The Zi Stack Architecture

System Architecture Overview

The Zi Stack is a federated system architecture designed to decompose operational bottlenecks through four interconnected technical modules. Each module operates independently while maintaining seamless integration through our GraphQL Federation layer.

Core Design Principles

Module A: Cöhr Console

The unified control plane for all Zi Stack operations. Provides single-pane-of-glass visibility across expertise pods, compliance status, and system health.

GraphQL Federation Schema

extend schema @link(url: "https://specs.apollo.dev/federation/v2.0")

type Query {
  expertisePod(id: ID!): ExpertisePod
  expertisePods(filter: PodFilterInput): [ExpertisePod!]!
  complianceStatus(framework: ComplianceFramework!): ComplianceReport
  auditEvents(since: DateTime!, limit: Int = 100): [AuditEvent!]!
  systemHealth: HealthStatus!
  quantumJobQueue: [QuantumJob!]!
}

type ExpertisePod @key(fields: "id") {
  id: ID!
  name: String!
  resourceProfile: ResourceProfile!
  status: PodStatus!
  availability: AvailabilitySchedule!
  integrations: [Integration!]!
  metrics: PodMetrics!
  quantumJobs: [QuantumJob!]! @requires(fields: "id")
}

type Integration {
  target: String!
  connector: ConnectorType!
  status: IntegrationStatus!
  lastSync: DateTime
  errorRate: Float
}

enum ComplianceFramework {
  SOC2_TYPE_II
  PCI_DSS
  SOX
  GDPR
  HIPAA
}

Expertise Pod Configuration

apiVersion: zi.us/v2
kind: ExpertisePod
metadata:
  name: zi-us-soc2-compliance-auditor
  namespace: zi-us-production
  labels:
    app.kubernetes.io/name: compliance-auditor
    zi.us/domain: compliance
spec:
  resourceProfile:
    type: senior-auditor-llm-enhanced
    compute:
      cpu: "4"
      memory: "16Gi"
      gpu: "nvidia-a100"
    scaling:
      minReplicas: 2
      maxReplicas: 10
      targetCPUUtilization: 70
      
  availability:
    schedule: "3d/wk"
    timezone: "America/New_York"
    
  integrations:
    - name: zi-us-sap-erp
      target: ZI_US_SAP_ERP
      connector: odbc-gateway-encrypted
      config:
        host: sap.zi-us.internal
        connectionPool: 20
      credentials:
        secretRef: zi-us-sap-credentials
        
    - name: zi-us-salesforce
      target: ZI_US_SALESFORCE
      connector: oauth2-proxy
      config:
        instanceUrl: https://zi-us.my.salesforce.com
        apiVersion: "58.0"
        
  complianceRules:
    - name: pci-dss-automated-checks
      schedule: "0 */4 * * *"
      controls: [PCI-DSS-1.1, PCI-DSS-3.4, PCI-DSS-8.2]
      
    - name: sox-control-testing
      trigger: monthly-close
      
  llmConfig:
    model: claude-3-opus
    capabilities: [anomaly-detection, evidence-summarization]
    temperature: 0.1

Module B: Quantum Algorithm Factory

Research and execution environment for quantum-enhanced algorithms with problem decomposition, hybrid scheduling, and algorithm versioning.

Backend Capabilities

Quantum Fraud Detection Algorithm

class QuantumFraudDetector:
    def __init__(self, n_features: int = 50):
        self.backend = zi.space.get_optimal_backend(
            problem_type='classification',
            qubits_required=self._calculate_qubits(),
            error_tolerance=1e-3
        )
        self.feature_map = self._build_feature_map()
        self.ansatz = self._build_ansatz()
        
    def _build_feature_map(self) -> FeatureMap:
        return QAOAFeatureMap(
            entanglement='full',
            reps=3,
            parameter_shift=True
        )
    
    async def predict(self, data: pd.DataFrame, shots: int = 10000):
        features = self.preprocess(data)
        circuits = [self.build_circuit(f) for f in features]
        
        result = await self.backend.run(
            circuits=circuits,
            shots=shots,
            optimization_level=3,
            resilience_level=2  # Error mitigation
        )
        
        probabilities = self._extract_probabilities(result)
        return self.neural_network(probabilities)

Module C: Quantum-Hybrid Data Fabric

Multi-tier data processing spanning edge, hybrid cloud, and specialized compute partitions.

Data Transformation Pipeline

CREATE MATERIALIZED VIEW zi_us_policies_quantum_ready
WITH (engine = 'zi_quantum_hybrid', replication_factor = 3) AS
SELECT 
    policy_id,
    premium,
    coverage,
    -- Quantum-encoded risk vector
    quantum_encode(
        ARRAY[age_factor, location_risk, claim_history_score],
        encoding_type => 'amplitude_embedding'
    ) AS q_risk_vector,
    -- Temporal graph via quantum walk
    TRAVERSE claim_history USING quantum_walk(
        max_depth => 5,
        walk_type => 'continuous_time'
    ) AS claim_graph_embedding
FROM zi_us_legacy.policies
WHERE migrate_status = 'pending'
OPTIMIZE USING quantum_annealing(timeout => '24h');

Module D: Hardware Abstraction Layer

On-premises quantum-classical hybrid infrastructure with FIPS 140-3 compliance.

Security & Compliance Architecture

Automated Compliance Engine

class AutomatedSOC2Compliance:
    CONTROL_MAPPINGS = {
        'CC6.1': {'name': 'Logical Access', 'checks': ['verify_rbac', 'audit_privileged_access']},
        'CC7.1': {'name': 'System Operations', 'checks': ['verify_encryption', 'check_backups']},
        'CC8.1': {'name': 'Change Management', 'checks': ['audit_key_rotation', 'verify_approvals']}
    }
    
    async def continuous_monitoring(self) -> ComplianceReport:
        results = {}
        for control_id, spec in self.CONTROL_MAPPINGS.items():
            check_results = await asyncio.gather(*[
                self._execute_check(check) for check in spec['checks']
            ])
            results[control_id] = self._aggregate_results(check_results)
            
        evidence_hash = await self.evidence_collector.store(results)
        blockchain_tx = await self.zi_blockchain.submit_evidence(evidence_hash)
        
        return ComplianceReport(
            framework='SOC2 Type II',
            status=self._overall_status(results),
            evidence_hash=evidence_hash,
            auditor_access='real-time via Cöhr Console'
        )

API Reference

Technical Resources

• Full API documentation (OpenAPI 3.0)
• Threat model documentation and security white papers
• Reference implementations for enterprise workflows
• Performance benchmark reports
• Quantum algorithm research papers