feat(pitch-deck): update Engineering + AI Pipeline slides with current data
Engineering slide: - Woodpecker CI → Gitea Actions + Coolify - Stats: 481K LOC, 10 containers, 48+ modules, 14 Dockerfiles - Infrastructure: Hetzner + SysEleven (BSI) + OVH, no US providers - Service architecture: compliance-only (Frontend, Backend, Infra) AI Pipeline slide: - 38+ indexed regulations, 6,259 extracted controls, 325+ obligations - 6 Qdrant collections, 2,274+ chunks - UCCA policy engine (45 rules, E0-E3 escalation) - LLM: 120B on OVH + 1000B on SysEleven (BSI), via LiteLLM - QA: PDF-QA pipeline, Gitea Actions CI, Coolify deploy Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Benjamin Admin
@@ -37,16 +37,16 @@ export default function AIPipelineSlide({ lang }: AIPipelineSlideProps) {
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const [activeTab, setActiveTab] = useState<PipelineTab>('rag')
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const heroStats = [
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{ value: '19', label: de ? 'Indexierte Verordnungen' : 'Indexed Regulations', sub: 'DSGVO · AI Act · NIS2 · CRA · ePrivacy · ...', color: 'text-indigo-400' },
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{ value: '7', label: de ? 'Autonome Agenten' : 'Autonomous Agents', sub: de ? 'SOUL-basiert · Orchestriert' : 'SOUL-based · Orchestrated', color: 'text-purple-400' },
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{ value: '5', label: de ? 'KI-Modelle lokal' : 'Local AI Models', sub: 'Llama 3.2 · Qwen 2.5 · BGE-M3 · TrOCR · CrossEncoder', color: 'text-emerald-400' },
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{ value: '97', label: de ? 'Golden-Suite Tests' : 'Golden Suite Tests', sub: de ? 'Automatische Qualitaetssicherung' : 'Automatic Quality Assurance', color: 'text-amber-400' },
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{ value: '38+', label: de ? 'Indexierte Verordnungen' : 'Indexed Regulations', sub: 'DSGVO · AI Act · NIS2 · CRA · BDSG · DSA · ...', color: 'text-indigo-400' },
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{ value: '6.259', label: de ? 'Extrahierte Controls' : 'Extracted Controls', sub: de ? '79% Source-Match · 9 Verordnungen' : '79% source match · 9 regulations', color: 'text-purple-400' },
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{ value: '6', label: de ? 'Qdrant Collections' : 'Qdrant Collections', sub: de ? 'Legal Corpus · DSFA · Recht · Templates · ...' : 'Legal Corpus · DSFA · Law · Templates · ...', color: 'text-emerald-400' },
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{ value: '325+', label: de ? 'Abgeleitete Pflichten' : 'Derived Obligations', sub: de ? 'NIS2 · DSGVO · AI Act · CRA · ...' : 'NIS2 · GDPR · AI Act · CRA · ...', color: 'text-amber-400' },
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]
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const tabs: { id: PipelineTab; label: string; icon: typeof Brain }[] = [
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{ id: 'rag', label: de ? 'RAG-Pipeline' : 'RAG Pipeline', icon: Search },
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{ id: 'agents', label: de ? 'Multi-Agent-System' : 'Multi-Agent System', icon: Bot },
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{ id: 'quality', label: de ? 'Qualitaetssicherung' : 'Quality Assurance', icon: Gauge },
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{ id: 'agents', label: de ? 'UCCA & Engines' : 'UCCA & Engines', icon: Bot },
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{ id: 'quality', label: de ? 'QA & Infrastruktur' : 'QA & Infrastructure', icon: Gauge },
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]
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// RAG Pipeline content
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@@ -55,19 +55,19 @@ export default function AIPipelineSlide({ lang }: AIPipelineSlideProps) {
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icon: FileText,
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color: 'text-blue-400',
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bg: 'bg-blue-500/10 border-blue-500/20',
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title: de ? '1. Ingestion' : '1. Ingestion',
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title: de ? '1. Ingestion & QA' : '1. Ingestion & QA',
