Control where AI runs, who serves it, and what it costs.
Route by geography, security tier, provider allowlist, cost, latency, and SLA without exposing infrastructure complexity to users.
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Requests
1.8M
Capacity
94%
Latency
212ms
Central controls without exposing provider complexity to teams.
Define policy
Set geographic, provider, security, budget, latency, and reliability requirements.
Route workloads
QDivZero applies those constraints when selecting capacity for each production workload.
Operate consistently
Teams call stable runtime endpoints while infrastructure policy stays centrally governed.
Policy controls for regulated, cost-sensitive, and SLA-bound AI workloads.
EU-only routing
Keep eligible workloads inside European regions and providers when policy requires it.
Provider allowlists
Restrict routing to approved GPU clouds, hyperscalers, or private capacity partners.
Secure cloud tiers
Separate cheap, trusted, and secure capacity classes for different workload profiles.
Confidential compute options
Reserve stricter execution environments for sensitive models, prompts, and data paths.
SLA-aware routing
Prefer capacity that meets availability and latency targets for production services.
Custom capacity policy
Encode business-specific rules for cost ceilings, fallback behavior, and workload priority.
Set the infrastructure policy. Let teams build against stable AI APIs.
Use QDivZero to govern geography, provider access, security tier, cost, latency, and SLA from one control plane.