web/src/data/fabric/verticals.ts

import type { VerticalProfile } from './types';

export const VERTICALS: readonly VerticalProfile[] = [
  {
    id: 'terra',
    name: 'Terra',
    tagline: 'Real estate intelligence and property command.',
    operatingModel: 'Property lifecycle intelligence — from acquisition due diligence through operations to disposition, with continuous asset health monitoring.',
    primaryUsers: ['Asset managers', 'Acquisitions analysts', 'Property operations leads', 'Portfolio directors'],
    coreEntities: ['property', 'asset', 'deal', 'pipeline', 'vendor', 'tenant', 'inspection', 'lease', 'budget', 'maintenance event'],
    signalTypes: ['pipeline change', 'vendor delay', 'inspection issue', 'lease risk', 'maintenance escalation', 'budget variance', 'occupancy drift', 'document gap'],
    workflowTypes: ['deal review', 'vendor onboarding', 'inspection dispatch', 'lease renewal', 'budget approval', 'maintenance scheduling'],
    riskTypes: ['deal slippage', 'vendor failure', 'compliance gap', 'budget overrun', 'asset degradation', 'missed deadline'],
    approvalTypes: ['deal advance', 'vendor selection', 'budget exception', 'lease modification', 'maintenance escalation'],
    evidenceTypes: ['inspection_note', 'document', 'vendor_update', 'system_event'],
    outcomeTypes: ['deal advanced', 'vendor remediated', 'inspection closed', 'lease reviewed', 'budget stabilized', 'asset risk reduced'],
    keyMetrics: ['Portfolio NOI', 'Occupancy rate', 'Cap rate spread', 'Maintenance backlog', 'Vendor SLA compliance'],
    connectedA11oyLayers: ['Signal Mesh', 'Chainlight', 'Proof Chain', 'Sentra', 'Argo'],
    maturityStage: 'operational',
    priorityLevel: 'high',
    route: '/terra',
    colorToken: '#c9b787',
    icon: '▣',
    innovationSeed: {
      name: 'Property Consequence Simulator',
      description: 'Models cascading impact on portfolio NOI when a property-level risk materializes — vendor failure, occupancy drop, or capex spike.',
      researchBasis: 'Adapted from Monte Carlo portfolio stress testing (Glasserman 2003) and causal inference chains (Pearl 2009).',
      capability: 'Run "what-if" scenarios per property and see downstream impact on fund-level returns before the risk arrives.',
    },
  },
  {
    id: 'vessels',
    name: 'Vessels',
    tagline: 'Maritime intelligence, voyage economics, and fleet-risk command.',
    operatingModel: 'Voyage-centric fleet operations — voyage planning, execution monitoring, deviation detection, and post-voyage settlement with sanctions and compliance checks.',
    primaryUsers: ['Fleet managers', 'Chartering desks', 'Operations controllers', 'Compliance officers'],
    coreEntities: ['vessel', 'voyage', 'port', 'route', 'AIS signal', 'charter', 'cargo', 'sanctions screen', 'fuel cost', 'weather event'],
    signalTypes: ['AIS gap', 'port delay', 'route deviation', 'sanctions flag', 'weather disruption', 'fuel variance', 'demurrage risk', 'cargo exception'],
    workflowTypes: ['voyage planning', 'route optimization', 'sanctions screening', 'bunker procurement', 'port scheduling', 'demurrage claim'],
    riskTypes: ['compliance risk', 'route risk', 'port risk', 'sanctions risk', 'cost overrun', 'safety exposure', 'operational delay'],
    approvalTypes: ['route deviation', 'sanctions override', 'bunker purchase', 'port change', 'cargo exception'],
    evidenceTypes: ['voyage_signal', 'document', 'scanner_result', 'system_event'],
    outcomeTypes: ['voyage optimized', 'compliance cleared', 'route adjusted', 'cost exposure reduced', 'exception resolved'],
    keyMetrics: ['Fleet utilization', 'Voyage P&L', 'Sanctions clearance rate', 'AIS coverage', 'Demurrage exposure'],
    connectedA11oyLayers: ['Signal Mesh', 'Chainlight', 'Proof Chain', 'Sentra', 'Argo'],
    maturityStage: 'operational',
    priorityLevel: 'critical',
    route: '/vessels',
    colorToken: '#8a8a8a',
    icon: '⚓',
    innovationSeed: {
      name: 'Voyage Cascade Analyzer',
