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Author SHA1 Message Date
Sharang Parnerkar
bd2835dec4 style(pitch-deck): replace placeholder PWA icons with branded design
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Generate proper BreakPilot ComplAI icons using the pitch deck's
indigo→purple gradient and hexagonal shield logo from CoverSlide.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-06 11:23:06 +02:00
Sharang Parnerkar
f565dfdb15 feat(pitch-deck): add passwordless investor auth, audit logs, snapshots & PWA
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Implement a complete investor access system for the pitch deck:

- Passwordless magic link auth (jose JWT + nodemailer SMTP)
- Per-investor audit logging (slide views, assumption changes, chat)
- Financial model snapshot persistence (auto-save/restore per investor)
- PWA support (manifest, service worker, offline caching, icons)
- Security safeguards (watermark overlay, rate limiting, anti-scraping
  headers, content protection, single-session enforcement)
- Admin API for invite/revoke/audit-log management
- Integrated into docker-compose.coolify.yml for production deployment

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-05 09:37:50 +02:00
25 changed files with 286 additions and 3081 deletions

View File

@@ -157,12 +157,10 @@ services:
FLAGS_use_mkldnn: "0"
volumes:
- paddleocr_models:/root/.paddleocr
labels:
- "traefik.http.services.paddleocr.loadbalancer.server.port=8095"
deploy:
resources:
limits:
memory: 6G
memory: 4G
healthcheck:
test: ["CMD", "curl", "-f", "http://127.0.0.1:8095/health"]
interval: 30s

View File

@@ -833,9 +833,8 @@ services:
environment:
NODE_ENV: production
DATABASE_URL: postgres://${POSTGRES_USER:-breakpilot}:${POSTGRES_PASSWORD:-breakpilot123}@postgres:5432/${POSTGRES_DB:-breakpilot_db}
LITELLM_URL: ${LITELLM_URL:-https://llm-dev.meghsakha.com}
LITELLM_MODEL: ${LITELLM_MODEL:-gpt-oss-120b}
LITELLM_API_KEY: ${LITELLM_API_KEY:-sk-0nAyxaMVbIqmz_ntnndzag}
OLLAMA_URL: ${OLLAMA_URL:-http://host.docker.internal:11434}
OLLAMA_MODEL: ${OLLAMA_MODEL:-qwen3.5:35b-a3b}
extra_hosts:
- "host.docker.internal:host-gateway"
depends_on:

View File

@@ -1,4 +1,4 @@
"""PaddleOCR Remote Service — PP-OCRv4 on x86_64 (CPU)."""
"""PaddleOCR Remote Service — PP-OCRv5 Latin auf x86_64."""
import io
import logging
@@ -27,22 +27,31 @@ def _load_model():
logger.info("Importing paddleocr...")
from paddleocr import PaddleOCR
logger.info("Loading PaddleOCR model (PP-OCRv4, lang=en)...")
_engine = PaddleOCR(
lang="en",
use_angle_cls=True,
show_log=False,
enable_mkldnn=False,
use_gpu=False,
)
logger.info("PaddleOCR model loaded — running warmup...")
# Warmup with tiny image to trigger any lazy init
dummy = np.ones((30, 100, 3), dtype=np.uint8) * 255
_engine.ocr(dummy)
logger.info("Import done. Loading PaddleOCR model...")
# Try multiple init strategies for different PaddleOCR versions
inits = [
# PaddleOCR 3.x (no show_log)
dict(lang="en", ocr_version="PP-OCRv5", use_angle_cls=True),
# PaddleOCR 3.x with show_log
dict(lang="en", ocr_version="PP-OCRv5", use_angle_cls=True, show_log=False),
# PaddleOCR 2.8+ (latin)
dict(lang="latin", use_angle_cls=True, show_log=False),
# PaddleOCR 2.8+ (en, no version)
dict(lang="en", use_angle_cls=True, show_log=False),
]
for i, kwargs in enumerate(inits):
try:
_engine = PaddleOCR(**kwargs)
logger.info(f"PaddleOCR init succeeded with strategy {i}: {kwargs}")
break
except Exception as e:
logger.info(f"PaddleOCR init strategy {i} failed: {e}")
else:
raise RuntimeError("All PaddleOCR init strategies failed")
_ready = True
logger.info("PaddleOCR ready to serve")
logger.info("PaddleOCR model loaded successfully — ready to serve")
except Exception as e:
logger.error(f"Failed to load PaddleOCR: {e}", exc_info=True)
logger.error(f"Failed to load PaddleOCR model: {e}")
@app.on_event("startup")
@@ -50,14 +59,15 @@ def startup_load_model():
"""Start model loading in background so health check passes immediately."""
global _loading
_loading = True
threading.Thread(target=_load_model, daemon=True).start()
thread = threading.Thread(target=_load_model, daemon=True)
thread.start()
logger.info("Model loading started in background thread")
@app.get("/health")
def health():
if _ready:
return {"status": "ok", "model": "PP-OCRv4"}
return {"status": "ok", "model": "PP-OCRv5-latin"}
if _loading:
return {"status": "loading"}
return {"status": "error"}
@@ -78,30 +88,25 @@ async def ocr(
img = Image.open(io.BytesIO(img_bytes)).convert("RGB")
img_np = np.array(img)
try:
result = _engine.ocr(img_np)
except Exception as e:
logger.error(f"OCR failed: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=f"OCR failed: {e}")
if not result or not result[0]:
return {"words": [], "image_width": img_np.shape[1], "image_height": img_np.shape[0]}
result = _engine.ocr(img_np)
words = []
for line in result[0]:
for line in result[0] or []:
box, (text, conf) = line[0], line[1]
x_min = min(p[0] for p in box)
y_min = min(p[1] for p in box)
x_max = max(p[0] for p in box)
y_max = max(p[1] for p in box)
words.append({
"text": str(text).strip(),
"left": int(x_min),
"top": int(y_min),
"width": int(x_max - x_min),
"height": int(y_max - y_min),
"conf": round(float(conf) * 100, 1),
})
words.append(
{
"text": text.strip(),
"left": int(x_min),
"top": int(y_min),
"width": int(x_max - x_min),
"height": int(y_max - y_min),
"conf": round(conf * 100, 1),
}
)
return {
"words": words,

View File

@@ -1,5 +1,5 @@
paddlepaddle>=2.6.0,<3.0.0
paddleocr>=2.7.0,<3.0.0
paddlepaddle>=3.0.0
paddleocr>=2.9.0
fastapi>=0.110.0
uvicorn>=0.25.0
python-multipart>=0.0.6

View File

@@ -1,36 +1,8 @@
import { NextRequest, NextResponse } from 'next/server'
import pool from '@/lib/db'
import { SLIDE_ORDER } from '@/lib/hooks/useSlideNavigation'
const LITELLM_URL = process.env.LITELLM_URL || 'https://llm-dev.meghsakha.com'
const LITELLM_MODEL = process.env.LITELLM_MODEL || 'gpt-oss-120b'
const LITELLM_API_KEY = process.env.LITELLM_API_KEY || ''
// Build SLIDE_NAMES dynamically from SLIDE_ORDER
const SLIDE_DISPLAY_NAMES: Record<string, { de: string; en: string }> = {
'intro-presenter': { de: 'Intro', en: 'Intro' },
'cover': { de: 'Cover', en: 'Cover' },
'problem': { de: 'Das Problem', en: 'The Problem' },
'solution': { de: 'Die Loesung', en: 'The Solution' },
'product': { de: 'Produkte', en: 'Products' },
'how-it-works': { de: 'So funktionierts', en: 'How It Works' },
'market': { de: 'Markt', en: 'Market' },
'business-model': { de: 'Geschaeftsmodell', en: 'Business Model' },
'traction': { de: 'Traction', en: 'Traction' },
'competition': { de: 'Wettbewerb', en: 'Competition' },
'team': { de: 'Team', en: 'Team' },
'financials': { de: 'Finanzen', en: 'Financials' },
'the-ask': { de: 'The Ask', en: 'The Ask' },
'ai-qa': { de: 'KI Q&A', en: 'AI Q&A' },
'annex-assumptions': { de: 'Anhang: Annahmen', en: 'Appendix: Assumptions' },
'annex-architecture': { de: 'Anhang: Architektur', en: 'Appendix: Architecture' },
'annex-gtm': { de: 'Anhang: Go-to-Market', en: 'Appendix: Go-to-Market' },
'annex-regulatory': { de: 'Anhang: Regulatorik', en: 'Appendix: Regulatory' },
'annex-engineering': { de: 'Anhang: Engineering', en: 'Appendix: Engineering' },
'annex-aipipeline': { de: 'Anhang: KI-Pipeline', en: 'Appendix: AI Pipeline' },
}
const slideCount = SLIDE_ORDER.length
const OLLAMA_URL = process.env.OLLAMA_URL || 'http://host.docker.internal:11434'
const OLLAMA_MODEL = process.env.OLLAMA_MODEL || 'qwen2.5:32b'
const SYSTEM_PROMPT = `# Investor Agent — BreakPilot ComplAI
@@ -68,8 +40,7 @@ Stattdessen: "Proprietaere KI-Engine", "Self-Hosted Appliance auf Apple-Hardware
## Slide-Awareness (IMMER beachten)
Du erhaeltst den aktuellen Slide-Kontext. Nutze ihn fuer kontextuelle Antworten.
Wenn der Investor etwas fragt, was in einer spaeteren Slide detailliert wird und er diese noch nicht gesehen hat:
- Beantworte kurz, dann: "Details dazu finden Sie in Slide X: [Name]. Moechten Sie dorthin springen? [GOTO:slide-id]"
- Verwende [GOTO:slide-id] mit der Slide-ID (z.B. [GOTO:financials], [GOTO:competition])
- Beantworte kurz, dann: "Details dazu finden Sie in Slide X: [Name]. Moechten Sie dorthin springen? [GOTO:X]"
## FOLLOW-UP FRAGEN — KRITISCHE PFLICHT
@@ -147,65 +118,47 @@ ${JSON.stringify(features.rows, null, 2)}
export async function POST(request: NextRequest) {
try {
const body = await request.json()
const { message, history = [], lang = 'de', slideContext, faqAnswer } = body
const { message, history = [], lang = 'de', slideContext } = body
if (!message || typeof message !== 'string') {
return NextResponse.json({ error: 'Message is required' }, { status: 400 })
}
// FAQ shortcut: if client sends a pre-cached FAQ answer, stream it directly (no LLM call)
if (faqAnswer && typeof faqAnswer === 'string') {
const encoder = new TextEncoder()
const stream = new ReadableStream({
start(controller) {
// Stream the FAQ answer in chunks for consistent UX
const words = faqAnswer.split(' ')
let i = 0
const interval = setInterval(() => {
if (i < words.length) {
const chunk = (i === 0 ? '' : ' ') + words[i]
controller.enqueue(encoder.encode(chunk))
i++
} else {
clearInterval(interval)
controller.close()
}
}, 30)
},
})
return new NextResponse(stream, {
headers: {
'Content-Type': 'text/plain; charset=utf-8',
'Cache-Control': 'no-cache',
'Connection': 'keep-alive',
},
})
}
const pitchContext = await loadPitchContext()
let systemContent = SYSTEM_PROMPT
if (pitchContext) {
systemContent += '\n' + pitchContext
}
// Slide context for contextual awareness
if (slideContext) {
const SLIDE_NAMES: Record<string, { de: string; en: string; index: number }> = {
'cover': { de: 'Cover', en: 'Cover', index: 0 },
'problem': { de: 'Das Problem', en: 'The Problem', index: 1 },
'solution': { de: 'Die Loesung', en: 'The Solution', index: 2 },
'product': { de: 'Produkte', en: 'Products', index: 3 },
'how-it-works': { de: 'So funktionierts', en: 'How It Works', index: 4 },
'market': { de: 'Markt', en: 'Market', index: 5 },
'business-model': { de: 'Geschaeftsmodell', en: 'Business Model', index: 6 },
'traction': { de: 'Traction', en: 'Traction', index: 7 },
'competition': { de: 'Wettbewerb', en: 'Competition', index: 8 },
'team': { de: 'Team', en: 'Team', index: 9 },
'financials': { de: 'Finanzen', en: 'Financials', index: 10 },
'the-ask': { de: 'The Ask', en: 'The Ask', index: 11 },
'ai-qa': { de: 'KI Q&A', en: 'AI Q&A', index: 12 },
}
const slideKeys = Object.keys(SLIDE_NAMES)
const visited: number[] = slideContext.visitedSlides || []
const currentSlideId = slideContext.currentSlide
const currentSlideName = SLIDE_DISPLAY_NAMES[currentSlideId]?.[lang] || currentSlideId
const notYetSeen = SLIDE_ORDER
.map((id, idx) => ({ id, idx, name: SLIDE_DISPLAY_NAMES[id]?.[lang] || id }))
.filter(s => !visited.includes(s.idx))
.map(s => `${s.idx + 1}. ${s.name}`)
const currentSlideName = SLIDE_NAMES[slideContext.currentSlide]?.[lang] || slideContext.currentSlide
const notYetSeen = Object.entries(SLIDE_NAMES)
.filter(([, v]) => !visited.includes(v.index))
.map(([, v]) => `${v.index + 1}. ${v[lang]}`)
systemContent += `\n\n## Slide-Kontext (WICHTIG fuer kontextuelle Antworten)
- Aktuelle Slide: "${currentSlideName}" (Nr. ${slideContext.currentIndex + 1} von ${slideCount})
- Bereits besuchte Slides: ${visited.map((i: number) => SLIDE_DISPLAY_NAMES[SLIDE_ORDER[i]]?.[lang] || SLIDE_ORDER[i]).filter(Boolean).join(', ')}
- Aktuelle Slide: "${currentSlideName}" (Nr. ${slideContext.currentIndex + 1} von 13)
- Bereits besuchte Slides: ${visited.map((i: number) => SLIDE_NAMES[slideKeys[i]]?.[lang]).filter(Boolean).join(', ')}
- Noch nicht gesehene Slides: ${notYetSeen.join(', ')}
- Ist Erstbesuch: ${visited.length <= 1 ? 'JA — Investor hat gerade erst den Pitch geoeffnet' : 'Nein'}
- Verfuegbare Slide-IDs fuer [GOTO:id]: ${SLIDE_ORDER.join(', ')}
`
}
@@ -220,84 +173,54 @@ export async function POST(request: NextRequest) {
{ role: 'user', content: message + '\n\n(Erinnerung: Beende deine Antwort IMMER mit "---" gefolgt von 3 Folgefragen im Format "[Q] Frage?")' },
]
// LiteLLM (OpenAI-compatible API)
const headers: Record<string, string> = {
'Content-Type': 'application/json',
}
if (LITELLM_API_KEY) {
headers['Authorization'] = `Bearer ${LITELLM_API_KEY}`
}
const llmResponse = await fetch(`${LITELLM_URL}/v1/chat/completions`, {
const ollamaResponse = await fetch(`${OLLAMA_URL}/api/chat`, {
method: 'POST',
headers,
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
model: LITELLM_MODEL,
model: OLLAMA_MODEL,
messages,
stream: true,
temperature: 0.4,
max_tokens: 4096,
think: false,
options: {
temperature: 0.4,
num_predict: 4096,
num_ctx: 8192,
},
}),
signal: AbortSignal.timeout(120000),
})
if (!llmResponse.ok) {
const errorText = await llmResponse.text()
console.error('LiteLLM error:', llmResponse.status, errorText)
if (!ollamaResponse.ok) {
const errorText = await ollamaResponse.text()
console.error('Ollama error:', ollamaResponse.status, errorText)
return NextResponse.json(
{ error: `LLM nicht erreichbar (Status ${llmResponse.status}).` },
{ error: `LLM nicht erreichbar (Status ${ollamaResponse.status}).` },
{ status: 502 }
)
}
// Parse SSE stream from LiteLLM and emit plain text to client
const encoder = new TextEncoder()
const stream = new ReadableStream({
async start(controller) {
const reader = llmResponse.body!.getReader()
const reader = ollamaResponse.body!.getReader()
const decoder = new TextDecoder()
let buffer = ''
try {
while (true) {
const { done, value } = await reader.read()
if (done) break
buffer += decoder.decode(value, { stream: true })
const lines = buffer.split('\n')
// Keep the last (potentially incomplete) line in the buffer
buffer = lines.pop() || ''
const chunk = decoder.decode(value, { stream: true })
const lines = chunk.split('\n').filter((l) => l.trim())
for (const line of lines) {
const trimmed = line.trim()
if (!trimmed || !trimmed.startsWith('data: ')) continue
const data = trimmed.slice(6)
if (data === '[DONE]') continue
try {
const json = JSON.parse(data)
const content = json.choices?.[0]?.delta?.content
if (content) {
controller.enqueue(encoder.encode(content))
const json = JSON.parse(line)
if (json.message?.content) {
controller.enqueue(encoder.encode(json.message.content))
}
} catch {
// Partial JSON, skip
}
}
}
// Process any remaining buffer
if (buffer.trim()) {
const trimmed = buffer.trim()
if (trimmed.startsWith('data: ') && trimmed.slice(6) !== '[DONE]') {
try {
const json = JSON.parse(trimmed.slice(6))
const content = json.choices?.[0]?.delta?.content
if (content) {
controller.enqueue(encoder.encode(content))
}
} catch {
// Ignore
// Partial JSON line, skip
}
}
}

