aerais
Enterprise AI Governance Systems

We build the operating system for enterprise AI governance.

aerais designs and operationalizes the risk, control, lifecycle, and assurance systems that let regulated and AI‑scaling organizations adopt AI safely — with auditability and board‑level confidence.

Alignment ISO/IEC 42001 · NIST AI RMF · EU AI Act
Delivery model Assess · Design · Implement · Operate
Position Boutique governance‑systems firm
Mandate · Why now

AI adoption is outpacing governance maturity.

Enterprises are embedding AI across core operations faster than oversight can keep up. The exposure is no longer theoretical — it is regulatory, operational, and reputational, and it now lands on the board.

You cannot govern what you cannot see — and you cannot defend what you cannot evidence.

R‑01Shadow AI is already widespread. Most enterprises cannot see their full AI footprint.
R‑02Approval and oversight remain inconsistent, fragmented, and undocumented.
R‑03Model behavior — drift, hallucination, bias — is becoming enterprise risk.
R‑04Third‑party and vendor AI multiply exposure across the supply chain.
R‑05Regulation is accelerating and diverging across jurisdictions.
Position · What we are

Not advisory. Infrastructure.

Most AI governance work stops at ethics statements, policy suites, and strategy decks. aerais operates one layer deeper — embedding governance directly into operating models, risk frameworks, delivery lifecycles, and accountability structures.

The result is governance that scales with innovation and holds up under regulatory examination. We sit above generalist boutiques and beneath Big‑4 overhead — deeper specialization, real implementation capability.

Not ethics consultants
Not policy shops
Not strategy advisors

We are an AI governance systems and controls firm.

Practice · Capabilities

A modular system of enterprise governance capabilities.

Enter at any point. Scale across maturity. Expand into a full transformation and managed‑governance relationship.

A · Strategy & AssessmentWhere are we now?

Establish current state

  • Governance maturity assessment
  • AI risk exposure diagnostic
  • ISO/IEC 42001 readiness
  • AI inventory & shadow‑AI discovery
B · Governance DesignWhat should it be?

Architect the system

  • Operating‑model design
  • Risk taxonomy & control framework
  • Responsible‑AI framework
  • Policy & standards suite
C · ImplementationMake it real

Operationalize governance

  • Lifecycle governance implementation
  • Control operationalization
  • Monitoring & assurance setup
  • Governance tooling enablement
D · ISO 42001 & RegulatoryDefensible

Certifiable & audit‑ready

  • AI Management System (AIMS) build
  • Regulatory alignment & mapping
  • Audit readiness & assurance
  • Mock certification review
E · Managed GovernanceRun it for them

Governance as a service

  • Governance office as a service
  • Risk & compliance monitoring
  • Control testing & assurance
  • Executive & board reporting
F · SpecializedPremium edge

High‑value programs

  • Shadow‑AI detection program
  • AI incident response & governance
  • Model‑risk governance
  • Data governance alignment
Method · How we deliver

One system. Four phases.

This is a transformation program, not a point solution. Each phase produces working governance — and compounds into the next.

01 / Assess
Assess

Establish current‑state maturity, risk exposure, and the AI footprint the organization cannot yet see.

02 / Design
Design

Architect the operating model, risk taxonomy, control framework, and policies that fit the risk profile.

03 / Build
Implement

Embed governance into intake, delivery, deployment, and monitoring. Controls that run — not controls on paper.

04 / Operate
Operate

Assure, monitor, and report continuously — or run the entire governance office as a managed service.

→ Land and expand. Enter at any maturity level; each phase becomes the mandate for the next.

Operating model · Structure

Federated governance with central oversight.

Governance that balances innovation and control — accountability distributed to the business, standards held at the center, assurance kept independent across three lines of defense.

Board & Executive Strategic oversight
Enterprise AI Governance Council Decision authority
AI Center of Excellence Standards & enablement
Risk · Security · Legal 2nd lineIndependent oversight
Business Units 1st lineAI ownership & execution
Engineering & Data Technical implementation
Internal Audit 3rd lineIndependent assurance
Framework · Our IP

Proprietary governance IP, not slideware.

