From isolated AI tools to a governed internal AI capability network.
ClusterAI is the control path that makes your internal AI stack usable as an enterprise service — declared, routed, governed and observed.
Seven primitives that turn AI tools into an internal AI service.
Capability declaration
Each daemon declares what it can do — domains, custom tags, data zones, model class, supported capabilities and status. The registry turns informal AI tools into discoverable enterprise services.
Routing by intent, role, data zone and health
Each request is matched against declared capabilities, evaluated against user permissions and routed only to nodes that are allowed and healthy.
Conversation continuity
ClusterAI tracks the conversation across turns and capability switches, so users keep one chat instead of one chat per tool.
Governed handoff
When a conversation moves between capabilities, the client transfers only a compressed, filtered and authorized summary — never the raw history.
Fallback and resilience
If a specialized capability is unavailable or saturated, ClusterAI can route to an allowed fallback such as a high-performance GPU node.
Admin visibility
Administrators can inspect which capability answered, why it was selected, whether fallback happened and what context was transferred.
Model and runtime flexibility
Designed to work with local and OpenAI-compatible runtimes — Ollama, vLLM, TGI, LiteLLM, LocalAI and internal APIs.
Operational visibility built in.
A look at the kind of view operators get — node status, data zones, latency, fallback state and recent routing decisions.
| Node | Capability | Status | Zone | Latency | Fallback |
|---|---|---|---|---|---|
| N-LGL-01 | Legal AI | online | confidential | 412 ms | — |
| N-CTR-02 | Contract AI | online | confidential | 538 ms | — |
| N-HR-03 | HR / RAG | online | internal | 287 ms | — |
| N-CDE-04 | Code AI | online | internal | 601 ms | — |
| N-COM-05 | Commercial AI | online | internal | 344 ms | — |
| N-PRD-06 | Product AI | online | internal | 356 ms | — |
| N-GEN-07 | Generalist AI | online | public | 198 ms | — |
| N-GPU-08 | GPU fallback | degraded | internal | 1.2 s | active |
- 12:42:08N-CTR-02
contract liability review
reason: domain match + authorized
- 12:42:11N-HR-03
remote work policy
reason: RAG specialist preferred
- 12:42:14N-CDE-04
python stack trace
reason: code-class intent
- 12:42:19N-COM-05
pilot offer draft
reason: commercial intent + internal zone
- 12:42:23N-GPU-08
long-context summary
reason: fallback — specialist saturated
How ClusterAI compares.
ClusterAI does not replace your models. It makes them operable, governable and scalable.
Traditional chatbot vs ClusterAI
- One model answers everything
- No notion of internal capabilities
- No data-zone or role awareness
- No routing reason, no fallback
- Many specialized internal AI capabilities
- Capability registry with declared scope
- Data zones and role-aware routing
- Explainable routing with fallback paths
Classic load balancer vs ClusterAI
- Sees servers and ports
- Routes by health and round-robin
- Has no domain knowledge
- Cannot reason about data permissions
- Sees AI capabilities, not just servers
- Routes by intent + zone + health + fit
- Aware of domain, tags and capability class
- Enforces data-zone and role permissions
RAG builder vs ClusterAI
- Builds individual AI applications
- Each app is its own silo
- Limited cross-app governance
- Hard to operate as one enterprise service
- Turns applications into routable nodes
- One control plane for the whole network
- Cross-capability governance and audit
- Enterprise-grade operability across teams
LLM gateway vs ClusterAI
- Routes by model endpoint
- Focused on API access, budgets, logs
- No business-capability awareness
- Limited internal context understanding
- Routes by business capability
- Considers data zone, role and conversation
- Integrates capabilities, not just models
- Designed for internal AI service operation
A load balancer sees servers. ClusterAI sees AI capabilities.
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.