AI Governance Orchestrator is a specialized engine designed to manage, audit, and secure private AI agents. It serves as the "Command Center" for local intelligence, ensuring that every AI decision is traced, evaluated, and compliant with sovereign security standards.
This repository focuses on the Operational Orchestration of tools like OpenClaw, Ollama, and Arize Phoenix within a unified environment.
flowchart TD
%% Global Styling
classDef default fill:#f9f9f9,stroke:#333,stroke-width:1px,color:#333,font-family:Inter,sans-serif;
classDef security fill:#e1f5fe,stroke:#01579b,stroke-width:2px;
classDef orchestrator fill:#ede7f6,stroke:#4527a0,stroke-width:2px;
classDef intelligence fill:#e8f5e9,stroke:#2e7d32,stroke-width:2px;
classDef governance fill:#fff3e0,stroke:#e65100,stroke-width:2px,stroke-dasharray: 5 5;
classDef infra fill:#eceff1,stroke:#455a64,stroke-width:1px;
%% Nodes & Structure
User((👤 User / Admin))
subgraph PERIMETER [Zero-Trust Access Perimeter]
direction LR
TS[Tailscale Node] --- CF[Cloudflare Tunnel]
GW[Reverse Proxy / Ingress]
end
subgraph CORE [Orchestration Layer]
OC{{OpenClaw Engine}}
N8N[n8n Automation]
end
subgraph BRAIN [Sovereign Intelligence]
direction TB
LI[LlamaIndex RAG] --- VDB[(Vector DB)]
OL[Ollama LLM]
end
subgraph AUDIT [Governance & Observability]
PHX[Arize Phoenix Dashboard]
end
%% Connections
User ==>|Secure Access| GW
GW ==> OC
OC <==>|Event Trigger| N8N
OC ==>|Context Query| LI
OC ==>|Local Inference| OL
%% Audit Trails (Dashed lines for clarity)
OC -.->|Trace Data| PHX
LI -.->|Eval Spans| PHX
OL -.->|Token Logs| PHX
%% Assign Classes
class TS,CF,GW security;
class OC,N8N orchestrator;
class LI,VDB,OL intelligence;
class PHX governance;
| Symbol/Style | Description | Classification (ISO/C4) |
|---|---|---|
| Double Circle (( )) | External Actor (User, Admin, or External Trigger) | Person |
| Hexagon {{ }} | Decision Engine / Logic Controller (OpenClaw) | Component |
| Cylinder [( )] | Data Persistence Layer (Vector Database) | Container (Store) |
| Bold Line (==>) | Primary Data Flow (Requests & Inference) | Primary Relation |
| Dashed Line (-.->) | Secondary Flow (Audit, Traces, Eval Metadata) | Dependency / Trace |
| Blue Box | Security & Access Management Layer | Infrastructure |
| Purple Box | Core System Orchestration | Logic Layer |
| Green Box | Local Intelligence & RAG System | Intelligence Layer |
| Orange Box | System Compliance & Observability | Governance Layer |
Acts as the central nervous system. It manages agentic workflows, deciding when to search the local knowledge base or trigger an external automation. It ensures that LLM interactions follow predefined safety and logic bounds.
Provides the raw inference power using local models like DeepSeek-R1 or Qwen-2.5. By running Ollama within the same network, we eliminate latency and data privacy risks associated with third-party APIs.
Provides "Context Sovereignty." It indexes private documents (PDFs, Markdown, Wikis) into a local vector database. When a query is made, LlamaIndex injects only the relevant private context into the prompt, ensuring the LLM remains grounded in factual, private data.
This is the "Governance" anchor. It records every trace, span, and retrieval step.
- Audit: Who asked what, and what context was retrieved?
- Evaluation: Did the LLM hallucinate? Was the retrieved context relevant?
- Sovereignty: Unlike SaaS alternatives, Phoenix runs locally, keeping the audit trail private.
Handles the "External World" integration. It acts as the sensor and actuator, pulling data from GitHub, SQL databases, or internal APIs and feeding it into the OpenClaw orchestration loop.
- Request: A user or an n8n trigger sends a request to OpenClaw.
- Context Retrieval: OpenClaw asks LlamaIndex for relevant private data.
- Inference: OpenClaw sends the prompt + context to Ollama.
- Tracing: Throughout the process, Arize Phoenix captures the metadata (Prompts, Token usage, Retrieval accuracy).
- Validation: Arize Phoenix runs automated Evals to ensure the response is safe and accurate before it is delivered.
- Response: The final, audited answer is sent back to the user/trigger.
| Layer | Technologies |
|---|---|
| Orchestration |   |
| Intelligence |   |
| Governance |  |
| Infrastructure |     |
| Security |   |
To instantly deploy and test the multi-node Zero-Trust AI architecture on your local machine, run our single-command simulation installer:
curl -sL https://raw.githubusercontent.com/patabuga/ai-governance-orchestrator/main/simulate.sh | bashNote: This requires Docker and Docker Compose to be installed on your system. It will safely orchestrate isolated virtual networks to demonstrate the sovereign infrastructure concept.
Standardized by PES AI-Assistant (Gemini CLI) Sovereign Infrastructure Compliance v1.0