SwissTripster: The Travel Planning Revolution
How we solved complex travel planning with AI and multi-platform delivery
The Travel Planning Problem
Planning day trips in Switzerland involves coordinating multiple complex factors: real-time train schedules, weather conditions, attraction hours, and personal preferences. Traditional solutions required users to juggle multiple apps and websites.
"I spent more time planning our day trip to Lucerne than actually enjoying it. Checking SBB, weather, restaurant reviews... it was exhausting!"- Tourist from Germany
Platform & Integration Challenges
Why traditional app development failed for travel planning
The Multi-Platform Dilemma
We faced three major challenges in building a comprehensive travel solution:
Platform Fragmentation
Users wanted access on web, WhatsApp, and Telegram. Building native apps for each platform was too expensive.
Real-time Data Integration
SBB APIs, weather data, and attraction hours needed real-time synchronization with complex caching strategies.
AI Understanding
Natural language processing had to understand complex travel requests with location and preference context.
Technical Roadblocks:
Multi-Platform Architecture
Unified backend with platform-specific frontends
The Triangulo Solution
We built a unified AI-powered backend that serves multiple frontend platforms, each optimized for its environment.
Any Platform
Request Routing
Request Processing
SBB + Weather
Platform Optimized
Platform-Specific Optimizations:
| Platform | Challenge | Solution | Result |
|---|---|---|---|
| Web | Rich interface needs | React + Real-time updates | Full-featured planning |
| Stateless, text-based | Quick replies + sessions | Conversational flow | |
| Telegram | Rich media support | Inline keyboards + images | Engaging experience |
Production Architecture & Code
Scalable backend with platform adapters
Core AI Planning Engine
class SwissTripsterPlanner:
def __init__(self):
self.sbb_client = SBBClient()
self.weather_client = WeatherClient()
self.ai_processor = AIClient()
async def plan_trip(self, user_request: str, use_real_schedules: bool = True):
"""
Core trip planning algorithm
Combines AI understanding with real-time data
"""
try:
# Step 1: Parse user request with AI
parsed_request = await self.ai_processor.analyze_request(user_request)
# Step 2: Get real-time data
if use_real_schedules:
schedules = await self.sbb_client.get_connections(
parsed_request.departure_city,
parsed_request.destination,
parsed_request.departure_time
)
else:
schedules = self._get_estimated_schedules(parsed_request)
# Step 3: Build optimized itinerary
itinerary = await self._build_itinerary(parsed_request, schedules)
# Step 4: Format for target platform
formatted_response = self._format_response(
itinerary,
parsed_request.platform
)
return formatted_response
except Exception as e:
logger.error(f"Trip planning failed: {e}")
return self._get_fallback_response(user_request)
class SBBClient:
def __init__(self):
self.base_url = "https://transport.opendata.ch/v1"
self.cache = RedisCache(ttl=300) # 5-minute cache
self.rate_limiter = RateLimiter(max_calls=100, period=60)
async def get_connections(self, from_city: str, to_city: str, time: datetime):
"""
Get real-time train connections with smart caching
"""
cache_key = f"sbb:{from_city}:{to_city}:{time.hour}"
# Check cache first
cached = await self.cache.get(cache_key)
if cached:
return json.loads(cached)
# Rate limit API calls
await self.rate_limiter.wait()
try:
params = {
'from': from_city,
'to': to_city,
'time': time.isoformat(),
'limit': 6
}
async with httpx.AsyncClient() as client:
response = await client.get(f"{self.base_url}/connections", params=params)
response.raise_for_status()
data = response.json()
# Cache successful responses
await self.cache.set(cache_key, json.dumps(data))
return self._parse_connections(data)
except Exception as e:
logger.error(f"SBB API error: {e}")
raise SBBServiceError("Failed to fetch train schedules")
class WhatsAppHandler:
def __init__(self, trip_planner: SwissTripsterPlanner):
self.planner = trip_planner
self.sessions = SessionManager()
async def handle_message(self, message: dict):
"""
Handle incoming WhatsApp messages
"""
user_id = message['from']
user_message = message['text']['body']
# Get or create user session
session = await self.sessions.get_session(user_id)
if user_message.lower() in ['/start', 'hello', 'hi']:
return self._get_welcome_message()
elif user_message.lower() == 'new trip':
session.state = 'awaiting_request'
await self.sessions.save_session(user_id, session)
return self._get_trip_prompt()
elif session.state == 'awaiting_request':
# Process trip planning request
try:
itinerary = await self.planner.plan_trip(
user_message,
use_real_schedules=True
)
# Format for WhatsApp (character limits, quick replies)
response = self._format_whatsapp_response(itinerary)
session.state = 'idle'
await self.sessions.save_session(user_id, session)
return response
except Exception as e:
return self._get_error_message()
else:
return self._get_help_message()
Business Impact & Multi-Platform Success
How SwissTripster demonstrates the power of strategic platform development
Measurable Business Results
73% Faster Planning
Users complete trip planning in under 2 minutes vs 45+ minutes previously
62% Chat Platform Usage
Majority of users prefer WhatsApp/Telegram over web interface
5x Development Efficiency
Single backend powers multiple platforms with 80% code reuse
🔑 Key Business Insights:
Platform Strategy Matters
Chat platforms have 3x higher engagement than traditional web apps for conversational use cases
Unified Backend Pays Off
Single AI engine serving multiple frontends reduces maintenance and speeds up feature development
Real-time Data Creates Value
Live SBB integration was the killer feature that differentiated from competitors
🔮 Multi-Platform Secrets
Chat Platform Advantage
👁️ Click to revealWhatsApp/Telegram bots have 80% lower user acquisition costs than mobile apps - users already have the platform installed!
Session Management Trick
👁️ Click to revealUse Redis with TTL for chat session management - automatically cleans up abandoned conversations after 24 hours.
Platform-Specific UX
👁️ Click to revealWhatsApp loves quick replies, Telegram prefers inline keyboards. Customize interaction patterns for each platform's strengths.
Ready to Build Your Multi-Platform Solution?
Let us help you apply these patterns to your business challenge with AI, real-time data, and strategic platform development.