight answers on AI governance: risk, compliance, audit readiness, lifecycle controls, and agentic AI.

They help organizations build practical frameworks, policies, controls, and oversight so AI is used responsibly, manages risk, and meets compliance and audit requirements.

Risks develop when tools are adopted without clear ownership, approved-use policies, monitoring, documentation, or human oversight. Governance makes AI use accountable and defensible.

Unapproved AI use, limited human oversight, regulatory exposure from poor documentation, and inconsistent or poorly governed data use.

No. Good governance supports innovation by building trust, reducing uncertainty, and helping teams adopt AI more confidently instead of slowing them down.

Book a discovery call. We review your current AI use, risk profile, and regulatory obligations, then outline a prioritized governance roadmap.