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items: de
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? ['PDF-Upload, URL-Crawling, API-Import', 'Automatische Spracherkennung (DE/EN)', 'Semantisches Chunking (rekursiv, 512 Tokens)', 'Metadaten-Extraktion (Verordnung, Artikel, Absatz)']
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: ['PDF upload, URL crawling, API import', 'Automatic language detection (DE/EN)', 'Semantic chunking (recursive, 512 tokens)', 'Metadata extraction (regulation, article, paragraph)'],
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? ['38+ PDF-Verordnungen (EU + DE + International)', 'Strukturelles Chunking an Artikel/Absatz-Grenzen', 'PDF-QA-Pipeline: 86% Artikel-Extraktion', 'Deduplizierung + Cross-Regulation Harmonisierung']
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: ['38+ PDF regulations (EU + DE + International)', 'Structural chunking at article/paragraph boundaries', 'PDF QA pipeline: 86% article extraction', 'Deduplication + cross-regulation harmonization'],
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},
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{
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icon: Cpu,
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color: 'text-purple-400',
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bg: 'bg-purple-500/10 border-purple-500/20',
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title: de ? '2. Embedding' : '2. Embedding',
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title: de ? '2. Embedding & LLM' : '2. Embedding & LLM',
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items: de
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? ['BGE-M3 Multilingual Embeddings (lokal)', 'CrossEncoder Re-Ranking (lokal)', 'HyDE: Hypothetical Document Embeddings', 'Lazy Model Loading (Speicher-optimiert)']
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: ['BGE-M3 multilingual embeddings (local)', 'CrossEncoder re-ranking (local)', 'HyDE: Hypothetical Document Embeddings', 'Lazy model loading (memory-optimized)'],
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? ['BGE-M3 Multilingual (1024-dim, lokal)', '120B LLM auf OVH (via LiteLLM, OpenAI-kompatibel)', '1000B LLM auf SysEleven (BSI-zertifiziert)', 'CrossEncoder Re-Ranking + HyDE']
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: ['BGE-M3 multilingual (1024-dim, local)', '120B LLM on OVH (via LiteLLM, OpenAI-compatible)', '1000B LLM on SysEleven (BSI-certified)', 'CrossEncoder re-ranking + HyDE'],
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},
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{
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icon: Database,
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@@ -75,8 +75,8 @@ export default function AIPipelineSlide({ lang }: AIPipelineSlideProps) {
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bg: 'bg-emerald-500/10 border-emerald-500/20',
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title: de ? '3. Vektorspeicher' : '3. Vector Store',
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items: de
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? ['Qdrant Vector DB (Self-hosted)', '5 Collections: Legal Corpus, DSFA, Compliance, Dokumente, Agenten-Wissen', 'MinIO Object Storage fuer Quelldokumente', 'Automatische Re-Indexierung bei Updates']
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: ['Qdrant Vector DB (self-hosted)', '5 Collections: Legal Corpus, DSFA, Compliance, Documents, Agent Knowledge', 'MinIO object storage for source documents', 'Automatic re-indexing on updates'],
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? ['Qdrant Vector DB (Hetzner, API-Key gesichert)', '6 Collections: CE, Recht, Gesetze, Datenschutz, DSFA, Templates', 'MinIO Object Storage (Hetzner, S3-kompatibel, TLS)', '2.274+ Chunks indexiert · HNSW-Index']
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: ['Qdrant Vector DB (Hetzner, API-key secured)', '6 Collections: CE, Law, Statutes, Privacy, DSFA, Templates', 'MinIO object storage (Hetzner, S3-compatible, TLS)', '2,274+ chunks indexed · HNSW index'],
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},
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{
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icon: Search,