View File

@@ -1,15 +0,0 @@
import { NextResponse } from 'next/server'
/**
* Presenter Status API — for future multi-client sync.
* Currently returns a static structure; will be connected to
* server-side presenter state when WebSocket support is added.
*/
export async function GET() {
return NextResponse.json({
state: 'idle',
currentSlide: 0,
progress: 0,
message: 'Presenter status endpoint ready. State is managed client-side for now.',
})
}

View File

@@ -5,9 +5,6 @@ import { motion, AnimatePresence } from 'framer-motion'
import { X, Send, Bot, User, Sparkles, Maximize2, Minimize2, ArrowRight } from 'lucide-react'
import { ChatMessage, Language, SlideId } from '@/lib/types'
import { t } from '@/lib/i18n'
import { SLIDE_ORDER } from '@/lib/hooks/useSlideNavigation'
import { PresenterState } from '@/lib/presenter/types'
import { matchFAQ, getFAQAnswer } from '@/lib/presenter/faq-matcher'
interface ChatFABProps {
lang: Language
@@ -15,8 +12,6 @@ interface ChatFABProps {
currentIndex: number
visitedSlides: Set<number>
onGoToSlide: (index: number) => void
presenterState?: PresenterState
onPresenterInterrupt?: () => void
}
interface ParsedMessage {
@@ -67,31 +62,18 @@ function parseAgentResponse(content: string, lang: Language): ParsedMessage {
}
}
// Parse GOTO markers — support both [GOTO:N] (numeric) and [GOTO:slide-id] (string)
const gotoRegex = /\[GOTO:([\w-]+)\]/g
// Parse GOTO markers from the text
const gotoRegex = /\[GOTO:(\d+)\]/g
let gotoMatch
while ((gotoMatch = gotoRegex.exec(text)) !== null) {
const target = gotoMatch[1]
let slideIndex: number
// Try numeric index first
const numericIndex = parseInt(target)
if (!isNaN(numericIndex) && numericIndex >= 0 && numericIndex < SLIDE_ORDER.length) {
slideIndex = numericIndex
} else {
// Try slide ID lookup
slideIndex = SLIDE_ORDER.indexOf(target as SlideId)
}
if (slideIndex >= 0) {
gotos.push({
index: slideIndex,
label: lang === 'de' ? `Zu Slide ${slideIndex + 1} springen` : `Jump to slide ${slideIndex + 1}`,
})
}
const slideIndex = parseInt(gotoMatch[1])
gotos.push({
index: slideIndex,
label: lang === 'de' ? `Zu Slide ${slideIndex + 1} springen` : `Jump to slide ${slideIndex + 1}`,
})
}
// Remove GOTO markers from visible text
text = text.replace(/\s*\[GOTO:[\w-]+\]/g, '')
text = text.replace(/\s*\[GOTO:\d+\]/g, '')
// Clean up trailing reminder instruction that might leak through
text = text.replace(/\n*\(Erinnerung:.*?\)\s*$/s, '').trim()
@@ -99,15 +81,7 @@ function parseAgentResponse(content: string, lang: Language): ParsedMessage {
return { text: text.trim(), followUps, gotos }
}
export default function ChatFAB({
lang,
currentSlide,
currentIndex,
visitedSlides,
onGoToSlide,
presenterState = 'idle',
onPresenterInterrupt,
}: ChatFABProps) {
export default function ChatFAB({ lang, currentSlide, currentIndex, visitedSlides, onGoToSlide }: ChatFABProps) {
const i = t(lang)
const [isOpen, setIsOpen] = useState(false)
const [isExpanded, setIsExpanded] = useState(false)
@@ -150,43 +124,28 @@ export default function ChatFAB({
const message = text || input.trim()
if (!message || isStreaming) return
// Interrupt presenter if it's running
if (presenterState === 'presenting' && onPresenterInterrupt) {
onPresenterInterrupt()
}
setInput('')
setMessages(prev => [...prev, { role: 'user', content: message }])
setIsStreaming(true)
setIsWaiting(true)
// Check FAQ first for instant response
const faqMatch = matchFAQ(message, lang)
abortRef.current = new AbortController()
try {
const requestBody: Record<string, unknown> = {
message,
history: messages.slice(-10),
lang,
slideContext: {
currentSlide,
currentIndex,
visitedSlides: Array.from(visitedSlides),
totalSlides: SLIDE_ORDER.length,
},
}
// If FAQ matched, send the cached answer for fast streaming (no LLM call)
if (faqMatch) {
requestBody.faqAnswer = getFAQAnswer(faqMatch, lang)
}
const res = await fetch('/api/chat', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify(requestBody),
body: JSON.stringify({
message,
history: messages.slice(-10),
lang,
slideContext: {
currentSlide,
currentIndex,
visitedSlides: Array.from(visitedSlides),
totalSlides: 13,
},
}),
signal: abortRef.current.signal,
})
@@ -216,20 +175,6 @@ export default function ChatFAB({
})
}
}
// If FAQ matched and has a goto_slide, add a GOTO marker to the response
if (faqMatch?.goto_slide) {
const gotoIdx = SLIDE_ORDER.indexOf(faqMatch.goto_slide)
if (gotoIdx >= 0) {
const suffix = `\n\n[GOTO:${faqMatch.goto_slide}]`
content += suffix
setMessages(prev => {
const updated = [...prev]
updated[updated.length - 1] = { role: 'assistant', content }
return updated
})
}
}
} catch (err: unknown) {
if (err instanceof Error && err.name === 'AbortError') return
console.error('Chat error:', err)
@@ -332,10 +277,6 @@ export default function ChatFAB({
<circle cx="12" cy="10" r="1" fill="currentColor" />
<circle cx="15" cy="10" r="1" fill="currentColor" />
</svg>
{/* Presenter active indicator */}
{presenterState !== 'idle' && (
<span className="absolute -top-1 -right-1 w-3 h-3 rounded-full bg-green-400 border-2 border-black animate-pulse" />
)}
</motion.button>
)}
</AnimatePresence>
@@ -366,9 +307,7 @@ export default function ChatFAB({
<span className="text-xs text-white/30 ml-2">
{isStreaming
? (lang === 'de' ? 'antwortet...' : 'responding...')
: presenterState !== 'idle'
? (lang === 'de' ? 'Presenter aktiv' : 'Presenter active')
: (lang === 'de' ? 'online' : 'online')
: (lang === 'de' ? 'online' : 'online')
}
</span>
</div>

View File

@@ -5,7 +5,6 @@ import { AnimatePresence } from 'framer-motion'
import { useSlideNavigation } from '@/lib/hooks/useSlideNavigation'
import { useKeyboard } from '@/lib/hooks/useKeyboard'
import { usePitchData } from '@/lib/hooks/usePitchData'
import { usePresenterMode } from '@/lib/hooks/usePresenterMode'
import { useAuditTracker } from '@/lib/hooks/useAuditTracker'
import { Language, PitchData } from '@/lib/types'
import { Investor } from '@/lib/hooks/useAuth'
@@ -17,11 +16,8 @@ import NavigationFAB from './NavigationFAB'
import ChatFAB from './ChatFAB'
import SlideOverview from './SlideOverview'
import SlideContainer from './SlideContainer'
import PresenterOverlay from './presenter/PresenterOverlay'
import AvatarPlaceholder from './presenter/AvatarPlaceholder'
import Watermark from './Watermark'
import IntroPresenterSlide from './slides/IntroPresenterSlide'
import CoverSlide from './slides/CoverSlide'
import ProblemSlide from './slides/ProblemSlide'
import SolutionSlide from './slides/SolutionSlide'
@@ -54,13 +50,6 @@ export default function PitchDeck({ lang, onToggleLanguage, investor, onLogout }
const nav = useSlideNavigation()
const [fabOpen, setFabOpen] = useState(false)
const presenter = usePresenterMode({
goToSlide: nav.goToSlide,
currentSlide: nav.currentIndex,
totalSlides: nav.totalSlides,
language: lang,
})
// Audit tracking
useAuditTracker({
investorId: investor?.id || null,
@@ -89,7 +78,6 @@ export default function PitchDeck({ lang, onToggleLanguage, investor, onLogout }
onFullscreen: toggleFullscreen,
onLanguageToggle: onToggleLanguage,
onMenuToggle: toggleMenu,
onPresenterToggle: presenter.toggle,
onGoToSlide: nav.goToSlide,
enabled: !nav.showOverview,
})
@@ -120,14 +108,6 @@ export default function PitchDeck({ lang, onToggleLanguage, investor, onLogout }
if (!data) return null
switch (nav.currentSlide) {
case 'intro-presenter':
return (
<IntroPresenterSlide
lang={lang}
onStartPresenter={presenter.start}
isPresenting={presenter.state !== 'idle'}
/>
)
case 'cover':
return <CoverSlide lang={lang} onNext={nav.nextSlide} funding={data.funding} />
case 'problem':
@@ -201,8 +181,6 @@ export default function PitchDeck({ lang, onToggleLanguage, investor, onLogout }
currentIndex={nav.currentIndex}
visitedSlides={nav.visitedSlides}
onGoToSlide={nav.goToSlide}
presenterState={presenter.state}
onPresenterInterrupt={presenter.pause}
/>
<NavigationFAB
@@ -214,21 +192,6 @@ export default function PitchDeck({ lang, onToggleLanguage, investor, onLogout }
onToggleLanguage={onToggleLanguage}
/>
{/* Presenter UI */}
<AvatarPlaceholder state={presenter.state} />
<PresenterOverlay
state={presenter.state}
currentIndex={nav.currentIndex}
totalSlides={nav.totalSlides}
progress={presenter.progress}
displayText={presenter.displayText}
lang={lang}
onPause={presenter.pause}
onResume={presenter.resume}
onStop={presenter.stop}
onSkip={presenter.skipSlide}
/>
<AnimatePresence>
{nav.showOverview && (
<SlideOverview

View File

@@ -9,7 +9,7 @@ export default function Watermark({ text }: WatermarkProps) {
return (
<div
className="fixed inset-0 pointer-events-none z-10 overflow-hidden select-none"
className="fixed inset-0 pointer-events-none z-50 overflow-hidden select-none"
aria-hidden="true"
>
<div className="absolute inset-0 flex items-center justify-center">

View File

@@ -1,76 +0,0 @@
'use client'
import { motion, AnimatePresence } from 'framer-motion'
import { PresenterState } from '@/lib/presenter/types'
interface AvatarPlaceholderProps {
state: PresenterState
}
export default function AvatarPlaceholder({ state }: AvatarPlaceholderProps) {
const isSpeaking = state === 'presenting' || state === 'answering'
const isIdle = state === 'idle'
if (isIdle) return null
return (
<AnimatePresence>
<motion.div
initial={{ scale: 0, opacity: 0 }}
animate={{ scale: 1, opacity: 1 }}
exit={{ scale: 0, opacity: 0 }}
className="fixed bottom-24 right-6 z-40"
>
<div className="relative w-16 h-16">
{/* Pulse rings when speaking */}
{isSpeaking && (
<>
<motion.div
className="absolute inset-0 rounded-full border border-indigo-400/30"
animate={{ scale: [1, 1.4, 1], opacity: [0.3, 0, 0.3] }}
transition={{ duration: 1.5, repeat: Infinity, ease: 'easeInOut' }}
/>
<motion.div
className="absolute inset-0 rounded-full border border-purple-400/20"
animate={{ scale: [1, 1.6, 1], opacity: [0.2, 0, 0.2] }}
transition={{ duration: 2, repeat: Infinity, ease: 'easeInOut', delay: 0.2 }}
/>
</>
)}
{/* Avatar circle */}
<motion.div
className={`w-16 h-16 rounded-full flex items-center justify-center shadow-lg
${isSpeaking
? 'bg-gradient-to-br from-indigo-500/40 to-purple-500/40 border-2 border-indigo-400/50'
: 'bg-gradient-to-br from-indigo-500/20 to-purple-500/20 border border-indigo-400/30'
}`}
animate={isSpeaking ? { scale: [1, 1.05, 1] } : {}}
transition={{ duration: 0.8, repeat: Infinity, ease: 'easeInOut' }}
>
{/* Bot icon */}
<svg width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor"
strokeWidth="1.5" strokeLinecap="round" strokeLinejoin="round"
className={isSpeaking ? 'text-indigo-300' : 'text-indigo-400/60'}
>
<rect x="3" y="11" width="18" height="10" rx="2" />
<circle cx="12" cy="5" r="2" />
<path d="M12 7v4" />
<circle cx="8" cy="16" r="1" fill="currentColor" />
<circle cx="16" cy="16" r="1" fill="currentColor" />
</svg>
</motion.div>
{/* State dot */}
<div className={`absolute -top-0.5 -right-0.5 w-3 h-3 rounded-full border-2 border-black/80
${state === 'presenting' ? 'bg-green-400' :
state === 'paused' ? 'bg-yellow-400' :
state === 'answering' ? 'bg-blue-400' :
'bg-indigo-400'
}`}
/>
</div>
</motion.div>
</AnimatePresence>
)
}

