Align AI deployment with data-handling requirements
Use approved deployment regions and provider policies to align workloads with data-handling requirements.
Illustrative scenario
Illustrative privacy scenario: a team needs to run AI workloads while keeping data-handling decisions visible and aligned with internal requirements.
External APIs may raise questions about deployment region, prompt retention, model-improvement use, and access controls.
The workflow needs clear provider policies and deployment choices before sensitive workloads move into production.
How QDivZero can fit
QDivZero Compute can run supported models on selected private infrastructure. Teams can choose approved deployment regions and review provider policies for retention, access, and model-use requirements.
This keeps architecture and data-handling decisions in one deployment workflow. Final compliance and policy decisions remain with the deploying organization and selected providers.
How QDivZero fits in
Selected infrastructure
Deploy supported workloads on selected private tenant infrastructure.
Prompt-handling policy
Review retention and model-use settings for the selected deployment.
Policy alignment
Use approved deployment regions and provider policies to align workloads with data-handling requirements.
Illustrative workflow
Select approved deployment regions and provider policies for the workload
Review data handling with legal and security stakeholders
Confirm whether prompts are retained or used for model improvement
Document the controls needed for the deployment