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@@ -84,26 +84,26 @@ export default function AIPipelineSlide({ lang }: AIPipelineSlideProps) {
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bg: 'bg-indigo-500/10 border-indigo-500/20',
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title: de ? '4. Hybrid Search' : '4. Hybrid Search',
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items: de
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? ['Dense Retrieval (70%) + BM25 Keyword (30%)', 'Deutsche Komposita-Zerlegung', 'Cross-Encoder Re-Ranking der Top-K Ergebnisse', 'Quellen-Attribution mit Artikel-Referenz']
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: ['Dense retrieval (70%) + BM25 keyword (30%)', 'German compound word decomposition', 'Cross-encoder re-ranking of top-K results', 'Source attribution with article reference'],
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? ['Multi-Collection-Suche mit Whitelist-Validierung', 'Deutsche Komposita-Zerlegung', 'Cross-Encoder Re-Ranking der Top-K Ergebnisse', 'Quellen-Attribution mit Artikel/Absatz-Referenz']
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: ['Multi-collection search with whitelist validation', 'German compound word decomposition', 'Cross-encoder re-ranking of top-K results', 'Source attribution with article/paragraph reference'],
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},
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]
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// Multi-Agent System content
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// Multi-Agent System content — UCCA + Policy Engine
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const agents = [
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{ name: de ? 'Compliance-Berater' : 'Compliance Advisor', soul: 'compliance-advisor.soul.md', desc: de ? 'Beantwortet Compliance-Fragen mit RAG-Kontext' : 'Answers compliance questions with RAG context', color: 'text-indigo-400' },
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{ name: de ? 'Audit-Agent' : 'Audit Agent', soul: 'quality-judge.soul.md', desc: de ? 'Prueft Dokumente gegen regulatorische Anforderungen' : 'Checks documents against regulatory requirements', color: 'text-emerald-400' },
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{ name: de ? 'Dokument-Agent' : 'Drafting Agent', soul: 'drafting-agent.soul.md', desc: de ? 'Erstellt Compliance-Dokumente und Policies' : 'Creates compliance documents and policies', color: 'text-purple-400' },
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{ name: 'Orchestrator', soul: 'orchestrator.soul.md', desc: de ? 'Task-Routing und Koordination aller Agenten' : 'Task routing and coordination of all agents', color: 'text-amber-400' },
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{ name: de ? 'Alert-Agent' : 'Alert Agent', soul: 'alert-agent.soul.md', desc: de ? 'Monitoring, Fristen und Benachrichtigungen' : 'Monitoring, deadlines and notifications', color: 'text-red-400' },
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{ name: de ? 'Tutor-Agent' : 'Tutor Agent', soul: 'tutor-agent.soul.md', desc: de ? 'Interaktive Compliance-Schulungen' : 'Interactive compliance training', color: 'text-blue-400' },
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{ name: 'UCCA', soul: de ? 'Use-Case Compliance' : 'Use-Case Compliance', desc: de ? 'Policy Engine (45 Regeln) + Eskalation E0–E3' : 'Policy engine (45 rules) + escalation E0–E3', color: 'text-indigo-400' },
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{ name: de ? 'Pflichten-Engine' : 'Obligations Engine', soul: de ? '325+ Pflichten' : '325+ obligations', desc: de ? 'Multi-Regulation: NIS2, DSGVO, AI Act, CRA, ...' : 'Multi-regulation: NIS2, GDPR, AI Act, CRA, ...', color: 'text-emerald-400' },
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{ name: de ? 'Compliance-Berater' : 'Compliance Advisor', soul: de ? 'Legal RAG + LLM' : 'Legal RAG + LLM', desc: de ? 'Wizard-basierter Chatbot mit Qdrant-Kontext' : 'Wizard-based chatbot with Qdrant context', color: 'text-purple-400' },
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{ name: de ? 'Dokument-Generator' : 'Document Generator', soul: de ? '20 Templates' : '20 templates', desc: de ? 'AGB, DSE, AV-Vertrag, Widerruf + 16 weitere' : 'T&C, Privacy Policy, DPA, Withdrawal + 16 more', color: 'text-amber-400' },
