Built around control, not uncontrolled AI access.
ClusterAI is designed for organizations that want to expand AI usage without losing control over data, users, capabilities and infrastructure.
Governance-first AI orchestration.
Private deployment
ClusterAI is designed for private deployment on the customer's infrastructure, with local models and internal data sources.
Data zones
Capabilities can be associated with public, internal, confidential or restricted data zones — routing respects those boundaries.
Role-aware access
Requests can be evaluated according to user role and capability permissions before reaching any model.
Governed context handoff
When a conversation moves from one capability to another, ClusterAI transfers only a compressed, filtered and authorized summary.
No daemon-side memory requirement
The selected daemon receives the governed context from the client. It does not need to retain history by itself.
Fallback and resilience
If a specialized capability is unavailable or saturated, ClusterAI can route to an allowed fallback.
Audit and observability
Administrators can see which capability answered, why it was selected, whether fallback occurred and which context was transferred.
Anti-abuse and protection
ClusterAI can apply rate limits, quotas, fast-fail behavior and provider protection to keep internal AI resources stable.
Enterprise hardening roadmap.
Items below describe planned enterprise hardening. Availability depends on deployment scope and pilot stage.
Private evaluation demo
A live evaluation environment exists, but it is not linked publicly. Access is shared directly with selected reviewers and design partners.
The public website intentionally does not expose the demo endpoint.
Public evaluation demos are protected by authentication and are not linked publicly.
Ready to turn AI prototypes into an internal AI service?
Your AI is the engine. ClusterAI is the operating layer that makes it usable across the enterprise.