Inventory and classify
Use cases, data classes, and model versions are registered with owners, DPIAs, and control objectives.
/ Conocimiento y gobernanza /
Cree los controles, las pistas de auditoría y el marco de riesgo que conviertan las implementaciones de IA de un pasivo en una parte gobernada y defendible de sus operaciones.
The problem
Teams are using AI tools nobody approved, on data nobody audited, producing outputs nobody can explain. The exposure grows daily.
Legal teams understand the regulation. Engineering teams don't. Nobody has translated policy into architecture.
Risk and compliance reviews happen at the end — when changing the system is expensive and the business is already committed.
Cómo funciona
Use cases, data classes, and model versions are registered with owners, DPIAs, and control objectives.
Human review, logging, drift checks, and rollback hooks are wired into prompts, tools, and deployment pipelines.
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.
Qué incluye
A governed layer across data, workflows, and handoffs—so teams ship safely and scale with metrics.
maps all AI use cases in your organisation and classifies them by EU AI Act risk tier
defines ownership, accountability (RACI), review cadence and escalation paths for every AI system
designs the oversight layer for high-risk systems — who reviews, what triggers review, how decisions are logged
data protection impact assessment templates adapted for AI and agentic systems
logging and traceability layer across AI systems so every decision can be explained and reviewed
gap analysis against current obligations and a sequenced implementation path — not legal advice, operational delivery
Impulsado por Thinkia Sentinel
Resultados
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.
Cómo trabajamos
Week 1–2
Use cases, data classes, and regulatory hooks are catalogued with accountable executives.
Week 3–5
Lifecycle gates, documentation, and monitoring are aligned to EU AI Act and internal policy.
Week 6–9
A subset of models and vendors runs through the full workflow; gaps become a backlog.
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.
Primer paso
We start with a focused session—no commitment—to map constraints and a sensible path.