The engineering platform forrepeatable AI delivery
Stop rebuilding the same integrations for every AI project. SmartSpace provides shared data connectivity, model access, identity and governance services inside your Azure tenant, so engineering teams configure new capabilities on a foundation that already exists.
Shared services architecture
Connect once. Reuse across every Workspace.
Governance at the platform layer
Entra ID, RBAC and audit controls applied from day one
Deployed in your Azure tenant
Your data and AI stay inside your own environment. You control the deployment boundary, residency and policy.
Stop rebuilding integrations
Approved connections to systems, databases and content stores are shared across Workspaces, not recreated for each one.
Centralise how AI is deployed
Shared model access, workflow execution and configuration patterns that every Workspace builds on.
Identity and access controls
Entra ID, RBAC and audit logging applied at the platform layer, so each Workspace inherits a consistent model.
Build the shared services once. Reuse them across every Workspace.
Most AI projects rebuild the same integrations, identity configuration and governance controls for each deployment. SmartSpace establishes those as shared services at the platform layer. Each new Workspace configures against what already exists rather than starting over.
Connectors, identity configuration and governance controls are shared services. Each new Workspace configures against them rather than recreating them, which reduces the setup work before delivery can start.
New Workspaces draw on existing connections, access controls and orchestration patterns. Expanding to a new team or use case is a configuration task, not a new infrastructure project.
Identity, audit and compliance controls sit at the platform layer, so each Workspace inherits them rather than requiring separate configuration. The same controls apply as you add teams and data sources.
Three service layers. One shared foundation.
Data connectivity, model access and identity controls are provisioned once at the platform layer. Every Workspace inherits them rather than requiring separate setup.
Data Connectivity
Connect approved sources once. Every Workspace uses them.
Shared system connectors
Files, databases, content stores and line-of-business systems registered at the platform layer and available to all Workspaces
Indexing and vectorisation
Content indexed and vectorised on ingestion, searchable across approved sources without per-Workspace configuration
Ingestion pipelines
Configurable transformation, deduplication and routing across structured and unstructured sources, preserving business context
Access-aware retrieval
Results are scoped to the permissions of the requesting identity, so users only surface content they are authorised to access
Model and Orchestration Services
Centralise how AI is accessed and how workflows run.
Azure OpenAI and AI Foundry access
Model endpoints configured at the platform level, so Workspaces reference shared resources without individual provisioning
Multi-step workflow orchestration
Sequential and parallel execution supporting agentic patterns, tool use and long-running operations
Structured inputs and outputs
Input schemas validated before processing and output schemas enforced before delivery, so data conforms at both ends of each workflow. Part of the platform extensibility framework.
Explore platform extensibilityConfigurable models and context
Adjust model selection, retrieval depth and context window per Workspace without rebuilding the service
Identity, Governance and Deployment
Platform-layer controls inherited by every Workspace.
Entra ID integration
SSO, group-based RBAC and conditional access applied at the platform layer, so each Workspace inherits a consistent identity model
Azure tenant deployment
Deployed inside your Azure tenant, with your team controlling the resource group, network boundaries and update policy
Audit logging
Audit logs available within the SmartSpace platform and Azure Log Analytics.
REST API surface
Documented REST APIs and extensibility tools provide a flexible foundation for connecting SmartSpace with the systems, applications and workflows your organisation relies on
What changes when your team builds on shared services
Faster time to first Workspace
Shared services are provisioned before your team configures the first Workspace, removing the platform setup phase that typically precedes AI delivery work.
Less engineering per project
Connections, identity and governance controls are shared services. Teams configure each new Workspace against them rather than rebuilding those services from scratch.
Controls applied consistently
Identity, audit and compliance policies sit at the platform layer. Each Workspace inherits them, so the same controls apply whether you are running one Workspace or twenty.
Delivery gets faster over time
Each Workspace reuses connections, access policies and orchestration patterns already in place. The engineering effort required tends to decrease with each successive capability.
Your tenant. Your control.
SmartSpace is deployed inside your Azure tenant, giving your organisation control over the platform, its connections, and how it operates within your Azure environment.
Deployed inside your Azure tenant
Platform services run inside your own Azure tenant. Your team controls the deployment boundary, network configuration and update policy.
Your team owns the lifecycle
Your team manages deployments, applies updates and defines integration policies. The platform operates under your governance model, not a shared SaaS boundary.
Identity and compliance built in
Entra ID, RBAC and audit logging are provisioned with the platform, not added as optional post-deployment configurations.
No data leaves your environment. Platform services run under your governance model inside your Azure tenant. Identity, audit and compliance controls are active from the point of deployment.
Built for the teams who own the platform
Integration tooling and REST APIs for engineering teams. Architecture and governance controls for platform architects. Operational visibility for the teams responsible for scale.
Integration and extensibility
- REST API surface for embedding capabilities in existing line-of-business applications
- Configurable retrieval strategies and context window control per Workspace
- Structured output schemas with validation before delivery to downstream systems
- Direct model endpoint access for approved integration patterns
- Custom connector support for systems outside the standard connector library
Architecture and governance
- Entra ID group-based RBAC with conditional access policy support
- Workspace isolation with shared platform-layer identity and governance
- Data governance policies defined once at the platform layer, inherited per Workspace
- Consistent access control boundaries across cross-team deployments
- Audit logs available within the SmartSpace platform and Azure Log Analytics
Operational visibility
- Usage and consumption metrics by Workspace and data source
- Performance monitoring with configurable alerting thresholds
- Capacity and scaling configurable through the SmartSpace platform
- Audit logs available within the SmartSpace platform and Azure Log Analytics
API documentation is included with the implementation programme
Endpoint references, authentication patterns and integration examples are delivered alongside deployment. Specific integration requirements can be discussed with the SmartSpace engineering team.
Ready to build your AI delivery platform inside Azure?
Deploy shared data connectivity, model access, identity and governance services inside your Azure tenant. Build the first Workspace on them, then reuse them for every capability that follows.
Deployed inside your Azure tenant. Identity, audit and governance controls active from day one. Each new Workspace builds on the same shared services.