      description: 'Traces how one maritime event — port closure, weather system, sanctions flag — propagates across the fleet as a dependency cascade.',
      researchBasis: 'Adapted from network contagion models (Barabasi 2002) and supply-chain disruption propagation (Ivanov & Dolgui 2020).',
      capability: 'Detect second-order fleet impacts from a single event before they materialize — e.g., one port delay cascading into 4 vessels missing their laycan windows.',
    },
  },
  {
    id: 'counsel',
    name: 'Counsel',
    tagline: 'Legal matter command, deadline intelligence, and proof-backed workflows.',
    operatingModel: 'Matter lifecycle management — from intake through discovery, filing, and resolution, with continuous deadline tracking and evidence chain assembly.',
    primaryUsers: ['Managing attorneys', 'Paralegals', 'Claims adjusters', 'Compliance counsel'],
    coreEntities: ['matter', 'claimant', 'policy', 'filing', 'deadline', 'evidence', 'demand', 'response', 'attorney review', 'court date'],
    signalTypes: ['deadline approaching', 'missing evidence', 'policy conflict', 'document inconsistency', 'filing status change', 'response overdue', 'matter risk increase'],
    workflowTypes: ['matter intake', 'discovery management', 'filing preparation', 'demand response', 'evidence assembly', 'attorney review'],
    riskTypes: ['missed deadline', 'evidentiary gap', 'compliance issue', 'adverse decision', 'duplicate work', 'weak proof chain'],
    approvalTypes: ['filing submission', 'settlement authority', 'expert retention', 'demand response', 'evidence disclosure'],
    evidenceTypes: ['legal_workflow_note', 'document', 'email_summary', 'policy_clause'],
    outcomeTypes: ['filing prepared', 'evidence organized', 'deadline met', 'attorney review completed', 'matter posture improved'],
    keyMetrics: ['Deadline compliance', 'Evidence completeness', 'Matter cycle time', 'Filing accuracy', 'Attorney utilization'],
    connectedA11oyLayers: ['Signal Mesh', 'Proof Chain', 'Sentra', 'Verity', 'Hermes'],
    maturityStage: 'operational',
    priorityLevel: 'high',
    route: '/counsel',
    colorToken: '#c9b787',
    icon: '⚖',
    innovationSeed: {
      name: 'Matter Posture Predictor',
      description: 'Uses outcome memory from resolved matters to estimate disposition probability for active cases based on evidence completeness, deadline compliance, and opposing posture.',
      researchBasis: 'Adapted from survival analysis (Cox proportional hazards) and legal analytics (Katz et al. 2017, Supreme Court prediction).',
      capability: 'Surface a disposition probability band for each active matter, updated daily as evidence and deadline data change.',
    },
  },
  {
    id: 'carlota',
    name: 'Carlota Jo',
    tagline: 'Private residence and family-office operations command.',
    operatingModel: 'Household operations intelligence — vendor coordination, service scheduling, preference tracking, and privacy-safe task routing for high-touch advisory.',
    primaryUsers: ['Estate managers', 'Family office principals', 'Household staff coordinators', 'Advisory leads'],
    coreEntities: ['residence', 'household asset', 'vendor', 'staff task', 'event', 'maintenance issue', 'family preference', 'travel plan', 'inventory', 'service schedule'],
    signalTypes: ['vendor delay', 'household issue', 'service window change', 'asset maintenance due', 'event requirement', 'travel coordination gap', 'budget exception'],
    workflowTypes: ['vendor coordination', 'service scheduling', 'event planning', 'maintenance dispatch', 'inventory audit', 'travel arrangement'],
    riskTypes: ['service failure', 'missed preference', 'vendor risk', 'maintenance delay', 'privacy exposure', 'operational friction'],
    approvalTypes: ['vendor engagement', 'budget exception', 'service change', 'guest access', 'travel modification'],
    evidenceTypes: ['vendor_update', 'inspection_note', 'system_event', 'approval_record'],
