AICOMPASS - EU Customer Trust & Safety

Trust position

AICOMPASS supports EU AI governance readiness; it does not claim legal advice, automated compliance certification, or production approval.

The demo is safe for customer conversations because it uses fictitious sample data, keeps human accountability explicit, and explains how decisions, evidence, approvals, and audit packs should be made defensible.

Safe

Fictitious sample data

No real personal data, customer data, employee data, candidate data, or regulated records are used in this customer-facing prototype.

EU-focused

Governance readiness

The product story is aligned to EU-style expectations around risk classification, transparency, privacy, human oversight, evidence, and auditability.

No overclaiming

Not a legal certification

AICOMPASS helps structure readiness and evidence; final legal interpretation and regulatory assurance remain with qualified customer stakeholders.

Customer-safe principles

1. Human accountabilityThe system supports decisions; it does not replace accountable business, legal, risk, privacy, or security approvers.

2. Evidence before approvalReadiness should be based on accepted evidence, reviewer comments, version history, and linked obligations/controls.

3. Explainable routingEvery route should show triggered rules, reason codes, required reviewers, required evidence, and override policy.

4. Privacy-aware demoExample use cases are fictional, and personal-data handling is described as a governance requirement, not processed in the demo.

5. Business relevanceEvery governance activity is connected to business value, launch readiness, cost, risk, and executive defensibility.

What to say to a customer

Customer question	Safe answer
Is this an EU AI Act compliance product?	It is an EU-focused AI governance readiness and evidence orchestration prototype, not a legal certification tool.
Is the data real?	No. Demo data is fictitious and used only to show the operating model.
Can it approve AI automatically?	No. It supports human review, evidence-backed approval, and accountable sign-off.
Can we adapt it to our policies?	Yes. The operating model is designed around configurable obligations, controls, reviewers, evidence, and workflow integration.
Why is it business-relevant?	It starts with AI opportunity value and carries the initiative through governance, execution, cost, monitoring, and audit.

EU-oriented readiness map

This is deliberately phrased as readiness support, not legal determination.

Readiness area	AICOMPASS support	Customer-owned decision
Risk classification	Captures triggers, route, reason code, and required reviewers.	Final classification and legal interpretation.
Transparency	Tracks transparency notice requirement, evidence, owner, and approval state.	Final notice wording and legal sufficiency.
Privacy and data protection	Tracks DPIA, data lineage, retention, access, and reviewer status.	DPO/legal approval and operational controls.
Human oversight	Tracks oversight plan, test evidence, reviewer comments, and launch gate.	Operational oversight design and accountability.
Auditability	Packages route rationale, evidence, approvals, gaps, residual risk, and monitoring state.	Audit conclusion and regulatory response.

Executive message

AICOMPASS helps the business scale AI while preserving control: every AI opportunity has a business owner, a risk route, required evidence, approval gates, and an audit-ready trail.