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{ name: de ? 'DSFA-Agent' : 'DSFA Agent', soul: de ? 'Art. 35 DSGVO' : 'Art. 35 GDPR', desc: de ? 'Risikobewertung mit Legal Context Injection' : 'Risk assessment with legal context injection', color: 'text-red-400' },
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{ name: de ? 'Schulungs-Engine' : 'Training Engine', soul: de ? 'Academy + TTS' : 'Academy + TTS', desc: de ? '28 Module · Piper TTS · Automatische Videos' : '28 modules · Piper TTS · Automatic videos', color: 'text-blue-400' },
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]
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const agentInfra = [
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{ icon: MessageSquare, label: 'SOUL Files', desc: de ? 'Deklarative Agenten-Persoenlichkeit in Markdown' : 'Declarative agent personality in Markdown' },
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{ icon: Brain, label: 'Shared Brain', desc: de ? 'Gemeinsamer Wissensspeicher + Langzeitgedaechtnis' : 'Shared knowledge store + long-term memory' },
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{ icon: Network, label: 'Message Bus', desc: de ? 'Valkey/Redis · Pub/Sub · Task Queue' : 'Valkey/Redis · Pub/Sub · Task Queue' },
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{ icon: Activity, label: 'Session Manager', desc: de ? 'Heartbeat · Checkpoints · Recovery' : 'Heartbeat · Checkpoints · Recovery' },
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{ icon: Shield, label: de ? 'Policy Engine' : 'Policy Engine', desc: de ? 'Deterministisch · LLM ist NICHT Wahrheitsquelle' : 'Deterministic · LLM is NOT source of truth' },
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{ icon: Brain, label: de ? 'LLM-Schicht' : 'LLM Layer', desc: de ? '120B (OVH) + 1000B (SysEleven BSI) · EU-only' : '120B (OVH) + 1000B (SysEleven BSI) · EU-only' },
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{ icon: Network, label: 'LiteLLM Gateway', desc: de ? 'OpenAI-kompatibel · Multi-Provider Routing' : 'OpenAI-compatible · Multi-provider routing' },
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{ icon: Activity, label: de ? 'Eskalation E0–E3' : 'Escalation E0–E3', desc: de ? 'Auto-Approve → Team-Lead → DSB → DSB+Legal' : 'Auto-approve → Team lead → DPO → DPO+Legal' },
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]
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// Quality Assurance content
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@@ -111,34 +111,34 @@ export default function AIPipelineSlide({ lang }: AIPipelineSlideProps) {
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{
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icon: Shield,
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color: 'text-emerald-400',
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title: de ? 'BQAS — Quality Assurance System' : 'BQAS — Quality Assurance System',
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title: de ? 'Control Quality Pipeline' : 'Control Quality Pipeline',
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items: de
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? ['97 Golden-Suite-Referenztests fuer Regressionserkennung', 'Synthetische Testgenerierung per LLM', 'RAG-Retrieval-Accuracy und Correction-Tests', 'Precision, Recall, F1 Tracking ueber alle Releases']
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: ['97 golden suite reference tests for regression detection', 'Synthetic test generation via LLM', 'RAG retrieval accuracy and correction tests', 'Precision, recall, F1 tracking across all releases'],
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? ['6.259 Controls extrahiert (79% Source-Match)', '3.301 Duplikate entfernt (Phase 5 Normalisierung)', '90+ QA-Skripte: Deduplizierung, Match-Validierung', 'Canonical Controls JSON-Schema-Validierung in CI']
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: ['6,259 controls extracted (79% source match)', '3,301 duplicates removed (Phase 5 normalization)', '90+ QA scripts: deduplication, match validation', 'Canonical Controls JSON schema validation in CI'],
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},
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{
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icon: Eye,
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color: 'text-indigo-400',
