Maply
A calm, AI-powered travel planning platform that transforms social inspiration and scattered notes into route-optimized, human-approved itineraries.
Understanding the Problem Space.
Nobody starts planning a trip with a blank itinerary. They start with scattered inspiration and no clear way to act on it.
The Core Problem
I've watched friends plan trips. I've watched myself plan trips. And I noticed something: nobody starts with a blank itinerary.
They start with Instagram saves, YouTube videos, a friend's recommendation, a Reddit thread, a blog post. It's messy. It's scattered. It's everywhere. And when they finally sit down to organize? They face another problem: route optimization. Traditional planners show "nearby" results as radius circles — but you don't teleport. You walk. You drive. You take trains. You follow paths, not circles.
Key Pain Points
- Inspiration is scattered across platforms
- No way to go from messy notes to a plan
- Route optimization tools use radius circles
- Generic suggestions, not personalized
The Opportunity
Build a product that starts where planning actually begins — with messy inspiration — and transforms it into something organized, optimized, and actionable. Respect how people actually plan trips.
Shaping the Solution.
Six core principles guided every decision — from the grayscale palette to the hotel-as-anchor routing logic.
Six Core Principles
Inspiration First
Start where planning begins — with messily collected ideas from anywhere.
→ Nobody opens a blank itinerary and knows what to write.
Hotel as Anchor
All routes reference where you stay, providing a central point for all travel logic.
→ Your hotel is the one constant. Everything else radiates from there.
AI Suggests, Humans Decide
Every AI extraction is editable and confirmable. No magic without user control.
→ AI should assist, not dictate. Trust comes from transparency.
Paths > Proximity
Route-based suggestions that make sense for travel, not radius circles.
→ You follow roads, not straight lines. Real travel has routes.
Calm Over Completeness
Low cognitive load experience. No cluttered dashboards.
→ Planning a trip should reduce stress, not create it.
Editability Over Magic
User control is paramount. AI helps, but the user owns the final plan.
→ Your trip, your choices. Always.
Design Philosophy: Apple Notes meets Apple Maps
After studying AI products extensively, one pattern emerged: grayscale interfaces outperform colorful ones for AI tools. When dealing with complex technology, the interface must reduce cognitive load — not add to it.
Create trip → Add places → Organize days → View itinerary
Solving the Hard Problems.
Four technical challenges that pushed beyond standard implementations — each one a lesson in pragmatic engineering.
The Stack
Frontend
- Next.js 16 (App Router)
- TypeScript
- Tailwind CSS (Zinc palette)
- shadcn/ui components
Intelligence Layer
- Google Gemini Flash
- Serper (web search)
- Hugging Face / OpenAI
- Tesseract.js (OCR)
Maps & Location
- Google Places API
- Google Directions API
- Google Maps JS API
- Haversine distance calc
Data & Files
- pdf-parse (PDF extraction)
- mammoth (DOCX parsing)
- localStorage (client state)
Place Categorization
If the name contains 'restaurant' → it's food. Failed for complex names like 'Bashundhara City Shopping Complex'.
Better but inconsistent. Different extraction methods produced different categories for the same place.
Every place validated via Google Places API. Google returns specific types (e.g. 'shopping_mall') which I map to categories. 100% accurate.
Don't reinvent the wheel. If a reliable source of truth exists, use it. Your job is to orchestrate existing systems intelligently, not rebuild them.
Route Optimization
Show places within X km of the hotel. Simple, clean — but wrong. You don't travel in circles. A place 2km away might require 15 minutes of backtracking.
Custom algorithm calculating detour costs. For any route A→B, find places within X minutes of detour. Uses Directions API with waypoints + Haversine pre-filtering.
Perfect is the enemy of good. A greedy Nearest Neighbor algorithm that runs instantly beats a perfect TSP solver that takes 30 seconds. User experience trumps algorithmic perfection.
AI Extraction from Messy Text
1. Structured Regex (fast, no API) → 2. OpenAI GPT (best quality) → 3. Hugging Face NER (free, decent) → 4. Zero-Shot Classification → 5. Regex fallback. Each layer has different trade-offs.
Build for graceful degradation. Even without API keys the system still works (just less accurately). Never let the perfect solution block the functional one.
AI-Powered Recommendations
Standard travel apps show garbage Google Places results — random office cafes, secondary schools for a romantic couple's trip. I built something different: web-scraped, AI-analyzed, context-aware recommendations.
❌ Before: Generic Results
- • "Racha Enterprise Building"
- • Random office cafes
- • Secondary schools (for couples!)
✅ After: AI Recommendations
- • Scraped from Reddit, blogs, Instagram
- • Analyzed by Google Gemini AI
- • Filtered by traveler context
- • Validated with Google Places
"Octave is consistently mentioned on Reddit r/Bangkok as the best rooftop bar for solo travelers, with stunning 360° views and a relaxed vibe perfect for meeting other travelers."
— Example AI reasoning surfaced to the user
What Makes Maply Different.
Not another travel planner. The travel planner I wished existed.
Traditional Planners
- ❌Start with blank itinerary
- ❌Manual research required
- ❌Radius-based 'nearby' search
- ❌Generic suggestions
- ❌Static plans
- ❌Feature-heavy dashboards
Maply
- ✅Start with your inspiration
- ✅AI extracts from any source
- ✅Route-aware place discovery
- ✅Context-aware AI recommendations
- ✅Dynamic re-optimization
- ✅Calm, minimal interface
In-Trip Intelligence
Planning is one thing. Executing in real-time is another. Maply doesn't just plan — it adapts.
Mark as Visited / Skipped
Visual progress bar shows completed, skipped, and remaining places.
Re-Optimize Route
Skipped a place? Route recalculates using nearest-neighbor to minimize backtracking.
Nearby Alternatives
Skipping a restaurant? Get similar places nearby instantly.
Day-by-Day Navigation
Switch between days, track progress. State persists to localStorage.
Key Takeaways
Design Meets Engineering
Building Maply proved that a designer who codes ships faster and with more intentionality. Every pixel had a reason. Every interaction was thought through.
AI as Amplifier
The multi-model AI pipeline doesn't replace human judgment — it amplifies it. Users always remain in control of the final plan.
Simplicity as Strategy
The zinc-only design wasn't a constraint — it was a deliberate choice. When the technology is complex, the interface must be calm. Users learn faster, trust sooner, stay longer.
"Inspiration first. AI assists. Humans decide."
This is the philosophy behind every feature, every design decision, every line of code.