Serve approved models
Expose selected models through controlled endpoints for applications and authorised teams.
Sovereign foundation
Operate model inference on infrastructure you control.
Control which models run, when versions change and what operational information may leave the environment.
Status: Roadmap. Availability, release terms and supported deployment conditions will be published as dated capability records before the status changes.
Core capabilities
Designed around accountable organisational work.
Exact coverage, deployment requirements and limitations are documented for the selected version and use case.
Route workloads deliberately
Direct requests according to model policy, capability, availability and deployment boundary.
Control versions and updates
Test, approve, promote, retain or roll back versions through an organisation-defined process.
Observe local operation
Monitor health, capacity, usage and service behaviour within documented telemetry boundaries.
Product boundary
Execution remains separate from orchestration
Model Runtime executes inference. Model services prepare artefacts. Assistants orchestrates calls and actions. AI Guard applies release and runtime controls.
Adoption outcome
Operate with explicit resource and support boundaries
Plan capacity, model policy, updates, monitoring, support access and recovery before the first production workload.
Sovereignty matrix
Evaluate the deployment across six dimensions.
Product-specific answers are established through the deployment architecture and dated evidence record.
DataOperationalTechnologyJurisdictionKnowledgeExit
Review the trust model
Connected capabilities
See how this responsibility fits the platform.
Intelligence
Custom Model Engineering
Model selection, adaptation, evaluation, documentation and transfer for defined use cases.
Status · Roadmap
Intelligence
SovereignEU Assistants
Permission-aware assistants, agents, workflows and connectors with human approvals.
Status · Roadmap
Trust
SovereignEU AI Guard
Discover, inspect, validate, protect and evidence AI across its lifecycle.
Status · Roadmap
A practical first step
Operate with explicit resource and support boundaries
Plan capacity, model policy, updates, monitoring, support access and recovery before the first production workload.