Customer evidence

How regulated organisations govern AI with AIRAS Cloud.

Real programmes, anonymised where appropriate, showing how teams move from fragmented AI awareness to a single, evidence-backed governance record.

Financial servicesIreland / EU

From spreadsheet inventory to governed AI register in eight weeks.

Organisation: A mid-sized European retail bank with operations in Ireland, Germany and the Netherlands.

The challenge

More than forty AI use cases were tracked across different risk, procurement and IT teams.
There was no single record of which systems were high-risk under the EU AI Act, who owned them, or what evidence existed.
The compliance deadline of 2 August 2026 was approaching while internal legal review was still manual.

The approach

Deployed a single AIRAS Cloud tenant with segregated workspaces for legal, risk, compliance and IT review.
Imported existing policy documents and vendor contracts to seed the discovery pipeline.
Ran the deterministic qualification engine against every registered use case to produce a defensible classification.

AI systems registered in the governed inventory

High-risk systems pre-classified with evidence packs

Weeks from tenant provisioning to executive report

100%

Append-only audit trail for every classification decision

“For the first time we can show our regulator exactly how we reached a classification, who reviewed it, and on what evidence.”
— Head of Model Risk, European retail bank

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HealthcareIreland

Clinical AI oversight with a clear chain of accountability.

Organisation: A private hospital group operating multiple sites across Ireland.

The challenge

Clinical decision-support tools, imaging algorithms and operational forecasting models were owned by different departments.
Patient-safety and data-protection teams needed a shared record that satisfied both clinical governance and EU AI Act expectations.
There was no consistent way to demonstrate human oversight for high-risk clinical AI.

The approach

Configured role-based access so clinical, legal, privacy and IT reviewers could each contribute without overreaching.
Linked every AI system to a named accountable owner, clinical workflow and evidence location.
Used the AIRAS oversight module to record review cadence, conditions of use and escalation paths.

Clinical and operational AI systems under governance

High-risk systems with documented human-oversight plans

Departments aligned on one governance record

Confidential data left the controlled environment

“The board wanted assurance that clinical AI was overseen, not just purchased. AIRAS gives us the record to prove it.”
— Chief Clinical Information Officer, Irish hospital group

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Life sciencesIreland / US

Global pharma pipeline governance from research to commercial.

Organisation: A biopharmaceutical company with R&D in Ireland and commercial operations in the United States and Europe.

The challenge

AI was used in compound screening, clinical-trial optimisation, pharmacovigilance signal detection and commercial analytics.
Different jurisdictions imposed different expectations, and the same system could be high-risk in one context and lower-risk in another.
The company needed a single source of truth that could be audited by both internal QA and external regulators.

The approach

Mapped each AI system to its jurisdiction, organisational role and intended use context.
Ran prohibited-practice and high-risk pre-classification screening against the EU AI Act baseline.
Created a material-change workflow so new indications, data sources or model versions triggered reassessment.

AI systems tracked across R&D, operations and commercial

Jurisdictional contexts modelled per system where needed

Assessments completed with reviewer segregation

Unified audit record spanning Ireland and US teams

“We needed governance that could travel with the product. AIRAS lets us show the same decision record to Irish, European and US stakeholders.”
— VP Regulatory Affairs, biopharmaceutical company

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TechnologyIreland / Remote

SaaS vendor proves AI governance to enterprise buyers.

Organisation: An Irish-founded B2B software company embedding generative AI features into its platform.

The challenge

Enterprise procurement teams began asking for evidence of AI governance, risk assessment and EU AI Act readiness.
The company had no formal AI register and no documented process for classifying new features.
Sales cycles were lengthening because security and legal reviews could not be answered quickly.

The approach

Used AIRAS Cloud to register every AI-powered feature, model provider and data flow.
Produced buyer-facing evidence packs directly from the assessment and decision records.
Established a lightweight governance operating procedure for new feature releases.

AI features registered and assessed

Enterprise procurement reviews supported with evidence packs

50%

Reduction in security-questionnaire turnaround time

Public trust centre page backed by the governed record

“Our customers stopped asking whether we had a process and started asking to see the record. That is what closes enterprise deals.”
— Chief Technology Officer, Irish B2B software company

Common outcomes

What these programmes share.

Defensible classification

Every high-risk determination is tied to a ruleset version, evidence item and named reviewer.

Deadline-ready workflow

Discovery, assessment, review and evidence are connected in one continuous process.

Executive visibility

Board and committee reports are generated from the same record the operational teams use.

Sales acceleration

Vendor and buyer-facing evidence packs shorten procurement and security reviews.

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Add your organisation to the evidence base.

Tell us your sector, your AI portfolio and your deadline. We will show you how AIRAS Cloud would build your governed record.

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