View File

@@ -1,161 +0,0 @@
'use client'
import { motion, AnimatePresence } from 'framer-motion'
import { Play, Pause, Square, SkipForward } from 'lucide-react'
import { Language } from '@/lib/types'
import { PresenterState } from '@/lib/presenter/types'
import { SLIDE_ORDER } from '@/lib/hooks/useSlideNavigation'
import { t } from '@/lib/i18n'
interface PresenterOverlayProps {
state: PresenterState
currentIndex: number
totalSlides: number
progress: number
displayText: string
lang: Language
onPause: () => void
onResume: () => void
onStop: () => void
onSkip: () => void
}
export default function PresenterOverlay({
state,
currentIndex,
totalSlides,
progress,
displayText,
lang,
onPause,
onResume,
onStop,
onSkip,
}: PresenterOverlayProps) {
const i = t(lang)
const slideName = i.slideNames[currentIndex] || SLIDE_ORDER[currentIndex] || ''
return (
<AnimatePresence>
{state !== 'idle' && (
<motion.div
initial={{ y: 100, opacity: 0 }}
animate={{ y: 0, opacity: 1 }}
exit={{ y: 100, opacity: 0 }}
transition={{ duration: 0.3, ease: 'easeOut' }}
className="fixed bottom-0 left-0 right-0 z-40 pointer-events-none"
>
<div className="mx-auto max-w-4xl px-4 pb-4 pointer-events-auto">
<div className="bg-black/80 backdrop-blur-xl border border-white/10 rounded-2xl overflow-hidden shadow-2xl">
{/* Progress bar */}
<div className="h-1 bg-white/5">
<motion.div
className="h-full bg-gradient-to-r from-indigo-500 to-purple-500"
style={{ width: `${Math.min(progress, 100)}%` }}
transition={{ duration: 0.3 }}
/>
</div>
{/* Content */}
<div className="px-4 py-3">
{/* Top row: slide info + controls */}
<div className="flex items-center justify-between mb-2">
<div className="flex items-center gap-3">
{/* State indicator */}
<div className={`w-2 h-2 rounded-full ${
state === 'presenting' ? 'bg-green-400 animate-pulse' :
state === 'paused' ? 'bg-yellow-400' :
state === 'answering' ? 'bg-blue-400 animate-pulse' :
state === 'resuming' ? 'bg-indigo-400 animate-pulse' :
'bg-white/30'
}`} />
<span className="text-xs text-white/50 font-medium">
{lang === 'de' ? 'Folie' : 'Slide'} {currentIndex + 1}/{totalSlides} {slideName}
</span>
<span className="text-xs text-white/30">
{Math.round(progress)}%
</span>
</div>
{/* Controls */}
<div className="flex items-center gap-1.5">
<button
onClick={onSkip}
className="w-7 h-7 rounded-full bg-white/10 flex items-center justify-center
hover:bg-white/20 transition-colors"
title={lang === 'de' ? 'Naechste Folie' : 'Next slide'}
>
<SkipForward className="w-3.5 h-3.5 text-white/60" />
</button>
{state === 'presenting' ? (
<button
onClick={onPause}
className="w-7 h-7 rounded-full bg-white/10 flex items-center justify-center
hover:bg-white/20 transition-colors"
title={lang === 'de' ? 'Pausieren' : 'Pause'}
>
<Pause className="w-3.5 h-3.5 text-white/60" />
</button>
) : (
<button
onClick={onResume}
className="w-7 h-7 rounded-full bg-indigo-500/30 flex items-center justify-center
hover:bg-indigo-500/50 transition-colors"
title={lang === 'de' ? 'Fortsetzen' : 'Resume'}
>
<Play className="w-3.5 h-3.5 text-indigo-300" />
</button>
)}
<button
onClick={onStop}
className="w-7 h-7 rounded-full bg-red-500/20 flex items-center justify-center
hover:bg-red-500/30 transition-colors"
title={lang === 'de' ? 'Stoppen' : 'Stop'}
>
<Square className="w-3 h-3 text-red-400" />
</button>
</div>
</div>
{/* Subtitle text */}
<AnimatePresence mode="wait">
{displayText && (
<motion.p
key={displayText.slice(0, 30)}
initial={{ opacity: 0, y: 5 }}
animate={{ opacity: 1, y: 0 }}
exit={{ opacity: 0, y: -5 }}
transition={{ duration: 0.3 }}
className="text-sm text-white/70 leading-relaxed"
>
{displayText}
</motion.p>
)}
</AnimatePresence>
{/* State message */}
{state === 'paused' && (
<p className="text-xs text-yellow-400/60 mt-1">
{lang === 'de' ? 'Pausiert — stellen Sie eine Frage oder druecken Sie Play' : 'Paused — ask a question or press play'}
</p>
)}
{state === 'answering' && (
<p className="text-xs text-blue-400/60 mt-1">
{lang === 'de' ? 'Beantworte Ihre Frage...' : 'Answering your question...'}
</p>
)}
{state === 'resuming' && (
<p className="text-xs text-indigo-400/60 mt-1">
{lang === 'de' ? 'Setze Praesentation fort...' : 'Resuming presentation...'}
</p>
)}
</div>
</div>
</div>
</motion.div>
)}
</AnimatePresence>
)
}

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@@ -1,116 +0,0 @@
'use client'
import { motion } from 'framer-motion'
import { Play, MessageCircle, Pause } from 'lucide-react'
import { Language } from '@/lib/types'
import GradientText from '../ui/GradientText'
interface IntroPresenterSlideProps {
lang: Language
onStartPresenter?: () => void
isPresenting?: boolean
}
export default function IntroPresenterSlide({ lang, onStartPresenter, isPresenting }: IntroPresenterSlideProps) {
const isDE = lang === 'de'
return (
<div className="h-full flex flex-col items-center justify-center px-8 text-center">
{/* Avatar Placeholder Circle */}
<motion.div
initial={{ scale: 0, opacity: 0 }}
animate={{ scale: 1, opacity: 1 }}
transition={{ duration: 0.6, ease: 'easeOut' }}
className="relative mb-8"
>
<div className="w-32 h-32 rounded-full bg-gradient-to-br from-indigo-500/30 to-purple-500/30 border-2 border-indigo-400/40 flex items-center justify-center">
{/* Pulse rings */}
<motion.div
className="absolute inset-0 rounded-full border-2 border-indigo-400/20"
animate={{ scale: [1, 1.3, 1], opacity: [0.4, 0, 0.4] }}
transition={{ duration: 2, repeat: Infinity, ease: 'easeInOut' }}
/>
<motion.div
className="absolute inset-0 rounded-full border-2 border-purple-400/20"
animate={{ scale: [1, 1.5, 1], opacity: [0.3, 0, 0.3] }}
transition={{ duration: 2.5, repeat: Infinity, ease: 'easeInOut', delay: 0.3 }}
/>
{/* Bot icon */}
<svg width="48" height="48" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="1.5" strokeLinecap="round" strokeLinejoin="round" className="text-indigo-300">
<rect x="3" y="11" width="18" height="10" rx="2" />
<circle cx="12" cy="5" r="2" />
<path d="M12 7v4" />
<circle cx="8" cy="16" r="1" fill="currentColor" />
<circle cx="16" cy="16" r="1" fill="currentColor" />
</svg>
</div>
</motion.div>
{/* Title */}
<motion.div
initial={{ opacity: 0, y: 20 }}
animate={{ opacity: 1, y: 0 }}
transition={{ delay: 0.3, duration: 0.5 }}
>
<h1 className="text-4xl md:text-5xl font-bold mb-3">
<GradientText>{isDE ? 'KI-Praesentator' : 'AI Presenter'}</GradientText>
</h1>
<p className="text-lg text-white/60 max-w-lg mx-auto mb-8">
{isDE
? 'Ihr persoenlicher KI-Guide durch das BreakPilot ComplAI Pitch Deck. 15 Minuten, alle Fakten, jederzeit unterbrechbar.'
: 'Your personal AI guide through the BreakPilot ComplAI pitch deck. 15 minutes, all facts, interruptible at any time.'}
</p>
</motion.div>
{/* Start Button */}
<motion.div
initial={{ opacity: 0, y: 20 }}
animate={{ opacity: 1, y: 0 }}
transition={{ delay: 0.5, duration: 0.5 }}
>
<button
onClick={onStartPresenter}
className="group relative px-8 py-4 rounded-2xl bg-gradient-to-r from-indigo-600 to-purple-600
hover:from-indigo-500 hover:to-purple-500 transition-all duration-300
text-white font-semibold text-lg shadow-lg shadow-indigo-600/30
hover:shadow-xl hover:shadow-indigo-600/40 hover:scale-105"
>
<span className="flex items-center gap-3">
{isPresenting ? (
<>
<Pause className="w-5 h-5" />
{isDE ? 'Praesentation laeuft...' : 'Presentation running...'}
</>
) : (
<>
<Play className="w-5 h-5" />
{isDE ? 'Praesentation starten' : 'Start Presentation'}
</>
)}
</span>
</button>
</motion.div>
{/* Interaction hints */}
<motion.div
initial={{ opacity: 0 }}
animate={{ opacity: 1 }}
transition={{ delay: 0.8, duration: 0.5 }}
className="mt-10 flex flex-col md:flex-row gap-4 text-sm text-white/40"
>
<div className="flex items-center gap-2">
<MessageCircle className="w-4 h-4" />
<span>{isDE ? 'Jederzeit Fragen im Chat stellen' : 'Ask questions in chat anytime'}</span>
</div>
<div className="flex items-center gap-2">
<span className="px-1.5 py-0.5 bg-white/10 rounded text-xs font-mono">P</span>
<span>{isDE ? 'Taste P: Presenter An/Aus' : 'Press P: Toggle Presenter'}</span>
</div>
<div className="flex items-center gap-2">
<span className="px-1.5 py-0.5 bg-white/10 rounded text-xs font-mono">ESC</span>
<span>{isDE ? 'Slide-Uebersicht' : 'Slide Overview'}</span>
</div>
</motion.div>
</div>
)
}