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title: de ? 'LLM Evaluation & Vergleich' : 'LLM Evaluation & Comparison',
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title: de ? 'RAG Quality & Monitoring' : 'RAG Quality & Monitoring',
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items: de
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? ['Side-by-Side-Vergleich: Ollama lokal vs. OpenAI vs. Claude', 'Latenz-, Token- und Qualitaets-Metriken pro Provider', 'Automatischer Fallback bei Provider-Ausfall', 'Self-RAG: Selbstreflektierende Antwortvalidierung']
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: ['Side-by-side comparison: Ollama local vs. OpenAI vs. Claude', 'Latency, token and quality metrics per provider', 'Automatic fallback on provider failure', 'Self-RAG: Self-reflective answer validation'],
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? ['PDF-QA-Pipeline: 86% Artikel-Extraktion', 'Multi-Collection-Whitelist-Validierung', 'Qdrant-Deduplizierung: 8-Stufen-Bereinigung', 'Fallback-Handling: RAG-Fehler brechen nie Hauptfunktion']
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: ['PDF QA pipeline: 86% article extraction', 'Multi-collection whitelist validation', 'Qdrant deduplication: 8-step cleanup', 'Fallback handling: RAG failures never break main function'],
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},
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{
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icon: Sparkles,
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color: 'text-purple-400',
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title: de ? 'Document Intelligence' : 'Document Intelligence',
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title: de ? 'CI/CD & Testing' : 'CI/CD & Testing',
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items: de
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? ['TrOCR Handschrifterkennung mit LoRA Fine-Tuning', 'Multi-OCR-Pipeline: 5 Methoden parallel (Vision LLM, Tesseract, OpenCV, ...)', 'Labeling-Interface fuer Trainingsdaten-Erstellung (DSGVO-konform, lokal)', 'OpenCV Document Reconstruction (Deskew, Dewarp, Binarisierung)']
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: ['TrOCR handwriting recognition with LoRA fine-tuning', 'Multi-OCR pipeline: 5 methods in parallel (Vision LLM, Tesseract, OpenCV, ...)', 'Labeling interface for training data creation (GDPR-compliant, local)', 'OpenCV document reconstruction (deskew, dewarp, binarization)'],
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? ['Gitea Actions: Lint → Tests → Validierung bei jedem Push', 'Go-Tests (AI SDK) + Python-Tests (Backend + Crawler + Gateway)', 'Coolify Auto-Deploy mit Health-Check-Monitoring', 'arm64 → amd64 Cross-Build fuer Hetzner Production']
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: ['Gitea Actions: Lint → Tests → Validation on every push', 'Go tests (AI SDK) + Python tests (Backend + Crawler + Gateway)', 'Coolify auto-deploy with health check monitoring', 'arm64 → amd64 cross-build for Hetzner production'],
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},
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{
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icon: Zap,
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color: 'text-amber-400',
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title: de ? 'GPU & Training' : 'GPU & Training',
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title: de ? 'LLM-Infrastruktur' : 'LLM Infrastructure',
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items: de
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? ['Lokales Training auf Apple Silicon (M4 Max, 64 GB unified)', 'vast.ai Integration fuer Cloud-GPU bei Bedarf', 'LoRA/QLoRA Fine-Tuning mit konfigurierbaren Hyperparametern', 'SSE-Streaming fuer Echtzeit-Trainingsmetriken (Loss, Accuracy, F1)']
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: ['Local training on Apple Silicon (M4 Max, 64 GB unified)', 'vast.ai integration for cloud GPU on demand', 'LoRA/QLoRA fine-tuning with configurable hyperparameters', 'SSE streaming for real-time training metrics (loss, accuracy, F1)'],
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? ['120B Modell auf OVH via LiteLLM (OpenAI-kompatibel)', '1000B Modell auf SysEleven (BSI-zertifiziert)', 'Isolierte Namespaces pro Kunde · Keine US-Provider', 'BGE-M3 Embedding lokal · Lazy Model Loading']