    outcomeTypes: ['residence stabilized', 'vendor coordinated', 'task completed', 'preference honored', 'event supported', 'service risk reduced'],
    keyMetrics: ['Service SLA', 'Preference satisfaction', 'Vendor reliability', 'Maintenance currency', 'Privacy compliance'],
    connectedA11oyLayers: ['Signal Mesh', 'Sentra', 'Proof Chain', 'Argo'],
    maturityStage: 'seed',
    priorityLevel: 'medium',
    route: '/carlota-jo',
    colorToken: '#c9b787',
    icon: '◎',
    innovationSeed: {
      name: 'Preference Drift Detector',
      description: 'Detects when household preferences shift over time by comparing current service patterns against historical preference memory, flagging divergence before it becomes friction.',
      researchBasis: 'Adapted from concept drift detection (Lu et al. 2018) and recommendation system preference evolution (Koren 2009, Netflix Prize temporal dynamics).',
      capability: 'Alert estate managers when a preference is stale — e.g., seasonal food preferences, temperature settings, or vendor selection criteria have shifted.',
    },
  },
  {
    id: 'aegis',
    name: 'Aegis',
    tagline: 'Cybersecurity, defense operations, and control assurance command.',
    operatingModel: 'Continuous security posture management — vulnerability lifecycle, incident response, control monitoring, and compliance evidence assembly.',
    primaryUsers: ['CISO', 'Security engineers', 'SOC analysts', 'Compliance managers'],
    coreEntities: ['asset', 'identity', 'vulnerability', 'control', 'incident', 'alert', 'policy', 'evidence', 'ticket', 'remediation'],
    signalTypes: ['vulnerability finding', 'identity anomaly', 'control drift', 'alert spike', 'failed backup', 'patch gap', 'access review issue', 'compliance exception'],
    workflowTypes: ['vulnerability triage', 'incident response', 'patch management', 'access review', 'control assessment', 'compliance audit'],
    riskTypes: ['unauthorized access', 'control failure', 'unresolved vulnerability', 'incident escalation', 'audit gap', 'operational disruption'],
    approvalTypes: ['patch deployment', 'access grant', 'exception approval', 'incident escalation', 'control change'],
    evidenceTypes: ['scanner_result', 'ticket', 'system_event', 'audit_event', 'policy_clause'],
    outcomeTypes: ['vulnerability remediated', 'control restored', 'incident contained', 'access reviewed', 'audit evidence preserved'],
    keyMetrics: ['MTTD', 'MTTR', 'Vulnerability backlog', 'Control coverage', 'Compliance score'],
    connectedA11oyLayers: ['Signal Mesh', 'Chainlight', 'Proof Chain', 'Sentra', 'Pallas'],
    maturityStage: 'scaling',
    priorityLevel: 'critical',
    route: '/sentra',
    colorToken: '#f5f5f5',
    icon: '⬡',
    innovationSeed: {
      name: 'Control Entropy Monitor',
      description: 'Measures the rate at which security controls degrade over time — patches go stale, access reviews slip, backup tests fail — and predicts which controls will breach thresholds next.',
      researchBasis: 'Adapted from information entropy (Shannon 1948) applied to control effectiveness decay curves and reliability engineering (Weibull analysis).',
      capability: 'Predict which controls will fail before they fail, based on their historical entropy trajectory — not just current state.',
    },
  },
  {
    id: 'lyte',
    name: 'Lyte',
    tagline: 'Business observability and executive decision intelligence.',
    operatingModel: 'Executive observability layer — tracks initiatives, KPIs, ownership, dependencies, and decision velocity across the organization.',
    primaryUsers: ['C-suite', 'VP-level leaders', 'Strategy leads', 'Board advisors'],
    coreEntities: ['initiative', 'KPI', 'owner', 'dependency', 'decision', 'risk', 'milestone', 'report', 'department', 'workflow'],
    signalTypes: ['KPI drift', 'milestone slip', 'ownership ambiguity', 'decision delay', 'dependency blockage', 'scope change', 'budget variance', 'executive escalation'],