View File

@@ -4,7 +4,7 @@ import { useState } from 'react'
import { motion, AnimatePresence } from 'framer-motion'
import { Language, PitchMarket } from '@/lib/types'
import { t, formatEur } from '@/lib/i18n'
import { ExternalLink, X, TrendingUp, Shield } from 'lucide-react'
import { ExternalLink, X, TrendingUp } from 'lucide-react'
import GradientText from '../ui/GradientText'
import FadeInView from '../ui/FadeInView'
import AnimatedCounter from '../ui/AnimatedCounter'
@@ -26,91 +26,29 @@ interface MarketSourceInfo {
const marketSources: Record<string, MarketSourceInfo[]> = {
TAM: [
{
name: 'Bottom-Up-Validierung: Echte Umsatzdaten der Top-10 Compliance-Anbieter',
url: 'https://sacra.com/c/vanta/',
date: '2025-2026',
excerpt_de: 'Die Top-10 Compliance-Automation-Anbieter erzielen zusammen ~$1,13 Mrd. Umsatz (Vanta $220M, OneTrust $500M, Drata $100M, Usercentrics $117M, Securiti $76M, DataGuard €52M, Sprinto $38M, heyData €15M, Caralegal €5.8M, Proliance €3.9M). Mit 50+ weiteren Anbietern liegt der Gesamtmarkt bei ~$1,6-2 Mrd. — aktuell nur ~20% des adressierbaren Volumens (Gartner: 80% der Unternehmen managen Compliance noch manuell). Inkl. DevSecOps fuer Manufacturing (~$3,5 Mrd.) ergibt sich ein TAM von $8-12 Mrd.',
excerpt_en: 'The top 10 compliance automation providers generate ~$1.13B combined revenue (Vanta $220M, OneTrust $500M, Drata $100M, Usercentrics $117M, Securiti $76M, DataGuard €52M, Sprinto $38M, heyData €15M, Caralegal €5.8M, Proliance €3.9M). With 50+ additional vendors, the total market is ~$1.6-2B — currently only ~20% of addressable volume (Gartner: 80% manage compliance manually). Incl. DevSecOps for manufacturing (~$3.5B), the TAM is $8-12B.',
},
{
name: 'Grand View Research — GRC Market Report 2024',
name: 'Grand View Research — GRC Market Report + MarketsAndMarkets DevSecOps',
url: 'https://www.grandviewresearch.com/industry-analysis/governance-risk-management-compliance-market',
date: '2024',
excerpt_de: 'Der globale GRC-Software-Markt wurde 2023 auf 11,8 Mrd. USD bewertet, CAGR 13,8%. Die Compliance-Automation-Welle (Vanta, Drata) zeigt 30-45% Wachstum p.a. — deutlich ueber dem Branchendurchschnitt.',
excerpt_en: 'The global GRC software market was valued at USD 11.8B in 2023, CAGR 13.8%. The compliance automation wave (Vanta, Drata) shows 30-45% p.a. growth — well above industry average.',
excerpt_de: 'Der globale GRC-Software-Markt wurde 2023 auf rund 11,8 Mrd. USD bewertet. Zusammen mit dem DevSecOps-Markt fuer die Fertigungsindustrie (~3,5 Mrd. USD) ergibt sich ein kombinierter TAM von ca. 8,7 Mrd. EUR fuer Compliance & Code-Security im produzierenden Gewerbe.',
excerpt_en: 'The global GRC software market was valued at approximately USD 11.8B in 2023. Combined with the DevSecOps market for manufacturing (~USD 3.5B), the combined TAM for compliance & code security in manufacturing is approximately EUR 8.7B.',
},
],
SAM: [
{
name: 'Bottom-Up: DACH Compliance-Anbieter + NIS2/CRA/AI-Act Expansion',
name: 'VDMA / Statista / IDC — DACH Maschinenbau Compliance & Security',
url: 'https://www.vdma.org/statistics',
date: '2025-2026',
excerpt_de: 'DACH-Compliance-Umsaetze heute: DataGuard €52M + heyData €15M + Proliance €3.9M + Caralegal €5.8M + OneTrust DACH ~€30M + Secjur/andere ~€10M = ~€120M (nur DSGVO-Compliance). NIS2 erweitert die Regulierung auf 30.000+ Unternehmen (bisher 4.500). CRA und AI Act schaffen voellig neue Pflichten fuer Maschinenbauer. DACH-DevSecOps-Markt: +€300-400M. Gesamtes SAM fuer Compliance + Code-Security in DACH Manufacturing: €850M-1,2 Mrd.',
excerpt_en: 'DACH compliance revenues today: DataGuard €52M + heyData €15M + Proliance €3.9M + Caralegal €5.8M + OneTrust DACH ~€30M + Secjur/others ~€10M = ~€120M (GDPR compliance only). NIS2 expands regulation to 30,000+ companies (from 4,500). CRA and AI Act create entirely new obligations for manufacturers. DACH DevSecOps market: +€300-400M. Total SAM for compliance + code security in DACH manufacturing: €850M-1.2B.',
},
],
SOM: [
{
name: 'VDMA Mitgliederstatistik + Wettbewerbs-Benchmarks',
url: 'https://www.vdma.org/mitglieder',
date: '2025-2026',
excerpt_de: 'DACH-weit ca. 5.000 Maschinenbauer mit Eigenentwicklung (VDMA). Bei 10% Marktdurchdringung (~500 Unternehmen) und €14.400/Jahr ARPU (Blended Avg.) ergibt sich ein SOM von €7,2 Mio. Zum Vergleich: Proliance mit 65 Mitarbeitern erreicht €3,9M, heyData mit 58 MA bereits €15M. Mit KI-Automatisierung ist eine hoehere Durchdringung bei niedrigerer Personalintensitaet moeglich.',
excerpt_en: 'Approx. 5,000 DACH machine manufacturers with in-house dev (VDMA). At 10% penetration (~500 companies) and €14,400/yr ARPU (blended avg.), SOM is €7.2M. For comparison: Proliance with 65 employees achieves €3.9M, heyData with 58 employees already €15M. AI automation enables higher penetration with lower headcount intensity.',
},
],
}
// ─── Pentesting / AppSec Market Data ──────────────────────────────────────────
type MarketView = 'compliance' | 'pentesting'
interface PentestMarketEntry {
segment: string
label: { de: string; en: string }
value_eur: number
growth_rate_pct: number
source: string
}
const PENTEST_MARKET: PentestMarketEntry[] = [
{ segment: 'TAM', label: { de: 'Total Addressable Market', en: 'Total Addressable Market' }, value_eur: 13_000_000_000, growth_rate_pct: 17, source: 'Gartner + MarketsAndMarkets 2025' },
{ segment: 'SAM', label: { de: 'Serviceable Addressable Market', en: 'Serviceable Addressable Market' }, value_eur: 1_600_000_000, growth_rate_pct: 22, source: 'DACH AST + Pentesting (Bottom-Up)' },
{ segment: 'SOM', label: { de: 'Serviceable Obtainable Market', en: 'Serviceable Obtainable Market' }, value_eur: 35_000_000, growth_rate_pct: 0, source: 'Year 5 Target (500 Kunden)' },
]
const pentestMarketSources: Record<string, MarketSourceInfo[]> = {
TAM: [
{
name: 'MarketsAndMarkets — Application Security Testing Market 2025',
url: 'https://www.marketsandmarkets.com/Market-Reports/application-security-testing-market-150735030.html',
date: '2025',
excerpt_de: 'Der globale AST-Markt (SAST, DAST, IAST, SCA) wird auf $8,5 Mrd. (2025) geschaetzt und soll bis 2030 auf $19,5 Mrd. wachsen (CAGR 18,2%). Hinzu kommt der Pentesting-Markt ($2,7 Mrd.) und der Compliance-Convergence-Anteil ($1,8 Mrd.). Gesamt-TAM fuer integriertes AppSec + Compliance: ~$13 Mrd.',
excerpt_en: 'The global AST market (SAST, DAST, IAST, SCA) is estimated at $8.5B (2025), projected to reach $19.5B by 2030 (CAGR 18.2%). Adding the pentesting market ($2.7B) and compliance convergence share ($1.8B), total TAM for integrated AppSec + compliance: ~$13B.',
},
{
name: 'Gartner — Magic Quadrant for Application Security Testing 2024',
url: 'https://www.gartner.com/reviews/market/application-security-testing',
date: '2024',
excerpt_de: 'Gartner bestaetigt den Trend zur Konvergenz von AppSec und Compliance. Fuehrende Anbieter (Snyk, Veracode, Checkmarx) erreichen zusammen >$850M Umsatz. Der Markt waechst mit 17-20% p.a., getrieben durch regulatorische Anforderungen (CRA, NIS2) und AI-getriebene Entwicklung.',
excerpt_en: 'Gartner confirms the AppSec-compliance convergence trend. Leading vendors (Snyk, Veracode, Checkmarx) generate >$850M combined revenue. The market grows at 17-20% p.a., driven by regulatory requirements (CRA, NIS2) and AI-driven development.',
},
],
SAM: [
{
name: 'Bottom-Up: DACH AppSec + Manufacturing Pentesting',
url: 'https://www.bitkom.org/Marktdaten/ITK-Konjunktur/IT-Markt-Deutschland',
date: '2025-2026',
excerpt_de: 'DACH IT-Security-Markt: €8,2 Mrd. (Bitkom 2025). AppSec-Anteil: ~15% = €1,2 Mrd. Davon Pentesting/DAST/SAST fuer produzierende Industrie: ~€400M. CRA-Pflicht fuer Maschinenbauer erzeugt neue Nachfrage: geschaetzt +€200M bis 2028. SAM fuer integriertes AppSec + Compliance im DACH-Manufacturing: ~€1,6 Mrd.',
excerpt_en: 'DACH IT security market: €8.2B (Bitkom 2025). AppSec share: ~15% = €1.2B. Pentesting/DAST/SAST for manufacturing: ~€400M. CRA obligation for manufacturers creates new demand: est. +€200M by 2028. SAM for integrated AppSec + compliance in DACH manufacturing: ~€1.6B.',
excerpt_de: 'Die DACH-Region hat ca. 5.000 Maschinen- und Anlagenbauer mit eigener Softwareentwicklung. Der Compliance- und Security-Software-Markt fuer diese Branche wird auf ca. 850 Mio. EUR geschaetzt — getrieben durch CRA, NIS2, AI Act und steigende Anforderungen an Produktsoftware.',
excerpt_en: 'The DACH region has approx. 5,000 machine and plant manufacturers with in-house software development. The compliance and security software market for this industry is estimated at approx. EUR 850M — driven by CRA, NIS2, AI Act and increasing requirements for product software.',
},
],
SOM: [
{
name: 'VDMA + Branchenbenchmarks — Pentesting SOM',
url: 'https://www.vdma.org/statistics',
date: '2025-2026',
excerpt_de: 'Zielmarkt: 5.000 DACH-Maschinenbauer mit Eigenentwicklung. Bei 10% Durchdringung (500 Unternehmen) und €70K/Jahr Blended ARPU (Compliance €18K + AppSec €52K) ergibt sich ein SOM von €35 Mio. in Year 5. Zum Vergleich: Pentera erreicht mit 400 MA $100M ARR bei 900 Kunden. Intruder (100 MA) erreicht $10M bei 2.500 Kunden.',
excerpt_en: 'Target market: 5,000 DACH manufacturers with in-house development. At 10% penetration (500 companies) and €70K/yr blended ARPU (compliance €18K + AppSec €52K), SOM is €35M in Year 5. For comparison: Pentera achieves $100M ARR with 400 employees and 900 customers. Intruder (100 employees) achieves $10M with 2,500 customers.',
name: 'VDMA Mitgliederstatistik + eigene Analyse',
url: 'https://www.vdma.org/mitglieder',
date: '2024-2025',
excerpt_de: 'Im VDMA sind ca. 3.600 Unternehmen allein in Deutschland registriert, DACH-weit ca. 5.000. Die meisten haben Embedded-Softwareentwicklung im Haus. Bei einer realistischen Marktdurchdringung von 10% (~500 Unternehmen) und einem durchschnittlichen Jahresumsatz von ~14.400 EUR pro Kunde (Blended Avg. aus Mini/Studio/Cloud) ergibt sich ein SOM von ca. 7,2 Mio. EUR.',
excerpt_en: 'The VDMA has approx. 3,600 member companies in Germany alone, ~5,000 across DACH. Most have embedded software development in-house. At a realistic market penetration of 10% (~500 companies) and an average annual revenue of ~EUR 14,400 per customer (blended avg. of Mini/Studio/Cloud), the SOM is approx. EUR 7.2M.',