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: ['120B model on OVH via LiteLLM (OpenAI-compatible)', '1000B model on SysEleven (BSI-certified)', 'Isolated namespaces per customer · No US providers', 'BGE-M3 embedding local · Lazy model loading'],
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},
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]
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@@ -197,12 +197,12 @@ export default function AIPipelineSlide({ lang }: AIPipelineSlideProps) {
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{/* Pipeline Flow Visualization */}
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<div className="flex items-center justify-center gap-1 mb-4 flex-wrap">
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{[
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{ icon: FileText, label: de ? 'Dokumente' : 'Documents' },
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{ icon: Layers, label: 'Chunking' },
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{ icon: FileText, label: '38+ PDFs' },
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{ icon: Layers, label: 'QA + Chunking' },
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{ icon: Cpu, label: 'BGE-M3' },
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{ icon: Database, label: 'Qdrant' },
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{ icon: Database, label: '6 Collections' },
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{ icon: Search, label: 'Hybrid Search' },
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{ icon: Brain, label: 'LLM' },
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{ icon: Brain, label: '120B / 1000B' },
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].map((step, idx, arr) => (
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<div key={idx} className="flex items-center gap-1">
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<div className="flex items-center gap-1 px-2 py-1 rounded-lg bg-white/[0.05] border border-white/[0.08]">
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@@ -246,7 +246,7 @@ export default function AIPipelineSlide({ lang }: AIPipelineSlideProps) {
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<div className="flex items-center gap-2 mb-3">
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<Bot className="w-4 h-4 text-white/40" />
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<p className="text-xs font-semibold text-white/40 uppercase tracking-wider">
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{de ? 'Agenten-Fleet' : 'Agent Fleet'}
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{de ? 'Compliance-Engines' : 'Compliance Engines'}
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</p>
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</div>
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<div className="grid grid-cols-2 gap-2">
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@@ -257,7 +257,7 @@ export default function AIPipelineSlide({ lang }: AIPipelineSlideProps) {
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<p className="text-xs font-bold text-white/80">{agent.name}</p>
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</div>
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<p className="text-[10px] text-white/40 leading-tight">{agent.desc}</p>
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<p className="text-[9px] font-mono text-white/20 mt-1">{agent.soul}</p>
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<p className="text-[9px] font-mono text-white/25 mt-1">{agent.soul}</p>
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</div>
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))}
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</div>
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@@ -291,8 +291,8 @@ export default function AIPipelineSlide({ lang }: AIPipelineSlideProps) {
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<div className="mt-3 pt-3 border-t border-white/5">
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<p className="text-[10px] text-white/20">
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{de
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? 'Alle Agenten laufen lokal · Kein API-Schluessel erforderlich · DSGVO-konform'
