Your AI Program Is One Audit, Security Review, or Board Question Away From Exposing Its Governance Debt
Governance treated as paperwork after the fact turns growth moments into stalled deals and audits into board-level findings. Etherion builds it into the architecture from day one.
The Gap That Breaks First-Time and Long-Running Data Programs Alike
Different trigger, same root cause: governance treated as something you produce after the platform is built, instead of a structure you design before it.
Why AI Startups Lose Enterprise Deals They Should Win
No governance paper trail that shows model versioning, lineage, or risk classification because it was never built into the pipeline. | Compliance bolted on late retrofitting HIPAA or APRA-aligned controls after launch means re-architecting under deadline pressure. | No one owns it, a lean team rarely has a governance lead, so the vendor questionnaire lands on an engineer with no framework to answer from.
- Legacy data debt audit
- Technical risk register construction
- Phased cloud-native migration roadmap
- Validated proof-of-concept architecture
Why Regulated Data Programs Fail Under Audit
Governance bolted on where controls are retrofitted after delivery and rarely survive contact with an auditor’s questions. | AI outrunning governance where model versioning and ingestion loops are running without a mapped AIMS framework. | Legacy debt compounding, SQL Server and SSIS-era estates carrying undocumented risk into cloud and AI initiatives.
- BSI ISO 42001 Lead Practitioner certified
- CDMP & DAMA-DMBOK aligned frameworks
- Automated data quality gates & lineage
- Critical data element definition & ownership
Your AI Systems Are Outrunning Your Ability to Govern Them
ISO 42001 is the first international standard for AI Management Systems and most organisations have no clear path to it. Map AI systems, model versioning pipelines, and data ingestion loops against the full AIMS framework. Produce a concrete AI risk inventory and lifecycle control structure. EU AI Act enforcement deadline arrives August 2026; Australian regulators are sharpening AI expectations. Structured AI governance is no longer optional
- ISO 42001 AIMS design & implementation
- AI risk inventory & impact assessments
- Model lifecycle control frameworks
- Board-ready AI governance reporting
Fixed-Scope Engagements. Defined Outcomes.
Every Etherion engagement is productised a bounded scope, a concrete deliverable, and a defined timeline. You know exactly what you’re buying before work begins.
AI Governance Readiness Snapshot
A fixed-price diagnostic scoring your AI and data pipeline against ISO 42001, HIPAA, and APRA CPG 235. You leave with a scored gap map, a prioritized risk list your board or investors can review, and a phased roadmap scoped to your stage.
- Scored gap map vs. ISO 42001 / HIPAA / APRA
- Prioritized risk list
- Stage-scoped phased roadmap
- No multi-month commitment required
Day 0 Migration Blueprint & Discovery
For CTOs and Program Directors preparing for major infrastructure shifts. Delivered in 4–6 weeks. Audit your legacy data estate and surface hidden debt and technical risk. Run structured discovery workshops. Produce a phased, board-ready cloud-native migration roadmap. Close with a validated proof-of-concept architecture and an execution-ready risk register.
- Legacy data estate audit & debt mapping
- Technical risk register construction
- Cloud-native migration roadmap
- Executive risk register & validated POC
ISO 42001 AI Trust & Governance Readiness
For organisations scaling ML or integrating Generative AI who must demonstrate algorithmic safety to their board, regulator, or enterprise procurement. Delivered in 4 weeks.. Design an AI Management System tailored to your data estate. Cover model versioning pipelines, data ingestion loops, risk classification, and lifecycle controls. Deliver an ISO 42001 alignment roadmap and structured AI risk inventory. Scoped for the window that exists right now before EU AI Act enforcement begins August 2026
- AI Management System (AIMS) design & scoping
- Model versioning pipeline evaluation
- ISO 42001 alignment roadmap & risk inventory
- Lifecycle control frameworks & board reporting
APRA CPG 235 / HIPAA Compliance Architecture
For Financial Services, Insurance, and Healthcare enterprises under active regulatory scrutiny. Automated data validation, profiling, and anomaly-detection built directly into ingestion and transformation pipelines. Verified end-to-end data lineage mapping. CPG 235-aligned control documentation. Audit-ready architecture your compliance team can present to regulators without qualification.