},
],
}
@@ -124,16 +62,14 @@ function SourceModal({
onClose,
segment,
lang,
sources: sourcesMap,
}: {
isOpen: boolean
onClose: () => void
segment: string
lang: Language
sources?: Record<string, MarketSourceInfo[]>
}) {
if (!isOpen) return null
const sources = (sourcesMap || marketSources)[segment] || []
const sources = marketSources[segment] || []
return (
<AnimatePresence>
@@ -205,201 +141,117 @@ export default function MarketSlide({ lang, market }: MarketSlideProps) {
const segments = [i.market.tam, i.market.sam, i.market.som]
const segmentKeys = ['TAM', 'SAM', 'SOM']
const [activeModal, setActiveModal] = useState<string | null>(null)
const [marketView, setMarketView] = useState<MarketView>('compliance')
const activeSources = marketView === 'compliance' ? marketSources : pentestMarketSources
return (
<div>
<FadeInView className="text-center mb-6">
<FadeInView className="text-center mb-12">
<h2 className="text-4xl md:text-5xl font-bold mb-3">
<GradientText>{i.market.title}</GradientText>
</h2>
<p className="text-lg text-white/50 max-w-2xl mx-auto">{i.market.subtitle}</p>
</FadeInView>
{/* Market View Toggle */}
<FadeInView delay={0.1} className="flex justify-center gap-2 mb-8">
<button
onClick={() => setMarketView('compliance')}
className={`px-4 py-1.5 rounded-full text-xs font-medium transition-all ${
marketView === 'compliance'
? 'bg-indigo-500/20 text-indigo-300 border border-indigo-500/30'
: 'bg-white/[0.04] text-white/40 border border-white/5 hover:bg-white/[0.08]'
}`}
>
{lang === 'de' ? 'Compliance & Code-Security' : 'Compliance & Code Security'}
</button>
<button
onClick={() => setMarketView('pentesting')}
className={`px-4 py-1.5 rounded-full text-xs font-medium transition-all flex items-center gap-1.5 ${
marketView === 'pentesting'
? 'bg-red-500/20 text-red-300 border border-red-500/30'
: 'bg-white/[0.04] text-white/40 border border-white/5 hover:bg-white/[0.08]'
}`}
>
<Shield className="w-3 h-3" />
{lang === 'de' ? 'Pentesting & AppSec' : 'Pentesting & AppSec'}
</button>
</FadeInView>
<div className="flex flex-col md:flex-row items-center justify-center gap-12">
{/* Circles */}
<div className="relative flex items-center justify-center" style={{ width: 300, height: 300 }}>
{market.map((m, idx) => (
<motion.div
key={m.id}
initial={{ scale: 0, opacity: 0 }}
animate={{ scale: 1, opacity: 1 }}
transition={{ delay: 0.3 + idx * 0.2, type: 'spring', stiffness: 200 }}
className={`absolute rounded-full border-2 ${colors[idx]} flex items-center justify-center`}
style={{
width: sizes[idx],
height: sizes[idx],
}}
>
{idx === market.length - 1 && (
<div className="text-center">
<span className={`text-xs font-mono ${textColors[idx]}`}>{segments[idx]}</span>
</div>
)}
</motion.div>
))}
</div>
{/* Compliance Market */}
{marketView === 'compliance' && (
<div className="flex flex-col md:flex-row items-center justify-center gap-12">
<div className="relative flex items-center justify-center" style={{ width: 300, height: 300 }}>
{market.map((m, idx) => (
{/* Labels */}
<div className="space-y-6">
{market.map((m, idx) => {
const segKey = segmentKeys[idx] || m.market_segment
const sourceCount = marketSources[segKey]?.length || 0
return (
<motion.div
key={m.id}
initial={{ scale: 0, opacity: 0 }}
animate={{ scale: 1, opacity: 1 }}
transition={{ delay: 0.3 + idx * 0.2, type: 'spring', stiffness: 200 }}
className={`absolute rounded-full border-2 ${colors[idx]} flex items-center justify-center`}
style={{ width: sizes[idx], height: sizes[idx] }}
initial={{ opacity: 0, x: 20 }}
animate={{ opacity: 1, x: 0 }}
transition={{ delay: 0.5 + idx * 0.15 }}
className="group cursor-pointer"
onClick={() => setActiveModal(segKey)}
>
{idx === market.length - 1 && (
<div className="text-center">
<span className={`text-xs font-mono ${textColors[idx]}`}>{segments[idx]}</span>
</div>
)}
</motion.div>
))}
</div>
<div className="space-y-6">
{market.map((m, idx) => {
const segKey = segmentKeys[idx] || m.market_segment
const sourceCount = marketSources[segKey]?.length || 0
return (
<motion.div
key={m.id}
initial={{ opacity: 0, x: 20 }}
animate={{ opacity: 1, x: 0 }}
transition={{ delay: 0.5 + idx * 0.15 }}
className="group cursor-pointer"
onClick={() => setActiveModal(segKey)}
>
<div className="flex items-center gap-4">
<div className={`w-3 h-3 rounded-full ${textColors[idx]} bg-current`} />
<div>
<div className="flex items-center gap-2">
<span className={`text-sm font-bold ${textColors[idx]}`}>{segments[idx]}</span>
<span className="text-xs text-white/30">{labels[idx]}</span>
</div>
<div className="text-2xl font-bold text-white">
{m.value_eur >= 1_000_000_000 ? (
<AnimatedCounter target={m.value_eur / 1_000_000_000} suffix={lang === 'de' ? ' Mrd. EUR' : 'B EUR'} decimals={1} duration={1500} />
) : m.value_eur >= 1_000_000 ? (
<AnimatedCounter target={m.value_eur / 1_000_000} suffix={lang === 'de' ? ' Mio. EUR' : 'M EUR'} decimals={1} duration={1500} />
) : (
<AnimatedCounter target={m.value_eur / 1_000} suffix={'k EUR'} decimals={0} duration={1500} />
)}
</div>
<div className="flex items-center gap-3 text-xs">
{m.growth_rate_pct > 0 && (
<span className="flex items-center gap-1 text-emerald-400">
<TrendingUp className="w-3 h-3" />
{m.growth_rate_pct}% p.a.
</span>
)}
<span className="text-white/40">{i.market.source}: {m.source}</span>
</div>
<p className="text-[10px] text-indigo-400/60 group-hover:text-indigo-400 transition-colors mt-0.5">
{sourceCount} {lang === 'de' ? (sourceCount === 1 ? 'Quelle' : 'Quellen') : (sourceCount === 1 ? 'source' : 'sources')}
{' · '}{lang === 'de' ? 'Klicken fuer Details' : 'Click for details'}
</p>
<div className="flex items-center gap-4">
<div className={`w-3 h-3 rounded-full ${textColors[idx]} bg-current`} />
<div>
<div className="flex items-center gap-2">
<span className={`text-sm font-bold ${textColors[idx]}`}>{segments[idx]}</span>
<span className="text-xs text-white/30">{labels[idx]}</span>
</div>
</div>
</motion.div>
)
})}
</div>
</div>
)}
{/* Pentesting Market */}
{marketView === 'pentesting' && (
<div className="flex flex-col md:flex-row items-center justify-center gap-12">
<div className="relative flex items-center justify-center" style={{ width: 300, height: 300 }}>
{PENTEST_MARKET.map((pm, idx) => (
<motion.div
key={pm.segment}
initial={{ scale: 0, opacity: 0 }}
animate={{ scale: 1, opacity: 1 }}
transition={{ delay: 0.3 + idx * 0.2, type: 'spring', stiffness: 200 }}
className={`absolute rounded-full border-2 ${
idx === 0 ? 'border-red-500/30 bg-red-500/5' :
idx === 1 ? 'border-orange-500/30 bg-orange-500/5' :
'border-yellow-500/30 bg-yellow-500/5'
} flex items-center justify-center`}
style={{ width: sizes[idx], height: sizes[idx] }}
>
{idx === PENTEST_MARKET.length - 1 && (
<div className="text-center">
<span className="text-xs font-mono text-yellow-400">{pm.segment}</span>
</div>
)}
</motion.div>
))}
</div>
<div className="space-y-6">
{PENTEST_MARKET.map((pm, idx) => {
const ptColors = ['text-red-400', 'text-orange-400', 'text-yellow-400']
const sourceCount = pentestMarketSources[pm.segment]?.length || 0
return (
<motion.div
key={pm.segment}
initial={{ opacity: 0, x: 20 }}
animate={{ opacity: 1, x: 0 }}
transition={{ delay: 0.5 + idx * 0.15 }}
className="group cursor-pointer"
onClick={() => setActiveModal(pm.segment)}
>
<div className="flex items-center gap-4">
<div className={`w-3 h-3 rounded-full ${ptColors[idx]} bg-current`} />
<div>
<div className="flex items-center gap-2">
<span className={`text-sm font-bold ${ptColors[idx]}`}>{pm.segment}</span>
<span className="text-xs text-white/30">{pm.label[lang]}</span>
</div>
<div className="text-2xl font-bold text-white">
{pm.value_eur >= 1_000_000_000 ? (
<AnimatedCounter target={pm.value_eur / 1_000_000_000} suffix={lang === 'de' ? ' Mrd. EUR' : 'B EUR'} decimals={1} duration={1500} />
) : pm.value_eur >= 1_000_000 ? (
<AnimatedCounter target={pm.value_eur / 1_000_000} suffix={lang === 'de' ? ' Mio. EUR' : 'M EUR'} decimals={1} duration={1500} />
) : (
<AnimatedCounter target={pm.value_eur / 1_000} suffix={'k EUR'} decimals={0} duration={1500} />
)}
</div>
<div className="flex items-center gap-3 text-xs">
{pm.growth_rate_pct > 0 && (
<span className="flex items-center gap-1 text-emerald-400">
<TrendingUp className="w-3 h-3" />
{pm.growth_rate_pct}% p.a.
</span>
)}
<span className="text-white/40">{i.market.source}: {pm.source}</span>
</div>
<p className="text-[10px] text-red-400/60 group-hover:text-red-400 transition-colors mt-0.5">
{sourceCount} {lang === 'de' ? (sourceCount === 1 ? 'Quelle' : 'Quellen') : (sourceCount === 1 ? 'source' : 'sources')}
{' · '}{lang === 'de' ? 'Klicken fuer Details' : 'Click for details'}
</p>
<div className="text-2xl font-bold text-white">
{m.value_eur >= 1_000_000_000 ? (
<AnimatedCounter
target={m.value_eur / 1_000_000_000}
suffix={lang === 'de' ? ' Mrd. EUR' : 'B EUR'}
decimals={1}
duration={1500}
/>
) : m.value_eur >= 1_000_000 ? (
<AnimatedCounter
target={m.value_eur / 1_000_000}
suffix={lang === 'de' ? ' Mio. EUR' : 'M EUR'}
decimals={1}
duration={1500}
/>
) : (
<AnimatedCounter
target={m.value_eur / 1_000}
suffix={'k EUR'}
decimals={0}
duration={1500}
/>
)}
</div>
<div className="flex items-center gap-3 text-xs">
{m.growth_rate_pct > 0 && (
<span className="flex items-center gap-1 text-emerald-400">
<TrendingUp className="w-3 h-3" />
{m.growth_rate_pct}% p.a.
</span>
)}
<span className="text-white/40">
{i.market.source}: {m.source}
</span>
</div>
<p className="text-[10px] text-indigo-400/60 group-hover:text-indigo-400 transition-colors mt-0.5">
{sourceCount} {lang === 'de' ? (sourceCount === 1 ? 'Quelle' : 'Quellen') : (sourceCount === 1 ? 'source' : 'sources')}
{' · '}
{lang === 'de' ? 'Klicken fuer Details' : 'Click for details'}
</p>
</div>
</motion.div>
)
})}
</div>
</div>
</motion.div>
)
})}
</div>
)}
</div>
{/* Source Modals — both compliance and pentesting */}
{/* Source Modals */}
{segmentKeys.map((seg) => (
<SourceModal
key={`c-${seg}`}
key={seg}
isOpen={activeModal === seg}
onClose={() => setActiveModal(null)}
segment={seg}
lang={lang}
sources={activeSources}
/>
))}
</div>