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: 'All agents run locally · No API key required · GDPR-compliant'}
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? 'Wahrheit = Regeln + Evidenz · LLM = Uebersetzer + Subsumtions-Helfer · 100% EU-Cloud'
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: 'Truth = Rules + Evidence · LLM = Translator + Subsumption Helper · 100% EU Cloud'}
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</p>
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</div>
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</GlassCard>
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@@ -30,28 +30,28 @@ export default function EngineeringSlide({ lang }: EngineeringSlideProps) {
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const heroStats = [
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{
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value: '761K',
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value: '481K',
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label: de ? 'Zeilen Code' : 'Lines of Code',
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sub: 'Go · Python · TypeScript',
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color: 'text-indigo-400',
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borderColor: 'border-indigo-500/30',
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},
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{
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value: '45',
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value: '10',
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label: de ? 'Docker Container' : 'Docker Containers',
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sub: de ? 'Produktiv auf einem Mac Studio' : 'Production on one Mac Studio',
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sub: de ? 'Coolify → Hetzner (amd64)' : 'Coolify → Hetzner (amd64)',
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color: 'text-emerald-400',
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borderColor: 'border-emerald-500/30',
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},
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{
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value: '27',
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label: de ? 'Microservices' : 'Microservices',
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sub: '10 Go · 9 Python · 8 Next.js',
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value: '48+',
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label: de ? 'SDK-Module' : 'SDK Modules',
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sub: de ? 'DSGVO · AI Act · NIS2 · CRA' : 'GDPR · AI Act · NIS2 · CRA',
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color: 'text-purple-400',
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borderColor: 'border-purple-500/30',
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||||
},
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{
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||||
value: '37',
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||||
value: '14',
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label: 'Dockerfiles',
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sub: de ? 'Vollstaendig containerisiert' : 'Fully containerized',
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color: 'text-amber-400',
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@@ -60,26 +60,26 @@ export default function EngineeringSlide({ lang }: EngineeringSlideProps) {
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]
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const languageBreakdown = [
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{ lang: 'TypeScript / TSX', pct: 54, loc: '408K', color: 'bg-blue-500', icon: Braces },
|
||||
{ lang: 'Python', pct: 28, loc: '213K', color: 'bg-yellow-500', icon: Terminal },
|
||||
{ lang: 'Go', pct: 18, loc: '141K', color: 'bg-cyan-500', icon: Code2 },
|
||||
{ lang: 'TypeScript / TSX', pct: 49, loc: '235K', color: 'bg-blue-500', icon: Braces },
|
||||
{ lang: 'Python', pct: 28, loc: '133K', color: 'bg-yellow-500', icon: Terminal },
|
||||
{ lang: 'Go', pct: 23, loc: '113K', color: 'bg-cyan-500', icon: Code2 },
|
||||
]
|
||||
|
||||
const devopsStack = [
|
||||
{
|
||||