    workflowTypes: ['initiative review', 'KPI calibration', 'decision escalation', 'dependency resolution', 'board reporting', 'strategy alignment'],
    riskTypes: ['execution drift', 'accountability gap', 'delayed decision', 'reporting inconsistency', 'initiative failure', 'stakeholder misalignment'],
    approvalTypes: ['budget reallocation', 'initiative pivot', 'KPI target change', 'headcount request', 'strategy revision'],
    evidenceTypes: ['executive_decision', 'document', 'email_summary', 'system_event'],
    outcomeTypes: ['decision clarified', 'owner assigned', 'risk reduced', 'initiative stabilized', 'executive visibility improved'],
    keyMetrics: ['Decision velocity', 'KPI attainment', 'Initiative health', 'Ownership clarity', 'Board readiness'],
    connectedA11oyLayers: ['Signal Mesh', 'Chainlight', 'PSYCHE', 'Hermes', 'Pallas'],
    maturityStage: 'operational',
    priorityLevel: 'high',
    route: '/lyte',
    colorToken: '#c9b787',
    icon: '◆',
    innovationSeed: {
      name: 'Decision Cascade Map',
      description: 'Visualizes how one executive decision creates a dependency chain across departments and initiatives — showing which downstream decisions are blocked, accelerated, or invalidated.',
      researchBasis: 'Adapted from directed acyclic graph theory (Kahn topological sort, 1962) and organizational decision network analysis (March & Simon, bounded rationality).',
      capability: 'Before approving a decision, see its full blast radius — which 3 other decisions it unblocks and which 2 it forces to re-evaluate.',
    },
  },
  {
    id: 'sentra',
    name: 'Sentra',
    tagline: 'Security, policy, approval, and audit control plane.',
    operatingModel: 'Cross-vertical governance enforcement — every high-impact action across every vertical passes through Sentra for approval, policy check, and audit trail.',
    primaryUsers: ['Governance leads', 'Audit managers', 'Policy architects', 'Security reviewers'],
    coreEntities: ['approval', 'policy', 'exception', 'blocked action', 'audit event', 'secret fingerprint', 'rollback plan', 'risk score', 'control', 'reviewer'],
    signalTypes: ['approval requested', 'policy violation', 'rollback needed', 'secret detected', 'action blocked', 'evidence missing', 'risk threshold crossed'],
    workflowTypes: ['approval routing', 'policy enforcement', 'rollback execution', 'audit compilation', 'exception review', 'secret redaction'],
    riskTypes: ['unsafe action', 'missing approval', 'weak audit trail', 'policy bypass', 'irreversible change', 'secret exposure'],
    approvalTypes: ['action approval', 'exception grant', 'policy override', 'rollback authorization', 'secret access'],
    evidenceTypes: ['approval_record', 'audit_event', 'policy_clause', 'system_event'],
    outcomeTypes: ['approval granted', 'action blocked', 'rollback ready', 'evidence anchored', 'policy enforced'],
    keyMetrics: ['Approval latency', 'Policy coverage', 'Audit completeness', 'Rollback readiness', 'Exception rate'],
    connectedA11oyLayers: ['Covenant', 'Proof Chain', 'PSYCHE', 'Axiom', 'Verity'],
    maturityStage: 'scaling',
    priorityLevel: 'critical',
    route: '/sentra',
    colorToken: '#b08d52',
    icon: '⬢',
    innovationSeed: {
      name: 'Policy Contradiction Scanner',
      description: 'Detects conflicting policies across verticals — e.g., Terra vendor onboarding policy allows 48h turnaround while Sentra requires 5-day compliance review, creating an unresolvable conflict.',
      researchBasis: 'Adapted from formal constraint satisfaction (Dechter 2003) and policy algebra (Becker et al., XACML conflict detection).',
      capability: 'Before a new policy is enacted, scan it against all existing policies across all verticals and surface contradictions with resolution recommendations.',
    },
  },
] as const;

export const VERTICAL_MAP = Object.fromEntries(VERTICALS.map(v => [v.id, v])) as Record<string, VerticalProfile>;