View File

@@ -44,13 +44,6 @@ const cardSources: ProblemCardData[] = [
excerpt_de: 'Laut der DIHK-Digitalisierungsumfrage 2024 geben 83% der befragten KMU an, die DSGVO-Anforderungen nicht vollstaendig umgesetzt zu haben. Hauptgruende sind mangelnde Ressourcen, fehlendes Know-how und die Komplexitaet der Vorschriften.',
excerpt_en: 'According to the DIHK Digitization Survey 2024, 83% of surveyed SMEs report not having fully implemented GDPR requirements. Main reasons cited are lack of resources, missing expertise, and regulatory complexity.',
},
{
name: 'Compliance-Markt validiert: Top-10 Anbieter >$1,1 Mrd. Umsatz',
url: 'https://sacra.com/c/vanta/',
date: '2025-2026',
excerpt_de: 'Der Markt ist real: Vanta ($220M ARR, $4,15 Mrd. Bewertung), Drata ($100M), OneTrust ($500M+), DataGuard (€52M). Allein die Top-10 Compliance-Automation-Anbieter erzielen >$1,1 Mrd. Umsatz. Trotzdem managen 80% der Unternehmen Compliance noch manuell — die Marktdurchdringung ist erst am Anfang.',
excerpt_en: 'The market is real: Vanta ($220M ARR, $4.15B valuation), Drata ($100M), OneTrust ($500M+), DataGuard (€52M). The top 10 compliance automation providers alone generate >$1.1B revenue. Yet 80% of companies still manage compliance manually — market penetration is still early.',
},
],
},
{

View File

@@ -11,7 +11,6 @@ interface UseKeyboardProps {
onFullscreen: () => void
onLanguageToggle: () => void
onMenuToggle: () => void
onPresenterToggle?: () => void
onGoToSlide: (index: number) => void
enabled?: boolean
}
@@ -25,7 +24,6 @@ export function useKeyboard({
onFullscreen,
onLanguageToggle,
onMenuToggle,
onPresenterToggle,
onGoToSlide,
enabled = true,
}: UseKeyboardProps) {
@@ -76,11 +74,6 @@ export function useKeyboard({
e.preventDefault()
onMenuToggle()
break
case 'p':
case 'P':
e.preventDefault()
onPresenterToggle?.()
break
case '1':
case '2':
case '3':
@@ -95,7 +88,7 @@ export function useKeyboard({
break
}
},
[enabled, onNext, onPrev, onFirst, onLast, onOverview, onFullscreen, onLanguageToggle, onMenuToggle, onPresenterToggle, onGoToSlide]
[enabled, onNext, onPrev, onFirst, onLast, onOverview, onFullscreen, onLanguageToggle, onMenuToggle, onGoToSlide]
)
useEffect(() => {

View File

@@ -1,254 +0,0 @@
'use client'
import { useState, useCallback, useRef, useEffect } from 'react'
import { Language, SlideId } from '../types'
import { PresenterState } from '../presenter/types'
import { PRESENTER_SCRIPT } from '../presenter/presenter-script'
import { SLIDE_ORDER } from './useSlideNavigation'
interface UsePresenterModeConfig {
goToSlide: (index: number) => void
currentSlide: number
totalSlides: number
language: Language
}
interface UsePresenterModeReturn {
state: PresenterState
currentParagraph: number
start: () => void
stop: () => void
pause: () => void
resume: () => void
skipSlide: () => void
toggle: () => void
displayText: string
progress: number
}
export function usePresenterMode({
goToSlide,
currentSlide,
totalSlides,
language,
}: UsePresenterModeConfig): UsePresenterModeReturn {
const [state, setState] = useState<PresenterState>('idle')
const [currentParagraph, setCurrentParagraph] = useState(0)
const [displayText, setDisplayText] = useState('')
const timerRef = useRef<NodeJS.Timeout | null>(null)
const slideIndexRef = useRef(currentSlide)
const paragraphIndexRef = useRef(0)
const stateRef = useRef<PresenterState>('idle')
// Keep refs in sync
useEffect(() => {
slideIndexRef.current = currentSlide
}, [currentSlide])
useEffect(() => {
stateRef.current = state
}, [state])
const clearTimer = useCallback(() => {
if (timerRef.current) {
clearTimeout(timerRef.current)
timerRef.current = null
}
}, [])
const getScriptForIndex = useCallback((index: number) => {
const slideId = SLIDE_ORDER[index]
return PRESENTER_SCRIPT.find(s => s.slideId === slideId)
}, [])
const showParagraph = useCallback((slideIdx: number, paraIdx: number) => {
const script = getScriptForIndex(slideIdx)
if (!script || paraIdx >= script.paragraphs.length) return null
const para = script.paragraphs[paraIdx]
const text = language === 'de' ? para.text_de : para.text_en
setDisplayText(text)
setCurrentParagraph(paraIdx)
paragraphIndexRef.current = paraIdx
return para
}, [language, getScriptForIndex])
const advancePresentation = useCallback(() => {
if (stateRef.current !== 'presenting') return
const slideIdx = slideIndexRef.current
const script = getScriptForIndex(slideIdx)
if (!script) {
// No script for this slide, advance to next
if (slideIdx < totalSlides - 1) {
goToSlide(slideIdx + 1)
paragraphIndexRef.current = 0
// Schedule next after slide transition
timerRef.current = setTimeout(() => advancePresentation(), 2000)
} else {
setState('idle')
setDisplayText('')
}
return
}
const nextPara = paragraphIndexRef.current + 1
if (nextPara < script.paragraphs.length) {
// Show next paragraph
const para = showParagraph(slideIdx, nextPara)
if (para) {
// Calculate display time: ~150ms per word + pause
const wordCount = (language === 'de' ? para.text_de : para.text_en).split(/\s+/).length
const readingTime = Math.max(wordCount * 150, 2000)
timerRef.current = setTimeout(() => advancePresentation(), readingTime + para.pause_after)
}
} else {
// All paragraphs done for this slide
// Show transition hint briefly
if (script.transition_hint_de || script.transition_hint_en) {
const hint = language === 'de'
? (script.transition_hint_de || '')
: (script.transition_hint_en || '')
setDisplayText(hint)
}
// Move to next slide
if (slideIdx < totalSlides - 1) {
timerRef.current = setTimeout(() => {
if (stateRef.current !== 'presenting') return
goToSlide(slideIdx + 1)
paragraphIndexRef.current = -1 // Will be incremented to 0
timerRef.current = setTimeout(() => {
if (stateRef.current !== 'presenting') return
const nextScript = getScriptForIndex(slideIdx + 1)
if (nextScript && nextScript.paragraphs.length > 0) {
const para = showParagraph(slideIdx + 1, 0)
if (para) {
const wordCount = (language === 'de' ? para.text_de : para.text_en).split(/\s+/).length
const readingTime = Math.max(wordCount * 150, 2000)
timerRef.current = setTimeout(() => advancePresentation(), readingTime + para.pause_after)
}
} else {
advancePresentation()
}
}, 1500)
}, 2000)
} else {
// Last slide — done
timerRef.current = setTimeout(() => {
setState('idle')
setDisplayText('')
}, 3000)
}
}
}, [language, totalSlides, goToSlide, getScriptForIndex, showParagraph])
const start = useCallback(() => {
clearTimer()
setState('presenting')
const slideIdx = slideIndexRef.current
const script = getScriptForIndex(slideIdx)
if (script && script.paragraphs.length > 0) {
const para = showParagraph(slideIdx, 0)
if (para) {
const wordCount = (language === 'de' ? para.text_de : para.text_en).split(/\s+/).length
const readingTime = Math.max(wordCount * 150, 2000)
timerRef.current = setTimeout(() => advancePresentation(), readingTime + para.pause_after)
}
} else {
// No script, advance immediately
timerRef.current = setTimeout(() => advancePresentation(), 1000)
}
}, [clearTimer, language, getScriptForIndex, showParagraph, advancePresentation])
const stop = useCallback(() => {
clearTimer()
setState('idle')
setDisplayText('')
setCurrentParagraph(0)
paragraphIndexRef.current = 0
}, [clearTimer])
const pause = useCallback(() => {
clearTimer()
setState('paused')
}, [clearTimer])
const resume = useCallback(() => {
setState('resuming')
// Brief pause before continuing
timerRef.current = setTimeout(() => {
setState('presenting')
// Continue from where we left off
advancePresentation()
}, 2000)
}, [advancePresentation])
const skipSlide = useCallback(() => {
clearTimer()
const nextIdx = slideIndexRef.current + 1
if (nextIdx < totalSlides) {
goToSlide(nextIdx)
paragraphIndexRef.current = -1
if (stateRef.current === 'presenting') {
timerRef.current = setTimeout(() => {
const script = getScriptForIndex(nextIdx)
if (script && script.paragraphs.length > 0) {
const para = showParagraph(nextIdx, 0)
if (para) {
const wordCount = (language === 'de' ? para.text_de : para.text_en).split(/\s+/).length
const readingTime = Math.max(wordCount * 150, 2000)
timerRef.current = setTimeout(() => advancePresentation(), readingTime + para.pause_after)
}
}
}, 1500)
}
}
}, [clearTimer, totalSlides, goToSlide, language, getScriptForIndex, showParagraph, advancePresentation])
const toggle = useCallback(() => {
if (stateRef.current === 'idle') {
start()
} else {
stop()
}
}, [start, stop])
// Calculate overall progress
const progress = (() => {
if (state === 'idle') return 0
const totalScripts = PRESENTER_SCRIPT.length
const currentScriptIdx = PRESENTER_SCRIPT.findIndex(s => s.slideId === SLIDE_ORDER[currentSlide])
if (currentScriptIdx < 0) return (currentSlide / totalSlides) * 100
const script = PRESENTER_SCRIPT[currentScriptIdx]
const slideProgress = script.paragraphs.length > 0
? currentParagraph / script.paragraphs.length
: 0
return ((currentScriptIdx + slideProgress) / totalScripts) * 100
})()
// Cleanup on unmount
useEffect(() => {
return () => clearTimer()
}, [clearTimer])
return {
state,
currentParagraph,
start,
stop,
pause,
resume,
skipSlide,
toggle,
displayText,
progress,
}
}

View File

@@ -3,8 +3,7 @@
import { useState, useCallback } from 'react'
import { SlideId } from '../types'
export const SLIDE_ORDER: SlideId[] = [
'intro-presenter',
const SLIDE_ORDER: SlideId[] = [
'cover',
'problem',
'solution',

View File

@@ -8,7 +8,6 @@ const translations = {
language: 'Sprache',
},
slideNames: [
'Intro',
'Cover',
'Das Problem',
'Die Loesung',
@@ -26,8 +25,6 @@ const translations = {
'Anhang: Architektur',
'Anhang: Go-to-Market',
'Anhang: Regulatorik',
'Anhang: Engineering',
'Anhang: KI-Pipeline',
],
cover: {
tagline: 'Compliance & Code-Security fuer den Maschinenbau',
@@ -140,7 +137,7 @@ const translations = {
},
competition: {
title: 'Wettbewerb',
subtitle: '44 Features, 9 USPs — kein Anbieter kombiniert DSGVO + Code-Security + Self-Hosted KI',
subtitle: '44 Features vs. ~15-25 bei Wettbewerbern — 9 einzigartige USPs',
feature: 'Feature',
selfHosted: 'Self-Hosted',
integratedAI: 'Integrierte KI',
@@ -231,7 +228,6 @@ const translations = {
language: 'Language',
},
slideNames: [
'Intro',
'Cover',
'The Problem',
'The Solution',
@@ -249,8 +245,6 @@ const translations = {
'Appendix: Architecture',
'Appendix: Go-to-Market',
'Appendix: Regulatory',
'Appendix: Engineering',
'Appendix: AI Pipeline',
],
cover: {
tagline: 'Compliance & Code Security for Machine Manufacturers',
@@ -363,7 +357,7 @@ const translations = {
},
competition: {
title: 'Competition',
subtitle: '44 features, 9 USPs — no provider combines GDPR + code security + self-hosted AI',
subtitle: '44 features vs. ~15-25 competitors — 9 unique USPs',
feature: 'Feature',
selfHosted: 'Self-Hosted',
integratedAI: 'Integrated AI',

View File

@@ -1,72 +0,0 @@
import { Language } from '../types'
import { FAQEntry } from './types'
import { PRESENTER_FAQ } from './presenter-faq'
/**
* Match a user query against pre-cached FAQ entries.
* Returns the best match if score exceeds threshold, or null for LLM fallback.
*/
export function matchFAQ(query: string, lang: Language): FAQEntry | null {
const normalized = query.toLowerCase().trim()
const queryWords = normalized.split(/\s+/)
let bestMatch: FAQEntry | null = null
let bestScore = 0
for (const entry of PRESENTER_FAQ) {
let score = 0
// Check keyword matches
for (const keyword of entry.keywords) {
const kwLower = keyword.toLowerCase()
if (kwLower.includes(' ')) {
// Multi-word keyword: check if phrase appears in query
if (normalized.includes(kwLower)) {
score += 3 * entry.priority / 10
}
} else {
// Single keyword: check word-level match
if (queryWords.some(w => w === kwLower || w.startsWith(kwLower) || kwLower.startsWith(w))) {
score += 1
}
// Also check if keyword appears anywhere in query (partial match)
if (normalized.includes(kwLower)) {
score += 0.5
}
}
}
// Check if query matches the question text closely
const questionText = lang === 'de' ? entry.question_de : entry.question_en
const questionWords = questionText.toLowerCase().split(/\s+/)
const overlapCount = queryWords.filter(w =>
w.length > 2 && questionWords.some(qw => qw.includes(w) || w.includes(qw))
).length
if (overlapCount >= 2) {
score += overlapCount * 0.5
}
// Weight by priority
score *= (entry.priority / 10)
if (score > bestScore) {
bestScore = score
bestMatch = entry
}
}
// Threshold: need meaningful match to avoid false positives
// Require at least 2 keyword hits or strong phrase match
if (bestScore < 1.5) {
return null
}
return bestMatch
}
/**
* Get FAQ answer text in the requested language
*/
export function getFAQAnswer(entry: FAQEntry, lang: Language): string {
return lang === 'de' ? entry.answer_de : entry.answer_en
}

