Sovereign foundation

One time-aware foundation for organisational AI.

Bring temporal graph, time-series, geospatial, vector and full-text workloads together with backend application logic for connected AI systems and digital twins.

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.

Model time and relationships

Represent entities, events and changing connections so applications can examine present and past state.

Query connected data

Combine graph, time-series, geospatial, semantic and full-text retrieval in one foundation.

Run application logic

Place backend logic, scheduling, authentication and service interfaces close to governed data.

Connect AI within the boundary

Expose authenticated interfaces and compute embeddings inside the customer-controlled environment where configured.

Product boundary

Data foundation, not every product responsibility

DB persists and queries data and authorised conversation state. Model Runtime performs inference. Assistants reasons and acts. Applications own their workflows.

Adoption outcome

Unify only where it reduces operational complexity

Review data models, workloads, recovery needs and integration boundaries against a versioned technical deployment.

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

A practical first step

Unify only where it reduces operational complexity

Review data models, workloads, recovery needs and integration boundaries against a versioned technical deployment.

Review a data architecture