- Automated validation
- profiling & anomaly detection
- End-to-end data lineage mapping
- APRA CPG 235 & HIPAA control alignment
- Audit-ready architecture sign-off documentation
Enterprise Data Governance Framework Design
For organisations that need structured data governance standing up not a report recommending one. Delivered in 6–8 weeks.. Define critical data elements, ownership, and stewardship accountability structures. Establish metadata standards and data classification frameworks. Set quality threshold controls across your enterprise data estate. Built to DAMA-DMBOK standards; embeds into your operating model, not just documentation
- Critical data element definition
- Data ownership & stewardship model
- Metadata standards & data classification
- Quality thresholds & governance operating model
Fractional Head of Data Governance & Strategy
For mid-market enterprises that need executive data leadership without a full-time hire. Available 1–2 days per week. Shape your data governance operating model and AI governance roadmap. Mentor engineering teams and drive capability uplift. Hold vendors accountable at the executive level. Designed for organisations building toward regulatory compliance or board-level data maturity
- Data & AI governance operating model design
- AI strategy & ISO 42001 roadmap advisory
- Engineering team mentorship & capability uplift
- Vendor accountability & board-level reporting
Legacy Systems Don't Modernise Themselves
We operate across the full stack from SQL Server and SSIS legacy estates to AWS, Databricks, Snowflake, dbt Core, and Apache Airflow. No proprietary frameworks, no vendor lock-in. Governance controls embedded in code, not maintained in spreadsheets. Clean, decoupled, auditable data architecture. Built for long-term resilience and platform independence
- AWS · Databricks · Snowflake · GCP · Azure
- dbt Core · Apache Airflow · DuckDB · Spark
- SQL Server & SSIS legacy migration
- CI/CD pipeline deployment & automated testing
Governance Embedded, Not Retrofitted
We’ve seen what happens when governance is treated as a project phase rather than an architectural principle. Governance controls written into code from day one. Lineage mapped before go-live, not after an audit. Quality gates automated before pipelines reach production. Audit-readiness as a delivery standard, not an emergency response
- Governance-by-design
- not retrofit
- Quality gates automated at ingestion
- Lineage mapped before production
- Audit-readiness as a delivery standard
Why Founders and Enterprise Leaders Both Work With Etherion
Most consultancies are strong on engineering or strong on governance. Etherion was built to be lean, senior, and without Big 4 overhead because regulated industries can't afford the gap between them, at any company size.
BSI
ISO 42001
Lead Implementer Practitioner
DAMA
DAMA-DMBOK
Certified Data Management Professional
15 Years
Experience
Regulated FS, Insurance, Healthcare Delivery
Markets
AU · EU · US
Cross-market regulatory experience
Common Questions From Founders and Enterprise Leaders
Straight answers before you book a call.
We're a lean, early-stage startup. Is AI governance too early for us?
If you're selling AI into healthcare or finance, no, this is the cheapest point to build it correctly. Retrofitting governance after your first enterprise contract or funding round is far more expensive than designing it in now.
We already have compliance documentation. Isn't this just more paperwork?
No. Documentation describes what should happen; governance-by-design is the architecture that makes it actually happen, lineage mapped before go-live, quality gates automated at ingestion, model controls built into the pipeline. Auditors and enterprise buyers test the architecture, not the document.
How is this different from hiring compliance counsel or a Big 4 firm?
Counsel tells you what the regulation requires. Big 4 firms typically staff junior teams at enterprise rates. Etherion builds the technical architecture, data lineage, and AI lifecycle controls directly. Senior practitioners only, fixed scope, no offshored junior staffing.
What does an engagement cost and how is it scoped?
Every engagement is fixed-scope with a defined deliverable and timeline. Startups typically start with the AI Governance Readiness Snapshot (1-2 weeks, fixed price) before scoping larger work. Enterprise engagements are quoted per program based on the Day 0 discovery findings.
We don't have regulatory requirements yet. Why start now?
Your first hospital, insurer, or bank customer will impose them via procurement and vendor risk review, whether or not you've prepared. Governance debt compounds the longer your pipeline runs without it.
How do you handle AI-specific risk versus traditional data governance?
ISO 42001 requires an AI Management System covering model versioning pipelines, data ingestion loops, and risk classification across the full AI lifecycle, a layer traditional data governance frameworks don't address. Etherion maps both together so AI risk controls and data governance are one architecture, not two.
Still Treating Governance as a Phase Instead of a Foundation?
That's the gap that turns audits into findings and AI pilots into board-level risk. Talk to us before your next migration, model deployment, or compliance review