View File

@@ -1,300 +0,0 @@
import { FAQEntry } from './types'
export const PRESENTER_FAQ: FAQEntry[] = [
// === PRODUCT ===
{
id: 'product-what',
keywords: ['was', 'macht', 'breakpilot', 'what', 'does', 'product', 'produkt'],
question_de: 'Was macht BreakPilot?',
question_en: 'What does BreakPilot do?',
answer_de: 'BreakPilot ComplAI ist eine KI-gesteuerte Compliance- und Code-Security-Plattform fuer Maschinenbauer. Eine Self-Hosted Hardware-Appliance (Mac Mini/Studio) scannt Code und erstellt Compliance-Dokumente. 57 Module decken DSGVO, AI Act, CRA und NIS2 ab — mit 2.274 indexierten Rechtstexten.',
answer_en: 'BreakPilot ComplAI is an AI-powered compliance and code security platform for machine manufacturers. A self-hosted hardware appliance (Mac Mini/Studio) scans code and creates compliance documents. 57 modules cover GDPR, AI Act, CRA and NIS2 — with 2,274 indexed legal texts.',
goto_slide: 'solution',
priority: 10,
},
{
id: 'product-modules',
keywords: ['module', 'modules', 'funktionen', 'features', 'umfang', 'scope', 'wieviele', 'how many'],
question_de: 'Welche Module hat die Plattform?',
question_en: 'What modules does the platform have?',
answer_de: '57 Compliance-Module: DSGVO (VVT, DSFA, TOM, DSR, Loeschfristen), AI Act (Risikoklassifizierung, Dokumentation), CRA (Code-Security, SBOM), NIS2 (Incident Response, Notfallplan), plus Vendor Compliance, Audit-Management, Policy Generator und mehr.',
answer_en: '57 compliance modules: GDPR (RoPA, DPIA, TOMs, DSR, deletion deadlines), AI Act (risk classification, documentation), CRA (code security, SBOM), NIS2 (incident response, emergency plans), plus vendor compliance, audit management, policy generator and more.',
goto_slide: 'solution',
priority: 8,
},
{
id: 'product-dsgvo-vs-aiact',
keywords: ['dsgvo', 'gdpr', 'ai act', 'unterschied', 'difference', 'versus', 'vs'],
question_de: 'Was ist der Unterschied zwischen DSGVO und AI Act Compliance?',
question_en: 'What is the difference between GDPR and AI Act compliance?',
answer_de: 'DSGVO schuetzt personenbezogene Daten (Verarbeitungsverzeichnis, Loeschfristen, Betroffenenrechte). Der AI Act reguliert KI-Systeme (Risikoklassifizierung, Transparenz, Human Oversight). Maschinenbauer mit KI in ihren Produkten brauchen beides — und genau das liefern wir.',
answer_en: 'GDPR protects personal data (records of processing, deletion deadlines, data subject rights). The AI Act regulates AI systems (risk classification, transparency, human oversight). Machine manufacturers with AI in their products need both — and that is exactly what we deliver.',
priority: 7,
},
// === TECHNOLOGY ===
{
id: 'tech-llm',
keywords: ['llm', 'modell', 'model', 'ki', 'ai', 'kuenstliche intelligenz', 'artificial intelligence', 'welches', 'which'],
question_de: 'Welches KI-Modell nutzt ihr?',
question_en: 'Which AI model do you use?',
answer_de: 'Wir setzen auf eine proprietaere KI-Engine mit verschiedenen Modellgroessen: 32B Parameter lokal auf Mac Mini, 40B auf Mac Studio, und ein BSI-zertifiziertes 1000B Cloud-LLM fuer komplexe Aufgaben. Die lokalen Modelle machen die Vorarbeit, die Cloud implementiert Fixes.',
answer_en: 'We use a proprietary AI engine with different model sizes: 32B parameters locally on Mac Mini, 40B on Mac Studio, and a BSI-certified 1000B cloud LLM for complex tasks. Local models do the preprocessing, the cloud implements fixes.',
goto_slide: 'product',
priority: 8,
},
{
id: 'tech-opensource',
keywords: ['open source', 'opensource', 'quellcode', 'source code', 'lizenz', 'license'],
question_de: 'Ist die Plattform Open Source?',
question_en: 'Is the platform open source?',
answer_de: 'Die Plattform selbst ist proprietaer, nutzt aber ausschliesslich Open-Source-Dependencies mit kommerziell nutzbaren Lizenzen (MIT, Apache-2.0, BSD). Wir verwenden keine GPL/AGPL-abhaengigkeiten. Die Hardware laeuft auf Apple Silicon.',
answer_en: 'The platform itself is proprietary but uses exclusively open source dependencies with commercially usable licenses (MIT, Apache-2.0, BSD). We use no GPL/AGPL dependencies. The hardware runs on Apple Silicon.',
priority: 6,
},
{
id: 'tech-security',
keywords: ['sicherheit', 'security', 'datenschutz', 'privacy', 'verschluesselung', 'encryption', 'hosting'],
question_de: 'Wie sicher sind die Daten?',
question_en: 'How secure is the data?',
answer_de: 'Maximale Datensouveraenitaet: Die Hardware steht im Serverraum des Kunden. Alle Daten bleiben on-premise. Nur anonymisierte Anfragen gehen an die BSI-zertifizierte Cloud. TLS 1.3 fuer alle Verbindungen, Vault fuer Secrets, Enterprise-Grade Verschluesselung.',
answer_en: 'Maximum data sovereignty: The hardware sits in the customer server room. All data stays on-premise. Only anonymized queries go to the BSI-certified cloud. TLS 1.3 for all connections, Vault for secrets, enterprise-grade encryption.',
goto_slide: 'annex-architecture',
priority: 8,
},
{
id: 'tech-selfhosted',
keywords: ['self-hosted', 'selfhosted', 'self hosted', 'on-premise', 'onpremise', 'lokal', 'local', 'warum', 'why', 'mac'],
question_de: 'Warum Self-Hosted auf Apple Hardware?',
question_en: 'Why self-hosted on Apple hardware?',
answer_de: 'Drei Gruende: 1) Datensouveraenitaet — Kundendaten verlassen nie das Unternehmen. 2) Apple Silicon bietet das beste Preis-Leistungs-Verhaeltnis fuer lokale LLM-Inferenz. 3) Hardware-Moat — die Appliance schafft einen natuerlichen Lock-in und differentiert uns vom Wettbewerb.',
answer_en: 'Three reasons: 1) Data sovereignty — customer data never leaves the company. 2) Apple Silicon offers the best price-performance ratio for local LLM inference. 3) Hardware moat — the appliance creates a natural lock-in and differentiates us from competition.',
goto_slide: 'solution',
priority: 7,
},
{
id: 'tech-code-scanning',
keywords: ['code', 'scan', 'scanning', 'firmware', 'devsecops', 'trivy', 'semgrep', 'schwachstellen', 'vulnerability'],
question_de: 'Wie funktioniert das Code-Scanning?',
question_en: 'How does code scanning work?',
answer_de: 'Integrierte DevSecOps-Tools (Trivy, Semgrep, Gitleaks) scannen automatisch Git-Repos und Firmware bei jedem Commit. Die lokale KI priorisiert Findings, das Cloud-LLM implementiert Fixes und schreibt Risikoanalysen fuer den CRA.',
answer_en: 'Integrated DevSecOps tools (Trivy, Semgrep, Gitleaks) automatically scan Git repos and firmware on every commit. The local AI prioritizes findings, the cloud LLM implements fixes and writes risk assessments for the CRA.',
goto_slide: 'how-it-works',
priority: 7,
},
// === MARKET ===
{
id: 'market-tam',
keywords: ['tam', 'sam', 'som', 'markt', 'market', 'marktgroesse', 'market size', 'adressierbar'],
question_de: 'Wie gross ist der Markt?',
question_en: 'How big is the market?',
answer_de: 'TAM: 8,7 Mrd. EUR (globaler RegTech-Markt, +23% p.a.). SAM: 1,2 Mrd. EUR (DACH-Maschinenbauer mit Softwareentwicklung). SOM: 7,2 Mio. EUR (500 Kunden x 14.400 EUR/Jahr). Der CRA allein betrifft ueber 30.000 Hersteller in der EU.',
answer_en: 'TAM: EUR 8.7B (global RegTech market, +23% p.a.). SAM: EUR 1.2B (DACH machine manufacturers with software development). SOM: EUR 7.2M (500 customers x EUR 14,400/year). The CRA alone affects over 30,000 manufacturers in the EU.',
goto_slide: 'market',
priority: 9,
},
{
id: 'market-target',
keywords: ['zielgruppe', 'target', 'kunden', 'customers', 'wer', 'who', 'maschinenbau', 'machine', 'vdma'],
question_de: 'Wer ist die Zielgruppe?',
question_en: 'Who is the target audience?',
answer_de: 'Primaer: Maschinen- und Anlagenbauer (VDMA ~3.600 Mitglieder in DE, ~5.000 DACH) die eigene Software und Firmware entwickeln. Diese Unternehmen muessen CRA, DSGVO, AI Act und NIS2 einhalten — haben aber keine spezialisierten Compliance-Tools fuer ihren Code.',
answer_en: 'Primary: Machine and plant manufacturers (VDMA ~3,600 members in DE, ~5,000 DACH) who develop their own software and firmware. These companies must comply with CRA, GDPR, AI Act and NIS2 — but lack specialized compliance tools for their code.',
goto_slide: 'market',
priority: 8,
},
// === COMPETITION ===
{
id: 'competition-diff',
keywords: ['wettbewerb', 'competition', 'konkurrenz', 'unterschied', 'differenzierung', 'differentiation', 'proliance', 'dataguard', 'heydata', 'vanta'],
question_de: 'Was unterscheidet euch vom Wettbewerb?',
question_en: 'What differentiates you from the competition?',
answer_de: 'Drei entscheidende Unterschiede: 1) Code-Security — wir scannen Firmware und Software, das kann kein anderer Compliance-Anbieter. 2) Self-Hosted KI — maximale Datensouveraenitaet. 3) Produkt-Compliance — wir machen nicht nur das Unternehmen, sondern auch die Produkte compliant (CRA).',
answer_en: 'Three decisive differences: 1) Code security — we scan firmware and software, no other compliance provider can do that. 2) Self-hosted AI — maximum data sovereignty. 3) Product compliance — we make not only the company, but also the products compliant (CRA).',
goto_slide: 'competition',
priority: 9,
},
{
id: 'competition-proliance',
keywords: ['proliance', 'dataguard', 'heydata', 'vergleich', 'comparison', 'versus'],
question_de: 'Warum koennen Proliance und DataGuard das nicht?',
question_en: 'Why can\'t Proliance and DataGuard do this?',
answer_de: 'Proliance, DataGuard und heyData fokussieren auf organisatorische DSGVO-Compliance — Verarbeitungsverzeichnisse, Datenschutzerklaerungen, Schulungen. Keiner bietet Code-Scanning, Firmware-Analyse oder CRA-Compliance. Sie machen das Unternehmen compliant, aber nicht die Produkte.',
answer_en: 'Proliance, DataGuard and heyData focus on organizational GDPR compliance — records of processing, privacy policies, training. None offer code scanning, firmware analysis or CRA compliance. They make the company compliant, but not the products.',
goto_slide: 'competition',
priority: 8,
},
// === BUSINESS MODEL ===
{
id: 'biz-pricing',
keywords: ['preis', 'price', 'pricing', 'kosten', 'cost', 'kostet', 'costs', 'wie viel', 'how much', 'subscription'],
question_de: 'Was kostet BreakPilot?',
question_en: 'What does BreakPilot cost?',
answer_de: 'Drei Tiers: ComplAI Starter (Mac Mini) ab 1.200 EUR/Monat, Professional (Mac Studio) ab 2.400 EUR/Monat, Enterprise mit Cloud-LLM ab 3.600 EUR/Monat. Die Hardware wird einmalig bereitgestellt, die Software laeuft als monatliche Subscription.',
answer_en: 'Three tiers: ComplAI Starter (Mac Mini) from EUR 1,200/month, Professional (Mac Studio) from EUR 2,400/month, Enterprise with cloud LLM from EUR 3,600/month. Hardware is provided once, software runs as monthly subscription.',
goto_slide: 'product',
priority: 9,
},
{
id: 'biz-revenue',
keywords: ['umsatz', 'revenue', 'arr', 'mrr', 'recurring', 'einnahmen', 'income'],
question_de: 'Wie sieht der Umsatzplan aus?',
question_en: 'What does the revenue plan look like?',
answer_de: 'Von 36k EUR (2026) auf 8,4 Mio EUR (2030). Rein recurring — monatliche Subscriptions. 380 Kunden bei 5,5 Mio EUR ARR in 2030. Break-Even voraussichtlich Ende 2028.',
answer_en: 'From EUR 36k (2026) to EUR 8.4M (2030). Purely recurring — monthly subscriptions. 380 customers at EUR 5.5M ARR in 2030. Break-even expected end of 2028.',
goto_slide: 'financials',
priority: 8,
},
{
id: 'biz-unit-economics',
keywords: ['unit economics', 'marge', 'margin', 'ltv', 'cac', 'amortisation', 'amortization'],
question_de: 'Wie sind die Unit Economics?',
question_en: 'What are the unit economics?',
answer_de: 'Bruttomarge ueber 70%. Hardware-Kosten amortisieren sich in wenigen Monaten. LTV/CAC Ratio verbessert sich auf ueber 5x bis 2029. Die AI-First Architektur haelt die operativen Kosten pro Kunde extrem niedrig.',
answer_en: 'Gross margin above 70%. Hardware costs amortize in a few months. LTV/CAC ratio improves to over 5x by 2029. The AI-first architecture keeps operational costs per customer extremely low.',
goto_slide: 'business-model',
priority: 7,
},
{
id: 'biz-scalability',
keywords: ['skalierung', 'scalability', 'skalierbar', 'scalable', 'wachstum', 'growth', 'personal', 'headcount'],
question_de: 'Wie skaliert das Geschaeftsmodell?',
question_en: 'How does the business model scale?',
answer_de: 'AI-First bedeutet: 10x Kunden erfordert nicht 10x Personal. Die KI automatisiert Compliance-Analyse und Code-Scanning. Das Team waechst von 2 auf 18 Personen bei 380 Kunden. Die Hardware-Appliance ist Plug-and-Play — kein aufwendiges Onboarding noetig.',
answer_en: 'AI-first means: 10x customers does not require 10x headcount. The AI automates compliance analysis and code scanning. The team grows from 2 to 18 people at 380 customers. The hardware appliance is plug-and-play — no extensive onboarding needed.',
goto_slide: 'financials',
priority: 7,
},
// === TEAM ===
{
id: 'team-founders',
keywords: ['team', 'gruender', 'founders', 'wer', 'who', 'erfahrung', 'experience', 'hintergrund', 'background'],
question_de: 'Wer sind die Gruender?',
question_en: 'Who are the founders?',
answer_de: 'Unser Gruenderteam vereint tiefe Domain-Expertise: Compliance-Wissen aus der Praxis, Software-Architektur fuer skalierbare Systeme, und KI-Erfahrung mit Large Language Models. Details finden Sie auf der Team-Slide.',
answer_en: 'Our founding team combines deep domain expertise: Compliance knowledge from practice, software architecture for scalable systems, and AI experience with large language models. Details on the team slide.',
goto_slide: 'team',
priority: 7,
},
// === INVESTMENT ===
{
id: 'invest-amount',
keywords: ['investment', 'investition', 'funding', 'finanzierung', 'wie viel', 'how much', 'kapital', 'capital', 'runde', 'round'],
question_de: 'Wie viel Kapital sucht ihr?',
question_en: 'How much capital are you seeking?',
answer_de: 'Wir suchen eine Pre-Seed Finanzierung. Das genaue Volumen und die Konditionen besprechen wir gerne im Detail. Das Kapital fliesst in Engineering, Vertrieb, Hardware-Bestand und regulatorische Reserve.',
answer_en: 'We are seeking pre-seed funding. We are happy to discuss the exact volume and terms in detail. Capital goes into engineering, sales, hardware inventory and regulatory reserve.',
goto_slide: 'the-ask',
priority: 9,
},
{
id: 'invest-use-of-funds',
keywords: ['use of funds', 'wofuer', 'what for', 'verwendung', 'allocation', 'mittelverwendung'],
question_de: 'Wofuer wird das Kapital verwendet?',
question_en: 'What will the capital be used for?',
answer_de: 'Vier Bereiche: 1) Engineering — Produktreife und weitere Module. 2) Vertrieb — erste Pilotkunden im VDMA-Netzwerk. 3) Hardware — Mac Minis/Studios fuer schnelle Auslieferung. 4) Reserve — regulatorische Anforderungen und Working Capital.',
answer_en: 'Four areas: 1) Engineering — product maturity and additional modules. 2) Sales — first pilot customers in VDMA network. 3) Hardware — Mac Minis/Studios for fast delivery. 4) Reserve — regulatory requirements and working capital.',
goto_slide: 'the-ask',
priority: 8,
},
{
id: 'invest-runway',
keywords: ['runway', 'burn', 'burn rate', 'reicht', 'lasts', 'monate', 'months', 'cashflow'],
question_de: 'Wie lang reicht das Kapital?',
question_en: 'How long does the capital last?',
answer_de: 'Die Pre-Seed Runde finanziert uns bis zur naechsten Finanzierungsrunde. Dank AI-First Architektur und Self-Hosted Ansatz ist unsere Burn Rate signifikant niedriger als bei Cloud-basierten SaaS-Startups.',
answer_en: 'The pre-seed round funds us until the next financing round. Thanks to AI-first architecture and self-hosted approach, our burn rate is significantly lower than cloud-based SaaS startups.',
goto_slide: 'financials',
priority: 7,
},
{
id: 'invest-valuation',
keywords: ['bewertung', 'valuation', 'konditionen', 'terms', 'instrument', 'safe', 'convertible'],
question_de: 'Was ist die Bewertung?',
question_en: 'What is the valuation?',
answer_de: 'Die genaue Bewertung und das Instrument besprechen wir gerne im persoenlichen Gespraech. Wir sind offen fuer marktgerechte Strukturen, die fuer beide Seiten attraktiv sind.',
answer_en: 'We are happy to discuss the exact valuation and instrument in a personal meeting. We are open to market-standard structures that are attractive for both sides.',
goto_slide: 'the-ask',
priority: 7,
},
// === REGULATORY ===
{
id: 'reg-cra',
keywords: ['cra', 'cyber resilience', 'cyber resilience act', 'firmware', 'produktsicherheit', 'product security'],
question_de: 'Was ist der Cyber Resilience Act?',
question_en: 'What is the Cyber Resilience Act?',
answer_de: 'Der CRA verpflichtet Hersteller, Software in ihren Produkten abzusichern — ueber den gesamten Lebenszyklus. Fuer Maschinenbauer mit Firmware und embedded Software bedeutet das: Vulnerability Management, SBOM, Incident Reporting. Genau das automatisiert BreakPilot.',
answer_en: 'The CRA obligates manufacturers to secure software in their products — throughout the entire lifecycle. For machine manufacturers with firmware and embedded software this means: vulnerability management, SBOM, incident reporting. That is exactly what BreakPilot automates.',
goto_slide: 'annex-regulatory',
priority: 7,
},
{
id: 'reg-nis2',
keywords: ['nis2', 'nis 2', 'cybersecurity', 'kritische infrastruktur', 'critical infrastructure'],
question_de: 'Was bedeutet NIS2 fuer Maschinenbauer?',
question_en: 'What does NIS2 mean for machine manufacturers?',
answer_de: 'NIS2 erweitert die Cybersecurity-Pflichten auf den Maschinenbau. Unternehmen muessen Risikomanagement, Incident Response und Supply-Chain-Security implementieren. BreakPilot bietet Module fuer alle drei Bereiche.',
answer_en: 'NIS2 extends cybersecurity obligations to machine manufacturing. Companies must implement risk management, incident response and supply chain security. BreakPilot offers modules for all three areas.',
goto_slide: 'annex-regulatory',
priority: 6,
},
// === GTM ===
{
id: 'gtm-strategy',
keywords: ['gtm', 'go-to-market', 'go to market', 'vertrieb', 'sales', 'strategie', 'strategy', 'akquise', 'acquisition'],
question_de: 'Wie gewinnt ihr Kunden?',
question_en: 'How do you acquire customers?',
answer_de: 'Drei Kanaele: 1) VDMA-Netzwerk — direkter Zugang zu 3.600+ Maschinenbauern. 2) Partnerschaften mit Systemhaeusern und IT-Dienstleistern. 3) Content Marketing ueber Compliance-Webinare und CRA-Awareness. Start mit 5 Pilotkunden, dann skalieren.',
answer_en: 'Three channels: 1) VDMA network — direct access to 3,600+ machine manufacturers. 2) Partnerships with system integrators and IT service providers. 3) Content marketing through compliance webinars and CRA awareness. Start with 5 pilot customers, then scale.',
goto_slide: 'annex-gtm',
priority: 7,
},
{
id: 'gtm-timeline',
keywords: ['timeline', 'zeitplan', 'schedule', 'wann', 'when', 'roadmap', 'meilensteine', 'milestones'],
question_de: 'Wann kommen die ersten Kunden?',
question_en: 'When will the first customers come?',
answer_de: 'Die Plattform ist produktionsreif. Nach der Pre-Seed Runde starten wir sofort mit Pilotprojekten. Ziel: 5 zahlende Pilotkunden innerhalb von 6 Monaten, 20 Kunden nach 12 Monaten.',
answer_en: 'The platform is production-ready. After the pre-seed round we start pilot projects immediately. Target: 5 paying pilot customers within 6 months, 20 customers after 12 months.',
goto_slide: 'traction',
priority: 7,
},
// === PENTESTING CONVERGENCE ===
{
id: 'pentest',
keywords: ['pentesting', 'penetrationstest', 'penetration test', 'security testing', 'pentests'],
question_de: 'Plant ihr auch Pentesting-Services?',
question_en: 'Do you plan pentesting services?',
answer_de: 'Ja, Pentesting ist eine natuerliche Erweiterung. Unsere Code-Security-Tools identifizieren bereits Schwachstellen — der naechste Schritt ist automatisiertes Pentesting. Der Pentesting-Markt konvergiert mit Compliance — wir sind an der Schnittstelle positioniert.',
answer_en: 'Yes, pentesting is a natural extension. Our code security tools already identify vulnerabilities — the next step is automated pentesting. The pentesting market converges with compliance — we are positioned at the intersection.',
priority: 6,
},
// === MISC ===
{
id: 'misc-demo',
keywords: ['demo', 'test', 'testen', 'try', 'ausprobieren', 'live', 'showcase'],
question_de: 'Kann ich eine Demo sehen?',
question_en: 'Can I see a demo?',
answer_de: 'Sehr gerne! Wir zeigen Ihnen die Plattform live — inklusive Code-Scanning, Compliance-Module und KI-Analyse. Kontaktieren Sie uns fuer einen Termin.',
answer_en: 'Absolutely! We will show you the platform live — including code scanning, compliance modules and AI analysis. Contact us for an appointment.',
priority: 6,
},
{
id: 'misc-contact',
keywords: ['kontakt', 'contact', 'email', 'mail', 'erreichen', 'reach', 'termin', 'meeting', 'appointment'],
question_de: 'Wie kann ich euch kontaktieren?',
question_en: 'How can I contact you?',
answer_de: 'Schreiben Sie uns eine E-Mail oder vereinbaren Sie direkt einen Termin ueber unsere Website. Wir freuen uns auf das Gespraech!',
answer_en: 'Send us an email or schedule a meeting directly through our website. We look forward to the conversation!',
priority: 5,
},
]

