Model deployment
Deploy models with managed licenses, artifacts, hardware and runtime configurations.
LARGE MODEL SERVING & INFERENCE RUNTIME
Deploy models, configure inference backends and expose model APIs in a controlled environment, supplying enterprise applications and AI service businesses.
WHO IT IS FOR
Enterprise AI teams, model service providers and compute operators building local model supply.
SovereignEngine
Deploy models with managed licenses, artifacts, hardware and runtime configurations.
AcceleratorStack provides the product-facing runtime layer, with GPUStack as a supported backend for model deployment, GPU scheduling and inference management.
Expose model endpoints to authorized applications with protocol-compatible routing.
Monitor model state, resource utilization and concurrent workloads, with capacity planning for stable service operations.
Engine supplies model execution and APIs. gateway-core connects directly to its model channels and manages products, customer quotas, charges and bills. Inference independently manages algorithm workloads and can consume model services; Compute is added when shared resource operations are needed.
Deployment & integration
Select models, hardware and the appropriate AcceleratorStack backend, then configure model APIs, monitoring and recovery workflows. GPUStack is a supported default backend.
Put it to work
A project delivery that combines the infrastructure products your team needs.
Explore 02 /A production loop from private data to releasable models.
Explore 03 /Build the commercial operations behind AI services, from branded storefronts and product pricing to quotas, charging and billing.
ExploreBusiness enquiries
Tell us what you want to build. We will help define the platform, delivery scope and next step.