Déploiement

On-Premise AI

Définition

Deploying AI models on infrastructure owned and managed by the organisation rather than using cloud APIs. On-premise AI is preferred in regulated industries—banking, defence, healthcare—where data sovereignty, GDPR compliance, and latency requirements preclude sending data to external providers.

Termes Connexes

Edge AI

Running AI models on edge devices—industrial controllers, cameras, vehicles, mobile phones—rather than in the cloud. Edge AI reduces latency, preserves data privacy, and enables operation in environments with limited connectivity, making it critical for physical AI deployments.

Data Governance

The policies, processes, and standards that manage data availability, usability, integrity, and security throughout its lifecycle. Strong data governance is a prerequisite for trustworthy AI—the EU AI Act explicitly requires data governance practices for training, validation, and testing datasets.

GDPR + AI

The intersection of the General Data Protection Regulation with AI systems. Key tensions include the right to explanation for automated decisions (Article 22), data minimisation requirements that limit training data use, and purpose limitation that constrains repurposing of collected data for model training.

Services Connexes

Eu Ai Act Compliance

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