Enterprise Deployment Architecture

A production-grade reference architecture for deploying ContextGraph OS with agents, RAG, policies, and human review workflows.

Architectural Philosophy

ContextGraph OS is not another agent framework. It is the governance spine that sits between agent cognition and real-world action.

The architecture enforces a simple but powerful rule:

No agent action is valid unless it is context-justified, policy-evaluated, and decision-traceable.

This is achieved by separating four planes:

High-Level System Diagram

┌───────────────────────────────────────────────────────────┐
│                   Enterprise Interfaces                   │
│  (Dashboards · Audit · Compliance · Admin · CLI · API)    │
└───────────────────────────────────────────────────────────┘
                ▲                        ▲
                │                        │
        Human Review Plane        Audit / Export Plane
                │                        │
┌───────────────────────────────────────────────────────────┐
│               ContextGraph OS (Core)                       │
│                                                           │
│  ┌──────────────┐   ┌──────────────┐   ┌──────────────┐  │
│  │ Knowledge     │   │ Policy Engine│   │ Decision     │  │
│  │ (Claims + KG) │◄──┤ (Deny-first) │──►│ Trace Graph  │  │
│  └──────────────┘   └──────────────┘   └──────────────┘  │
│           ▲                   ▲                   │      │
│           │                   │                   │      │
│  ┌──────────────┐     ┌──────────────┐     ┌──────────┐ │
│  │ Provenance   │     │ Exceptions   │     │ Telemetry│ │
│  │ Ledger       │     │ & Approvals  │     │ & RBAC   │ │
│  └──────────────┘     └──────────────┘     └──────────┘ │
└───────────────────────────────────────────────────────────┘
                ▲
                │
┌───────────────────────────────────────────────────────────┐
│              Agent Runtime Layer                           │
│  (LangChain / AutoGen / Custom Agents / Tools)             │
└───────────────────────────────────────────────────────────┘
                ▲
                │
┌───────────────────────────────────────────────────────────┐
│            Data + RAG Infrastructure                       │
│  (Vector DB · Search · Docs · APIs · OSINT · Internal)     │
└───────────────────────────────────────────────────────────┘

Component Breakdown

Agent Runtime Layer (Pluggable)

Supported Frameworks:

• LangChain / LangGraph
• CrewAI / AutoGen
• Custom internal agents
• Deterministic tools (APIs, scripts, workflows)

Key Rule: Agents never execute tools directly. They submit Action Intents to ContextGraph OS.

// Agent submits intent, not execution
agent.requestAction({
  type: "publish_report",
  target: "external_audience",
  risk: "HIGH",
  contextQuery: {
    entityId: reportId,
    minConfidence: 0.8,
  }
});

Knowledge Plane (Contextual RAG + Claims)

This is where ContextGraph OS diverges sharply from typical RAG.

Instead of: "Here are top-k chunks"

ContextGraph stores: Claims with full context:

{
  "entity": "Market_Analysis_Q4",
  "claim": "Revenue growth projected at 15%",
  "validFrom": "2024-10-01",
  "validUntil": "2024-12-31",
  "confidence": 0.85,
  "source": "Internal Finance Report",
  "provenanceHash": "0x9af3..."
}

This enables:

• Time-travel queries ("What did we know in March?")
• Contradiction coexistence (multiple sources, different claims)
• Evidence-weighted reasoning
• Audit-ready provenance

Policy Engine (Deny-First by Design)

Policies are evaluated before any execution.

policy:
  name: external_publish_guard
  effect: deny
  when:
    action: publish
    target: external_audience
    risk: [HIGH, CRITICAL]
  then:
    require_approval: true
    approvers: [role:compliance_officer, role:legal]

Policy evaluation flow:

Action Intent → Policy Engine → DENY (needs approval)
                    │
                    └──→ Exception Queue → Human Review → APPROVE/REJECT
                                                │
                                                └──→ Execution (if approved)

Human Review & Exception Workflow

When a policy denies an action:

1. Decision enters Exception Queue
2. Human reviewer sees:
   • Proposed action details
   • Evidence used (claims, entities)
   • Confidence levels
   • Policy that triggered denial
   • Risk assessment
3. Reviewer can:
   • Approve (with justification)
   • Reject (with reason)
   • Request more evidence

All outcomes are written into the Decision Trace Graph for permanent audit.

Execution Plane (Controlled Dispatch)

Execution only occurs after:

• Policy ALLOW, or
• Human approval for denied actions

// Execution is side-effect isolated and traceable
const result = await executor.dispatch({
  decisionId: approvedDecision.id,
  action: action,
  context: assembledContext,
});

// Full execution logged to provenance

Audit & Compliance Plane

Outputs:

• Quarterly AI decision reports
• Evidence summaries per decision
• Policy override logs
• Provenance verification hashes
• GDPR data subject reports

Export formats:

• JSON (machine-readable)
• PDF (human-readable)
• CSV (spreadsheet analysis)

Deployment Models

Option A: Central Governance Service (Recommended)

┌─────────────┐  ┌─────────────┐  ┌─────────────┐
│  Agent A    │  │  Agent B    │  │  Agent C    │
└──────┬──────┘  └──────┬──────┘  └──────┬──────┘
       │                │                │
       └────────────────┼────────────────┘
                        │
              ┌─────────▼─────────┐
              │  ContextGraph OS  │
              │  (Central Service)│
              └───────────────────┘

Benefits:

• Strongest audit posture
• Unified policy enforcement
• Cross-agent visibility
• Single source of truth

Option B: Embedded Mode

┌─────────────────────────┐
│        Agent A          │
│  ┌───────────────────┐  │
│  │  ContextGraph OS  │  │
│  │    (Embedded)     │  │
│  └───────────────────┘  │
└─────────────────────────┘

Benefits:

• Lower latency
• No network dependency
• Simpler deployment

Trade-offs:

• Reduced cross-org visibility
• Per-app audit silos

Option C: Hybrid

┌─────────────────────────────────────────┐
│     Central Policy + Provenance         │
└─────────────────────────────────────────┘
         ▲              ▲              ▲
         │              │              │
    ┌────┴────┐    ┌────┴────┐    ┌────┴────┐
    │ Agent A │    │ Agent B │    │ Agent C │
    │ (Local  │    │ (Local  │    │ (Local  │
    │  Cache) │    │  Cache) │    │  Cache) │
    └─────────┘    └─────────┘    └─────────┘

Benefits:

• Central governance
• Local performance
• Scalable architecture

Security Considerations

Data Classification

Access Control

• RBAC for all operations
• Policy-based action control
• Audit logging for all access
• SSO/SAML integration (Enterprise)

Network Security

• TLS 1.3 for all connections
• mTLS for service-to-service
• API key + JWT authentication
• Rate limiting

Next Steps

• Governance Deep Dive
• Policy Configuration
• Decision Trace Graph
• Compliance Reporting