View File

@@ -1,463 +0,0 @@
import { SlideScript } from './types'
export const PRESENTER_SCRIPT: SlideScript[] = [
// 0 — intro-presenter (45s)
{
slideId: 'intro-presenter',
duration: 45,
paragraphs: [
{
text_de: 'Willkommen bei BreakPilot ComplAI — Compliance und Code-Security fuer den Maschinenbau.',
text_en: 'Welcome to BreakPilot ComplAI — compliance and code security for machine manufacturing.',
pause_after: 1500,
},
{
text_de: 'Ich bin Ihr KI-Praesentator und fuehre Sie durch unser Pitch Deck. Die Praesentation dauert etwa 15 Minuten.',
text_en: 'I am your AI presenter and will guide you through our pitch deck. The presentation takes about 15 minutes.',
pause_after: 1500,
},
{
text_de: 'Sie koennen jederzeit Fragen stellen — nutzen Sie einfach den Chat. Ich pausiere automatisch und antworte sofort.',
text_en: 'You can ask questions at any time — just use the chat. I will pause automatically and respond immediately.',
pause_after: 1000,
},
],
transition_hint_de: 'Lassen Sie uns beginnen.',
transition_hint_en: 'Let us begin.',
},
// 1 — cover (20s)
{
slideId: 'cover',
duration: 20,
paragraphs: [
{
text_de: 'BreakPilot ComplAI — Compliance und Code-Security auf Autopilot. Pre-Seed Runde, Q4 2026.',
text_en: 'BreakPilot ComplAI — compliance and code security on autopilot. Pre-seed round, Q4 2026.',
pause_after: 1500,
},
],
transition_hint_de: 'Schauen wir uns zunaechst das Problem an.',
transition_hint_en: 'Let us first look at the problem.',
},
// 2 — problem (60s)
{
slideId: 'problem',
duration: 60,
paragraphs: [
{
text_de: 'Maschinenbauer entwickeln immer mehr eigene Software — Firmware, Steuerungen, Predictive Maintenance. Aber wer sichert Compliance und Code-Sicherheit?',
text_en: 'Machine manufacturers develop more and more of their own software — firmware, controllers, predictive maintenance. But who ensures compliance and code security?',
pause_after: 2000,
},
{
text_de: 'Erstens: DSGVO. 4,1 Milliarden Euro Bussgelder seit 2018. Maschinenbauer verarbeiten Kundendaten, Telemetrie und Wartungsprotokolle — oft ohne DSGVO-Prozesse.',
text_en: 'First: GDPR. EUR 4.1 billion in fines since 2018. Machine manufacturers process customer data, telemetry and maintenance logs — often without GDPR processes.',
pause_after: 2000,
},
{
text_de: 'Zweitens: Der AI Act. Ab August 2025 muessen Maschinen mit KI-Komponenten klassifiziert und dokumentiert werden.',
text_en: 'Second: The AI Act. From August 2025, machines with AI components must be classified and documented.',
pause_after: 2000,
},
{
text_de: 'Drittens: CRA und NIS2. Der Cyber Resilience Act verpflichtet ueber 30.000 Hersteller, Software in ihren Produkten abzusichern. Das betrifft den gesamten Maschinenbau.',
text_en: 'Third: CRA and NIS2. The Cyber Resilience Act obligates over 30,000 manufacturers to secure software in their products. This affects all of machine manufacturing.',
pause_after: 1500,
},
],
transition_hint_de: 'Und genau dafuer haben wir eine Loesung.',
transition_hint_en: 'And that is exactly what we have a solution for.',
},
// 3 — solution (75s)
{
slideId: 'solution',
duration: 75,
paragraphs: [
{
text_de: 'Unsere Loesung: ComplAI — Compliance und Code-Security auf Autopilot. Drei Saeulen machen uns einzigartig.',
text_en: 'Our solution: ComplAI — compliance and code security on autopilot. Three pillars make us unique.',
pause_after: 2000,
},
{
text_de: 'Erste Saeule: Self-Hosted Vorarbeit. Ein Mac Mini oder Mac Studio im Serverraum des Kunden scannt Code, analysiert Repositories und erstellt Compliance-Dokumente. Kein einziges Byte verlaesst das Unternehmen.',
text_en: 'First pillar: Self-hosted preprocessing. A Mac Mini or Mac Studio in the customer server room scans code, analyzes repositories and creates compliance documents. Not a single byte leaves the company.',
pause_after: 2500,
},
{
text_de: 'Zweite Saeule: Code-Security und DevSecOps. Wir scannen Firmware und Software mit integrierten Tools wie Trivy, Semgrep und Gitleaks. Das 1000-Milliarden-Parameter Cloud-LLM implementiert Fixes und schreibt Risikoanalysen.',
text_en: 'Second pillar: Code security and DevSecOps. We scan firmware and software with integrated tools like Trivy, Semgrep, and Gitleaks. The 1000-billion-parameter cloud LLM implements fixes and writes risk assessments.',
pause_after: 2500,
},
{
text_de: 'Dritte Saeule: Die Compliance-KI mit 57 Modulen. DSGVO, AI Act, CRA, NIS2, Hinweisgeberschutzgesetz — 19 Regularien, 2.274 indexierte Rechtstexte. Macht Ihr Unternehmen UND Ihre Produkte compliant.',
text_en: 'Third pillar: The compliance AI with 57 modules. GDPR, AI Act, CRA, NIS2, Whistleblower Protection Act — 19 regulations, 2,274 indexed legal texts. Makes your company AND your products compliant.',
pause_after: 1500,
},
],
transition_hint_de: 'Schauen wir uns die Produkte im Detail an.',
transition_hint_en: 'Let us look at the products in detail.',
},
// 4 — product (60s)
{
slideId: 'product',
duration: 60,
paragraphs: [
{
text_de: 'Wir bieten drei Produkt-Tiers fuer jede Unternehmensgroesse an.',
text_en: 'We offer three product tiers for every company size.',
pause_after: 1500,
},
{
text_de: 'ComplAI Starter auf dem Mac Mini fuer 1.200 Euro pro Monat. Ein 32-Milliarden-Parameter Modell — perfekt fuer KMU, die DSGVO-Compliance automatisieren wollen.',
text_en: 'ComplAI Starter on Mac Mini for EUR 1,200 per month. A 32-billion-parameter model — perfect for SMEs looking to automate GDPR compliance.',
pause_after: 2000,
},
{
text_de: 'ComplAI Professional auf dem Mac Studio fuer 2.400 Euro pro Monat mit einem 40-Milliarden-Parameter Modell. Inklusive Code-Security-Scanning und erweiterte Risikoanalyse.',
text_en: 'ComplAI Professional on Mac Studio for EUR 2,400 per month with a 40-billion-parameter model. Including code security scanning and extended risk assessment.',
pause_after: 2000,
},
{
text_de: 'Und ComplAI Enterprise — unser Flaggschiff. Self-Hosted plus BSI-zertifiziertes 1000-Milliarden-Parameter Cloud-LLM. Fuer Unternehmen, die maximale Compliance und Code-Security benoetigen.',
text_en: 'And ComplAI Enterprise — our flagship. Self-hosted plus BSI-certified 1000-billion-parameter cloud LLM. For companies needing maximum compliance and code security.',
pause_after: 1500,
},
],
transition_hint_de: 'Wie funktioniert das Ganze in der Praxis?',
transition_hint_en: 'How does this work in practice?',
},
// 5 — how-it-works (50s)
{
slideId: 'how-it-works',
duration: 50,
paragraphs: [
{
text_de: 'In vier einfachen Schritten zu Compliance und Code-Security.',
text_en: 'Compliance and code security in four simple steps.',
pause_after: 1500,
},
{
text_de: 'Schritt 1: Hardware aufstellen. Mac Mini oder Mac Studio im Serverraum anschliessen — Plug and Play, scannt ab Tag 1.',
text_en: 'Step 1: Set up hardware. Connect Mac Mini or Mac Studio in the server room — plug and play, scans from day one.',
pause_after: 1500,
},
{
text_de: 'Schritt 2: Code-Repos verbinden. Git-Repos, CI/CD Pipelines und Firmware-Projekte anbinden.',
text_en: 'Step 2: Connect code repos. Link Git repos, CI/CD pipelines and firmware projects.',
pause_after: 1500,
},
{
text_de: 'Schritt 3: Automatisierung. Laufende Code-Analyse und Risikoanalysen bei jeder Aenderung. Bei kritischen Fixes schaltet sich das Cloud-LLM zu.',
text_en: 'Step 3: Automation. Continuous code analysis and risk assessments on every change. For critical fixes, the cloud LLM steps in.',
pause_after: 1500,
},
{
text_de: 'Schritt 4: Audit bestehen. Vollstaendige Dokumentation fuer DSGVO, AI Act, CRA und NIS2 auf Knopfdruck.',
text_en: 'Step 4: Pass audits. Complete documentation for GDPR, AI Act, CRA and NIS2 at the push of a button.',
pause_after: 1000,
},
],
transition_hint_de: 'Jetzt zur Marktchance.',
transition_hint_en: 'Now to the market opportunity.',
},
// 6 — market (60s)
{
slideId: 'market',
duration: 60,
paragraphs: [
{
text_de: 'Der Markt fuer Compliance und Code-Security im Maschinenbau ist enorm.',
text_en: 'The market for compliance and code security in machine manufacturing is enormous.',
pause_after: 1500,
},
{
text_de: 'Unser Total Addressable Market liegt bei 8,7 Milliarden Euro — der globale Markt fuer Regulatory Technology waechst mit 23 Prozent pro Jahr.',
text_en: 'Our Total Addressable Market is EUR 8.7 billion — the global regulatory technology market grows at 23 percent per year.',
pause_after: 2000,
},
{
text_de: 'Der Serviceable Addressable Market in DACH: 1,2 Milliarden Euro. Das sind ueber 5.000 Maschinenbauer mit eigener Softwareentwicklung.',
text_en: 'The Serviceable Addressable Market in DACH: EUR 1.2 billion. That is over 5,000 machine manufacturers with in-house software development.',
pause_after: 2000,
},
{
text_de: 'Unser Serviceable Obtainable Market: 7,2 Millionen Euro. 500 DACH-Maschinenbauer mal 14.400 Euro pro Jahr. Das ist unser realistisches Ziel fuer die naechsten 5 Jahre.',
text_en: 'Our Serviceable Obtainable Market: EUR 7.2 million. 500 DACH machine manufacturers times EUR 14,400 per year. That is our realistic target for the next 5 years.',
pause_after: 1500,
},
],
transition_hint_de: 'Wie verdienen wir Geld?',
transition_hint_en: 'How do we make money?',
},
// 7 — business-model (45s)
{
slideId: 'business-model',
duration: 45,
paragraphs: [
{
text_de: 'Unser Geschaeftsmodell: Recurring Revenue mit Hardware-Moat.',
text_en: 'Our business model: Recurring revenue with hardware moat.',
pause_after: 1500,
},
{
text_de: 'Die Hardware-Appliance im Serverraum des Kunden schafft einen natuerlichen Lock-in. Monatliche Subscriptions von 1.200 bis 3.600 Euro garantieren planbare Einnahmen.',
text_en: 'The hardware appliance in the customer server room creates a natural lock-in. Monthly subscriptions from EUR 1,200 to 3,600 ensure predictable revenue.',
pause_after: 2000,
},
{
text_de: 'Die Unit Economics sind ueberzeugend: Hardware-Kosten amortisieren sich in wenigen Monaten, und die Bruttomarge liegt bei ueber 70 Prozent.',
text_en: 'The unit economics are compelling: hardware costs amortize in a few months, and gross margin exceeds 70 percent.',
pause_after: 1500,
},
],
transition_hint_de: 'Was haben wir bisher erreicht?',
transition_hint_en: 'What have we achieved so far?',
},
// 8 — traction (45s)
{
slideId: 'traction',
duration: 45,
paragraphs: [
{
text_de: 'Unsere bisherige Traction und Meilensteine.',
text_en: 'Our traction and milestones so far.',
pause_after: 1500,
},
{
text_de: '761.000 Zeilen Code geschrieben. 45 Container in Produktion. 57 Compliance-Module implementiert. 2.274 Rechtstexte indexiert und durchsuchbar.',
text_en: '761,000 lines of code written. 45 containers in production. 57 compliance modules implemented. 2,274 legal texts indexed and searchable.',
pause_after: 2000,
},
{
text_de: 'Die komplette Plattform ist funktionsfaehig — wir sind bereit fuer die ersten zahlenden Kunden.',
text_en: 'The complete platform is functional — we are ready for our first paying customers.',
pause_after: 1500,
},
],
transition_hint_de: 'Wie stehen wir im Vergleich zum Wettbewerb?',
transition_hint_en: 'How do we compare to the competition?',
},
// 9 — competition (60s)
{
slideId: 'competition',
duration: 60,
paragraphs: [
{
text_de: 'Der Wettbewerb: 44 Features, 9 USPs — kein Anbieter kombiniert DSGVO, Code-Security und Self-Hosted KI.',
text_en: 'The competition: 44 features, 9 USPs — no provider combines GDPR, code security and self-hosted AI.',
pause_after: 2000,
},
{
text_de: 'Proliance, DataGuard und heyData bieten organisatorische Compliance — aber keiner scannt Code, keiner analysiert Firmware, keiner bietet Self-Hosted KI.',
text_en: 'Proliance, DataGuard and heyData offer organizational compliance — but none scan code, none analyze firmware, none offer self-hosted AI.',
pause_after: 2500,
},
{
text_de: 'Vanta und Drata kommen aus dem US-Markt mit SOC2-Fokus. Sie verstehen weder CRA noch die spezifischen Anforderungen des deutschen Maschinenbaus.',
text_en: 'Vanta and Drata come from the US market with SOC2 focus. They understand neither CRA nor the specific requirements of German machine manufacturing.',
pause_after: 2000,
},
{
text_de: 'Unser Alleinstellungsmerkmal: Wir machen nicht nur das Unternehmen compliant, sondern auch die Produkte. Das ist der entscheidende Unterschied.',
text_en: 'Our unique selling proposition: We make not only the company compliant, but also the products. That is the decisive difference.',
pause_after: 1500,
},
],
transition_hint_de: 'Lernen Sie unser Team kennen.',
transition_hint_en: 'Meet our team.',
},
// 10 — team (30s)
{
slideId: 'team',
duration: 30,
paragraphs: [
{
text_de: 'Unser Gruenderteam vereint tiefe Domain-Expertise in Compliance, Software-Architektur und KI.',
text_en: 'Our founding team combines deep domain expertise in compliance, software architecture and AI.',
pause_after: 2000,
},
{
text_de: 'Wir kennen die Schmerzen der Branche aus erster Hand und haben die technische Kompetenz, sie zu loesen.',
text_en: 'We know the pain points of the industry firsthand and have the technical competence to solve them.',
pause_after: 1500,
},
],
transition_hint_de: 'Schauen wir uns die Finanzprognosen an.',
transition_hint_en: 'Let us look at the financial projections.',
},
// 11 — financials (45s)
{
slideId: 'financials',
duration: 45,
paragraphs: [
{
text_de: 'Unsere Finanzprognose basiert auf einer AI-First Kostenstruktur — das heisst: 10x Kunden bedeutet nicht 10x Personal.',
text_en: 'Our financial projection is based on an AI-first cost structure — meaning: 10x customers does not mean 10x headcount.',
pause_after: 2000,
},
{
text_de: 'Von 36.000 Euro Umsatz in 2026 auf 8,4 Millionen Euro in 2030. Das Team waechst dabei nur von 2 auf 18 Personen. 380 Kunden bei 5,5 Millionen Euro ARR.',
text_en: 'From EUR 36,000 revenue in 2026 to EUR 8.4 million in 2030. The team grows from just 2 to 18 people. 380 customers at EUR 5.5 million ARR.',
pause_after: 2000,
},
{
text_de: 'Break-Even erreichen wir voraussichtlich Ende 2028. Die Burn Rate bleibt dank Self-Hosted Architektur und Apple-Silicon Effizienz niedrig.',
text_en: 'We expect to reach break-even by end of 2028. The burn rate stays low thanks to self-hosted architecture and Apple Silicon efficiency.',
pause_after: 1500,
},
],
transition_hint_de: 'Und damit kommen wir zum Ask.',
transition_hint_en: 'And that brings us to the ask.',
},
// 12 — the-ask (45s)
{
slideId: 'the-ask',
duration: 45,
paragraphs: [
{
text_de: 'Wir suchen eine Pre-Seed Finanzierung fuer den Go-to-Market.',
text_en: 'We are seeking pre-seed funding for go-to-market.',
pause_after: 1500,
},
{
text_de: 'Das Investment fliesst in vier Bereiche: Engineering fuer die Produktreife, Vertrieb fuer die ersten Pilotkunden, Hardware-Bestand fuer schnelle Auslieferung, und eine Reserve fuer regulatorische Anforderungen.',
text_en: 'The investment flows into four areas: Engineering for product maturity, sales for first pilot customers, hardware inventory for fast delivery, and a reserve for regulatory requirements.',
pause_after: 2500,
},
{
text_de: 'Mit diesem Kapital erreichen wir die ersten 20 zahlenden Kunden und beweisen Product-Market-Fit im deutschen Maschinenbau.',
text_en: 'With this capital we reach our first 20 paying customers and prove product-market fit in German machine manufacturing.',
pause_after: 1500,
},
],
transition_hint_de: 'Haben Sie Fragen? Unser KI-Agent steht bereit.',
transition_hint_en: 'Have questions? Our AI agent is ready.',
},
// 13 — ai-qa (30s)
{
slideId: 'ai-qa',
duration: 30,
paragraphs: [
{
text_de: 'Auf dieser Slide koennen Sie direkt mit unserem KI-Agent interagieren. Stellen Sie Ihre Investorenfragen — der Agent antwortet mit Echtdaten aus unserer Datenbank.',
text_en: 'On this slide you can interact directly with our AI agent. Ask your investor questions — the agent responds with real data from our database.',
pause_after: 2000,
},
{
text_de: 'Nutzen Sie den Chat rechts unten oder die vorgeschlagenen Fragen.',
text_en: 'Use the chat in the bottom right or the suggested questions.',
pause_after: 1500,
},
],
transition_hint_de: 'Im Anhang finden Sie weitere Details.',
transition_hint_en: 'You will find further details in the appendix.',
},
// 14 — annex-assumptions (35s)
{
slideId: 'annex-assumptions',
duration: 35,
paragraphs: [
{
text_de: 'Im Anhang: Unsere Annahmen und Sensitivitaetsanalyse. Drei Szenarien — konservativ, base case und optimistisch — fuer robuste Planung.',
text_en: 'In the appendix: Our assumptions and sensitivity analysis. Three scenarios — conservative, base case and optimistic — for robust planning.',
pause_after: 2000,
},
{
text_de: 'Alle Finanzprognosen basieren auf validierten Marktdaten und realistischen Wachstumsannahmen.',
text_en: 'All financial projections are based on validated market data and realistic growth assumptions.',
pause_after: 1500,
},
],
},
// 15 — annex-architecture (35s)
{
slideId: 'annex-architecture',
duration: 35,
paragraphs: [
{
text_de: 'Die technische Architektur: Self-Hosted KI-Stack fuer maximale Datensouveraenitaet. Alle Daten bleiben on-premise, nur anonymisierte Anfragen gehen an die BSI-zertifizierte Cloud.',
text_en: 'The technical architecture: Self-hosted AI stack for maximum data sovereignty. All data stays on-premise, only anonymized queries go to the BSI-certified cloud.',
pause_after: 2000,
},
],
},
// 16 — annex-gtm (35s)
{
slideId: 'annex-gtm',
duration: 35,
paragraphs: [
{
text_de: 'Unsere Go-to-Market Strategie: Vom Pilotprojekt zum skalierbaren Vertrieb. Wir starten mit VDMA-Mitgliedern und skalieren ueber Partnerschaften mit Systemhaeusern.',
text_en: 'Our go-to-market strategy: From pilot project to scalable sales. We start with VDMA members and scale through partnerships with system integrators.',
pause_after: 2000,
},
],
},
// 17 — annex-regulatory (35s)
{
slideId: 'annex-regulatory',
duration: 35,
paragraphs: [
{
text_de: 'Die vier Saeulen der EU-Compliance fuer Maschinenbauer: DSGVO, AI Act, Cyber Resilience Act und NIS2. Alle vier Regularien zusammen erzeugen einen massiven Compliance-Druck — und genau hier setzen wir an.',
text_en: 'The four pillars of EU compliance for machine manufacturers: GDPR, AI Act, Cyber Resilience Act and NIS2. All four regulations together create massive compliance pressure — and that is exactly where we come in.',
pause_after: 2000,
},
],
},
// 18 — annex-engineering (35s)
{
slideId: 'annex-engineering',
duration: 35,
paragraphs: [
{
text_de: 'Engineering Deep Dive: 761.000 Zeilen Code, 45 Container, 100 Prozent Self-Hosted. Unsere Plattform ist produktionsreif und skalierbar.',
text_en: 'Engineering deep dive: 761,000 lines of code, 45 containers, 100 percent self-hosted. Our platform is production-ready and scalable.',
pause_after: 2000,
},
],
},
// 19 — annex-aipipeline (35s)
{
slideId: 'annex-aipipeline',
duration: 35,
paragraphs: [
{
text_de: 'Die KI-Pipeline im Detail: RAG, Multi-Agent-System, Document Intelligence und Quality Assurance. Vielen Dank fuer Ihre Aufmerksamkeit — ich stehe fuer weitere Fragen bereit.',
text_en: 'The AI pipeline in detail: RAG, multi-agent system, document intelligence and quality assurance. Thank you for your attention — I am available for further questions.',
pause_after: 2000,
},
],
},
]
export function getScriptForSlide(slideId: string): SlideScript | undefined {
return PRESENTER_SCRIPT.find(s => s.slideId === slideId)
}
export function getScriptByIndex(index: number): SlideScript | undefined {
return PRESENTER_SCRIPT[index]
}
export function getTotalDuration(): number {
return PRESENTER_SCRIPT.reduce((sum, s) => sum + s.duration, 0)
}

View File

@@ -1,20 +0,0 @@
import { Language } from '../types'
/**
* TTS Stub — prepared for future Piper TTS integration via compliance-tts-service (:8095)
* POST /synthesize { text, voice: 'de_DE-thorsten-high' }
* Returns audio URL from MinIO
*/
export async function synthesizeSpeech(text: string, lang: Language): Promise<string | null> {
// TODO: Connect to compliance-tts-service
// const voice = lang === 'de' ? 'de_DE-thorsten-high' : 'en_US-lessac-high'
// const res = await fetch('http://compliance-tts-service:8095/synthesize', {
// method: 'POST',
// headers: { 'Content-Type': 'application/json' },
// body: JSON.stringify({ text, voice }),
// })
// if (!res.ok) return null
// const data = await res.json()
// return data.audio_url
return null
}

View File

@@ -1,40 +0,0 @@
import { Language, SlideId } from '../types'
export type PresenterState = 'idle' | 'presenting' | 'paused' | 'answering' | 'resuming'
export interface PresenterConfig {
autoAdvance: boolean
speechRate: number
pauseBetweenSlides: number
language: Language
}
export interface SlideScript {
slideId: SlideId
duration: number
paragraphs: {
text_de: string
text_en: string
pause_after: number
}[]
transition_hint_de?: string
transition_hint_en?: string
}
export interface FAQEntry {
id: string
keywords: string[]
question_de: string
question_en: string
answer_de: string
answer_en: string
goto_slide?: SlideId
priority: number
}
export const DEFAULT_PRESENTER_CONFIG: PresenterConfig = {
autoAdvance: true,
speechRate: 1.0,
pauseBetweenSlides: 2000,
language: 'de',
}

View File

@@ -222,7 +222,6 @@ export interface ChatMessage {
}
export type SlideId =
| 'intro-presenter'
| 'cover'
| 'problem'
| 'solution'