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KI, der Ihr Vorstand, Ihre Rechtsabteilung und Ihre Aufsichtsbehörden zustimmen können.

Erstellen Sie die Kontrollen, Audit-Trails und das Risiko-Framework, die KI-Einsätze von einer Belastung zu einem kontrollierten, vertretbaren Teil Ihres Betriebs machen.

Book a governance session Zum Problem

The problem

When shadow ai with no visibility or control becomes the norm

  • Shadow AI with no visibility or control

    Teams are using AI tools nobody approved, on data nobody audited, producing outputs nobody can explain. The exposure grows daily.

  • EU AI Act obligations with no implementation path

    Legal teams understand the regulation. Engineering teams don't. Nobody has translated policy into architecture.

  • Governance that arrives after the build

    Risk and compliance reviews happen at the end — when changing the system is expensive and the business is already committed.

So funktioniert es

Governance that travels with the model—not a binder on a shelf

Schritt 1

Inventory and classify

Use cases, data classes, and model versions are registered with owners, DPIAs, and control objectives.

Schritt 2

Embed controls

Human review, logging, drift checks, and rollback hooks are wired into prompts, tools, and deployment pipelines.

Schritt 3

Report continuously

Dashboards for committees and regulators tie incidents, changes, and attestations to live systems.

Frameworks like EU AI Act readiness map to concrete checks—not checklists only.

KI, der Ihr Vorstand, Ihre Rechtsabteilung und Ihre Aufsichtsbehörden zustimmen können.

Leistungsumfang

What you get when you run this with Thinkia

A governed layer across data, workflows, and handoffs—so teams ship safely and scale with metrics.

AI inventory and risk classification

maps all AI use cases in your organisation and classifies them by EU AI Act risk tier

Governance framework design

defines ownership, accountability (RACI), review cadence and escalation paths for every AI system

Human oversight architecture

designs the oversight layer for high-risk systems — who reviews, what triggers review, how decisions are logged

DPIA patterns for AI

data protection impact assessment templates adapted for AI and agentic systems

Audit trail infrastructure

logging and traceability layer across AI systems so every decision can be explained and reviewed

EU AI Act compliance readiness

gap analysis against current obligations and a sequenced implementation path — not legal advice, operational delivery

Unterstützt von Thinkia Sentinel

Ergebnisse

What changes when this runs in production

6–10 weeks

From gap analysis to first compliant AI system in production

–80%

Share of ungoverned AI tools brought under formal oversight

–60%

Reduction in time to produce compliance documentation for a given AI system

Results vary by number of AI systems, regulatory context and existing documentation maturity.

So arbeiten wir

From policy PDFs to operating rhythm for AI and data risk

Frame risk

Week 1–2

Use cases, data classes, and regulatory hooks are catalogued with accountable executives.

Design controls

Week 3–5

Lifecycle gates, documentation, and monitoring are aligned to EU AI Act and internal policy.

Pilot register

Week 6–9

A subset of models and vendors runs through the full workflow; gaps become a backlog.

Enterprise embed

Week 10+

Dashboards, attestation cycles, and third-party reviews integrate with existing GRC tools.

Maturity and decentralisation of AI adoption change workload; we align waves to board priorities.

Loslegen

Ready to scope this for your context?

We start with a focused session—no commitment—to map constraints and a sensible path.

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