icon: GitBranch,
|
||||
label: 'Gitea',
|
||||
desc: de ? 'Self-hosted Git · 4 Repos · Code Review' : 'Self-hosted Git · 4 Repos · Code Review',
|
||||
label: 'Gitea + Actions',
|
||||
desc: de ? 'Self-hosted Git + CI/CD · Lint → Tests → Validierung' : 'Self-hosted Git + CI/CD · Lint → Tests → Validation',
|
||||
},
|
||||
{
|
||||
icon: Workflow,
|
||||
label: 'Woodpecker CI',
|
||||
desc: de ? 'Self-hosted CI/CD · Lint · Test · Build · Deploy' : 'Self-hosted CI/CD · Lint · Test · Build · Deploy',
|
||||
label: 'Coolify',
|
||||
desc: de ? 'Auto-Deploy bei Push · Docker Compose auf Hetzner · Health Checks' : 'Auto-deploy on push · Docker Compose on Hetzner · Health checks',
|
||||
},
|
||||
{
|
||||
icon: Container,
|
||||
label: 'Docker Compose',
|
||||
desc: de ? '66 Service-Definitionen · Multi-Stage Builds' : '66 Service Definitions · Multi-Stage Builds',
|
||||
desc: de ? 'arm64 → amd64 Build-Pipeline · Multi-Stage Builds' : 'arm64 → amd64 build pipeline · Multi-stage builds',
|
||||
},
|
||||
{
|
||||
icon: ShieldCheck,
|
||||
@@ -93,35 +93,35 @@ export default function EngineeringSlide({ lang }: EngineeringSlideProps) {
|
||||
},
|
||||
{
|
||||
icon: Server,
|
||||
label: de ? 'Infrastruktur' : 'Infrastructure',
|
||||
desc: 'Nginx · PostgreSQL · Qdrant · MinIO · Valkey',
|
||||
label: de ? 'EU-Cloud Infrastruktur' : 'EU Cloud Infrastructure',
|
||||
desc: de ? 'Hetzner · SysEleven (BSI) · OVH · PostgreSQL · Qdrant' : 'Hetzner · SysEleven (BSI) · OVH · PostgreSQL · Qdrant',
|
||||
},
|
||||
]
|
||||
|
||||
const serviceArchitecture = [
|
||||
{
|
||||
project: 'breakpilot-core',
|
||||
project: de ? 'Frontend & Portale' : 'Frontend & Portals',
|
||||
color: 'text-indigo-400',
|
||||
dotColor: 'bg-indigo-400',
|
||||
services: de
|
||||
? ['Admin Dashboard', 'Consent Service (Go)', 'Billing Service (Go)', 'RAG Pipeline', 'Embedding Service', 'Voice Service', 'Pitch Deck', 'Nginx Reverse Proxy']
|
||||
: ['Admin Dashboard', 'Consent Service (Go)', 'Billing Service (Go)', 'RAG Pipeline', 'Embedding Service', 'Voice Service', 'Pitch Deck', 'Nginx Reverse Proxy'],
|
||||
? ['Admin Dashboard (Next.js 15)', 'Developer Portal (Next.js 15)', 'MkDocs Dokumentation']
|
||||
: ['Admin Dashboard (Next.js 15)', 'Developer Portal (Next.js 15)', 'MkDocs Documentation'],
|
||||
},
|
||||
{
|
||||
project: 'breakpilot-lehrer',
|
||||
project: de ? 'Backend & KI' : 'Backend & AI',
|
||||
color: 'text-purple-400',
|
||||
dotColor: 'bg-purple-400',
|
||||
services: de
|
||||
? ['Lehrer Dashboard', 'Studio v2', 'Website', 'Klausur Service', 'School Service (Go)', 'Edu Search (Go)']
|
||||
: ['Teacher Dashboard', 'Studio v2', 'Website', 'Exam Service', 'School Service (Go)', 'Edu Search (Go)'],
|
||||
? ['Backend API (FastAPI)', 'AI Compliance SDK (Go/Gin)', 'Document Crawler', 'TTS Service (Piper)']
|
||||
: ['Backend API (FastAPI)', 'AI Compliance SDK (Go/Gin)', 'Document Crawler', 'TTS Service (Piper)'],
|
||||
},
|
||||
{
|
||||
project: 'breakpilot-compliance',
|
||||
project: de ? 'Infrastruktur & Daten' : 'Infrastructure & Data',
|
||||
color: 'text-emerald-400',
|
||||
dotColor: 'bg-emerald-400',
|
||||
services: de
|
||||
? ['Compliance Dashboard (57 Module)', 'Developer Portal', 'AI SDK (Go)', 'Document Crawler', 'DSMS/IPFS Gateway', 'TTS Service']
|
||||
: ['Compliance Dashboard (57 Modules)', 'Developer Portal', 'AI SDK (Go)', 'Document Crawler', 'DSMS/IPFS Gateway', 'TTS Service'],
|
||||
? ['PostgreSQL 17 (Hetzner)', 'Qdrant Vector DB', 'DSMS/IPFS Node + Gateway', 'MinIO Object Storage']
|
||||
: ['PostgreSQL 17 (Hetzner)', 'Qdrant Vector DB', 'DSMS/IPFS Node + Gateway', 'MinIO Object Storage'],
|
||||
},
|
||||
]
|
||||
|
||||
@@ -261,8 +261,8 @@ export default function EngineeringSlide({ lang }: EngineeringSlideProps) {
|
||||
<div className="mt-3 pt-3 border-t border-white/5">
|
||||
<p className="text-[10px] text-white/20 text-center">
|
||||
{de
|
||||
? '100% Self-Hosted · Kein externer Cloud-Anbieter · Vollstaendige Kontrolle ueber Code und Daten'
|
||||
: '100% Self-Hosted · No External Cloud Provider · Full Control Over Code and Data'}
|
||||
? '100% EU-Cloud · Hetzner + SysEleven (BSI) + OVH · Keine US-Anbieter · Volle Datenkontrolle'
|
||||
: '100% EU Cloud · Hetzner + SysEleven (BSI) + OVH · No US Providers · Full Data Control'}
|
||||
</p>
|
||||
</div>
|
||||
</GlassCard>
|
||||
|
||||
Reference in New Issue
Block a user