fix(admin-v2): Restore complete admin-v2 application

The admin-v2 application was incomplete in the repository. This commit
restores all missing components:

- Admin pages (76 pages): dashboard, ai, compliance, dsgvo, education,
  infrastructure, communication, development, onboarding, rbac
- SDK pages (45 pages): tom, dsfa, vvt, loeschfristen, einwilligungen,
  vendor-compliance, tom-generator, dsr, and more
- Developer portal (25 pages): API docs, SDK guides, frameworks
- All components, lib files, hooks, and types
- Updated package.json with all dependencies

The issue was caused by incomplete initial repository state - the full
admin-v2 codebase existed in backend/admin-v2 and docs-src/admin-v2
but was never fully synced to the main admin-v2 directory.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

admin-v2/lib/sdk/demo-data/use-cases.ts

@@ -0,0 +1,85 @@
+/**
+ * Demo Use Cases for AI Compliance SDK
+ */
+
+import { UseCaseAssessment, AssessmentResult } from '../types'
+
+export const DEMO_USE_CASES: UseCaseAssessment[] = [
+  {
+    id: 'demo-uc-1',
+    name: 'KI-gestützte Kundenanalyse',
+    description: 'Analyse von Kundenverhalten und Präferenzen mittels Machine Learning zur Personalisierung von Angeboten und Verbesserung des Customer Lifetime Value. Das System verarbeitet Transaktionsdaten, Clickstreams und demographische Informationen.',
+    category: 'Marketing',
+    stepsCompleted: 5,
+    steps: [
+      { id: 'uc1-step-1', name: 'Grunddaten', completed: true, data: { type: 'customer-analytics', department: 'Marketing' } },
+      { id: 'uc1-step-2', name: 'Datenquellen', completed: true, data: { sources: ['CRM', 'Webshop', 'Newsletter'] } },
+      { id: 'uc1-step-3', name: 'KI-Komponenten', completed: true, data: { algorithms: ['Clustering', 'Recommender', 'Churn-Prediction'] } },
+      { id: 'uc1-step-4', name: 'Betroffene', completed: true, data: { subjects: ['Kunden', 'Interessenten'] } },
+      { id: 'uc1-step-5', name: 'Risikobewertung', completed: true, data: { riskLevel: 'HIGH' } },
+    ],
+    assessmentResult: {
+      riskLevel: 'HIGH',
+      applicableRegulations: ['DSGVO', 'AI Act', 'TTDSG'],
+      recommendedControls: ['Einwilligungsmanagement', 'Profilbildungstransparenz', 'Opt-out-Mechanismus'],
+      dsfaRequired: true,
+      aiActClassification: 'LIMITED',
+    },
+    createdAt: new Date('2026-01-15'),
+    updatedAt: new Date('2026-02-01'),
+  },
+  {
+    id: 'demo-uc-2',
+    name: 'Automatisierte Bewerbungsvorauswahl',
+    description: 'KI-System zur Vorauswahl von Bewerbungen basierend auf Lebenslauf-Analyse, Qualifikationsabgleich und Erfahrungsbewertung. Ziel ist die Effizienzsteigerung im Recruiting-Prozess bei gleichzeitiger Gewährleistung von Fairness.',
+    category: 'HR',
+    stepsCompleted: 5,
+    steps: [
+      { id: 'uc2-step-1', name: 'Grunddaten', completed: true, data: { type: 'hr-screening', department: 'Personal' } },
+      { id: 'uc2-step-2', name: 'Datenquellen', completed: true, data: { sources: ['Bewerbungsportal', 'LinkedIn', 'XING'] } },
+      { id: 'uc2-step-3', name: 'KI-Komponenten', completed: true, data: { algorithms: ['NLP', 'Matching', 'Scoring'] } },
+      { id: 'uc2-step-4', name: 'Betroffene', completed: true, data: { subjects: ['Bewerber'] } },
+      { id: 'uc2-step-5', name: 'Risikobewertung', completed: true, data: { riskLevel: 'HIGH' } },
+    ],
+    assessmentResult: {
+      riskLevel: 'HIGH',
+      applicableRegulations: ['DSGVO', 'AI Act', 'AGG'],
+      recommendedControls: ['Bias-Monitoring', 'Human-in-the-Loop', 'Transparenzpflichten'],
+      dsfaRequired: true,
+      aiActClassification: 'HIGH',
+    },
+    createdAt: new Date('2026-01-20'),
+    updatedAt: new Date('2026-02-02'),
+  },
+  {
+    id: 'demo-uc-3',
+    name: 'Chatbot für Kundenservice',
+    description: 'Konversationeller KI-Assistent für die automatisierte Beantwortung von Kundenanfragen im First-Level-Support. Basiert auf Large Language Models mit firmeneigenem Wissen.',
+    category: 'Kundenservice',
+    stepsCompleted: 5,
+    steps: [
+      { id: 'uc3-step-1', name: 'Grunddaten', completed: true, data: { type: 'chatbot', department: 'Support' } },
+      { id: 'uc3-step-2', name: 'Datenquellen', completed: true, data: { sources: ['FAQ', 'Wissensdatenbank', 'Ticketsystem'] } },
+      { id: 'uc3-step-3', name: 'KI-Komponenten', completed: true, data: { algorithms: ['LLM', 'RAG', 'Intent-Classification'] } },
+      { id: 'uc3-step-4', name: 'Betroffene', completed: true, data: { subjects: ['Kunden', 'Interessenten'] } },
+      { id: 'uc3-step-5', name: 'Risikobewertung', completed: true, data: { riskLevel: 'MEDIUM' } },
+    ],
+    assessmentResult: {
+      riskLevel: 'MEDIUM',
+      applicableRegulations: ['DSGVO', 'AI Act'],
+      recommendedControls: ['KI-Kennzeichnung', 'Übergabe an Menschen', 'Datensparsamkeit'],
+      dsfaRequired: false,
+      aiActClassification: 'LIMITED',
+    },
+    createdAt: new Date('2026-01-25'),
+    updatedAt: new Date('2026-02-03'),
+  },
+]
+
+export function getDemoUseCases(): UseCaseAssessment[] {
+  return DEMO_USE_CASES.map(uc => ({
+    ...uc,
+    createdAt: new Date(uc.createdAt),
+    updatedAt: new Date(uc.updatedAt),
+  }))
+}