Every engagement configures the same operating system — reusable, testable, regulator‑defensible assets refined across the practice.

IP · REF‑ARCH Reference Architecture The standardized enterprise governance model — structure, control layers, lifecycle gates, and operational integration.
IP · RSK‑TAX AI Risk Taxonomy Domains → categories → scenarios, scored for inherent and residual risk and mapped directly to controls.
IP · CTL‑LIB Control Library Specified, evidenced, and testable controls with implementation guidance and maturity criteria per control.
IP · LIFE‑CYC Lifecycle Framework Governance gates across intake, design, validation, deployment, monitoring, and retirement.
IP · MAT‑MOD Maturity Model A 1–5 enterprise scoring system across governance, risk, control, lifecycle, monitoring, and regulatory alignment.
IP · ASSESS‑KIT Assessment Toolkit Interview guides, evidence‑based scoring matrices, and heatmaps that produce board‑ready findings in weeks.
Enterprise governance maturity — scoring scale
01
Initial
02
Emerging
03
Established
04
Managed
05
Optimized
Signal states Active · live junction Compliant · guardrail met Drift · review Breach · kill⁠-switch
Engagement · Investment

A commercial model built to land and expand.

Four tiers, from a focused diagnostic to a fully managed governance function. Ranges are indicative and scoped to enterprise size, AI footprint, and regulatory exposure.

01
DiagnosticEstablish exposure & roadmap
Maturity assessment · risk exposure · executive roadmap.
$100K – $300KFixed fee
02
DesignArchitect the system
Operating model · control framework · risk taxonomy · policies.
$300K – $1MFixed fee
03
TransformationOperationalize at scale
Implementation · lifecycle integration · assurance enablement.
$1M – $5M+Milestone‑based
04
Managed GovernanceRun it continuously
Governance operations · assurance · regulatory tracking · reporting.
$300K – $3MPer year

Indicative ranges, USD. Fixed‑fee engagements are scoped from medium time estimates, with overruns absorbed — pricing confidence, not client friction.

Sectors · Who we serve

Built for regulated and AI‑scaling enterprises.

S‑01Financial ServicesModel risk, explainability, and regulatory defensibility.
S‑02InsuranceUnderwriting fairness, claims explainability, and bias management.
S‑03HealthcarePatient safety, clinical oversight, and consent governance.
S‑04Public SectorTransparency, accountability, and procurement governance.
S‑05Energy & UtilitiesOperational AI risk in safety‑critical environments.
S‑06TechnologyGovernance at the scale and complexity of AI‑native operations.
Ideal fit $1B–$50B revenue· low‑to‑medium governance maturity· moderate‑to‑high regulatory exposure
FAQ · Common questions

Straight answers.

Q‑01

How is aerais different from a Big‑4 firm?

We specialize in operational AI governance systems and actually implement them — faster delivery cycles, deeper specialization, and far less overhead than broad compliance advisory.

Q‑02

Do you only work on ISO/IEC 42001?

No. ISO/IEC 42001 readiness is one entry point. We also align to the NIST AI RMF and the EU AI Act, and integrate AI governance with your existing risk, security, and privacy frameworks.

Q‑03

Do you advise, or do you build?

We build. aerais embeds governance into intake, delivery, deployment, and monitoring — controls that run inside your systems, not documents that sit on a shelf.

Q‑04

How quickly can we see value?

A diagnostic produces board‑ready findings — current‑state maturity, risk exposure, and a prioritized roadmap — in a matter of weeks.

Q‑05

Who is the right fit?

Regulated and AI‑scaling enterprises, typically $1B–$50B in revenue, with low‑to‑medium governance maturity and moderate‑to‑high regulatory exposure.

Q‑06

Can you operate governance for us?

Yes. Our managed‑governance tier runs the governance office continuously — intake approvals, control testing, assurance, regulatory tracking, and board reporting.

Contact · Next step

Establish enterprise AI governance capability.

Start with a diagnostic to map current‑state risk exposure, governance gaps, and a roadmap for enterprise‑scale AI governance.