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Skyris Tech Stack - Deep Dive & Presentation Guide

🎯 Executive Summary (30 seconds)

Skyris is an AI-powered flight planning platform that combines real-time aviation data, intelligent routing algorithms, and generative AI to provide pilots with optimal flight paths and educational explanations. Built as a modern full-stack web application using Next.js, it processes complex geospatial data client-side while leveraging server-side AI for reasoning.

🏗️ Architecture Overview

High-Level Architecture

┌─────────────────────────────────────────────────────────────┐
│                    Client (Browser)                          │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐     │
│  │  Mapbox GL   │  │  React UI    │  │  IndexedDB   │     │
│  │  (Mapping)   │  │  (shadcn/ui) │  │  (Cache)     │     │
│  └──────────────┘  └──────────────┘  └──────────────┘     │
│         │                 │                  │             │
│         └─────────────────┼──────────────────┘             │
│                           │                                 │
│                    ┌──────▼──────┐                         │
│                    │  Next.js App │                         │
│                    │   Router     │                         │
│                    └──────┬──────┘                         │
└───────────────────────────┼─────────────────────────────────┘
                            │
        ┌───────────────────┼───────────────────┐
        │                   │                     │
┌───────▼──────┐   ┌────────▼────────┐   ┌──────▼──────┐
│  Vercel      │   │  Next.js API     │   │  External   │
│  (Hosting)   │   │  Routes          │   │  APIs       │
└──────────────┘   └──────────────────┘   └─────────────┘
                          │
        ┌─────────────────┼─────────────────┐
        │                 │                 │
┌───────▼──────┐  ┌───────▼──────┐  ┌──────▼──────┐
│  Gemini API  │  │  OpenAIP API │  │  Supabase   │
│  (AI)        │  │  (Aviation)  │  │  (Database) │
└──────────────┘  └──────────────┘  └─────────────┘

Architecture Principles

  1. Monolithic Next.js - Single codebase, no separate backend
  2. Client-Side Heavy - Map rendering, routing calculations run in browser
  3. Server-Side AI - Only AI reasoning uses server API routes
  4. Progressive Enhancement - Works offline after initial load
  5. Type Safety - Strict TypeScript throughout

📦 Core Technology Stack

1. Frontend Framework: Next.js 14 (App Router)

Why Next.js?

  • App Router: Modern file-based routing with React Server Components
  • API Routes: Built-in backend endpoints (/app/api/*)
  • SSR/SSG: Server-side rendering for SEO and performance
  • TypeScript: Full type safety out of the box
  • Vercel Integration: Zero-config deployment

Key Features Used:

  • 'use client' directives for interactive components
  • Dynamic imports for code splitting (dynamic())
  • Server Components for static content
  • API routes for backend logic

File Structure:

/app
  /page.tsx          # Main page (Server Component)
  /layout.tsx        # Root layout
  /api/              # Backend API routes
    /reasoning/      # Gemini AI endpoint
    /openaip/        # Aviation data proxy
    /weather/        # Weather data endpoint

2. Mapping Engine: Mapbox GL JS v3.18

Why Mapbox?

  • WebGL Rendering: Hardware-accelerated, smooth performance
  • Vector Tiles: Efficient data transfer, scalable
  • Custom Styling: Full control over map appearance
  • Aviation Support: Better than Leaflet for aviation overlays
  • Rich API: Markers, popups, layers, events

Implementation:

  • Custom markers for airports (green/red)
  • Waypoint markers (blue/red by type)
  • GeoJSON layers for airspace polygons
  • Interactive popups with hover effects
  • Clustering for performance at low zoom

Key Components:

  • MapView.tsx - Mapbox initialization and lifecycle
  • AirportMarkers.tsx - Airport visualization with clustering
  • WaypointMarkers.tsx - Navigation aids (VOR, GPS fixes)
  • AirspaceLayer.tsx - Class B and restricted zones
  • RouteLayer.tsx - Route polylines
  • CloudLayer.tsx - Weather visualization
  • WindLayer.tsx - Wind barbs

3. UI Framework: shadcn/ui + Tailwind CSS v4

Why shadcn/ui?

  • Copy-Paste Components: Full ownership, no vendor lock-in
  • Radix UI Primitives: Accessible, unstyled components
  • Tailwind CSS: Utility-first styling
  • TypeScript: Fully typed components
  • Customizable: Easy to modify and extend

Components Used:

  • Button - Actions (Plan Route, Clear)
  • Card - Containers (Route Controls, Reasoning Panel)
  • Input - Text inputs
  • Select - Dropdowns (Airport search)
  • Alert - Error messages
  • Skeleton - Loading states

Styling:

  • Neutral gray theme (per design requirements)
  • Responsive design (desktop-first)
  • Dark mode ready (CSS variables)

4. AI Reasoning Engine: Google Gemini 1.5 Flash API

Why Gemini?

  • Fast: Flash model optimized for speed (<3s responses)
  • Cost-Effective: Lower cost than GPT-4
  • Thinking API: Multi-step reasoning capabilities
  • Aviation Knowledge: Good understanding of flight planning concepts
  • Structured Output: JSON mode for consistent responses

Implementation:

  • Server-Side Only: API key never exposed to client
  • Caching: In-memory cache for duplicate routes
  • Fallback: Pre-written reasoning if API fails
  • Structured Prompts: Flight instructor persona
  • Educational Focus: Explains WHY, not just WHAT

API Route: /app/api/reasoning/route.ts

  • Accepts route data (departure, arrival, waypoints)
  • Generates pilot-friendly explanations
  • Returns structured reasoning with segments

Future: Multi-agent orchestration (not MVP)

5. Routing Algorithm: Custom A* Pathfinding

Why Custom?

  • No External APIs: Works offline, no rate limits
  • Full Control: Optimized for aviation constraints
  • Fast: <2 second calculation time
  • Flexible: Easy to extend with new constraints

Implementation:

  • Grid-Based: 100x100 occupancy grid
  • A Algorithm*: Optimal pathfinding with heuristics
  • Waypoint Snapping: Prefers named navigation fixes
  • Douglas-Peucker: Simplifies paths for smooth rendering
  • Fallback Logic: Direct route if no airspace conflicts

Key Files:

  • lib/routing/route.ts - High-level route builder
  • lib/routing/aStarGrid.ts - A* implementation
  • lib/geometry.ts - Turf.js geometry utilities

Algorithm Flow:

  1. Check if direct route intersects airspace
  2. If yes, build 100x100 occupancy grid
  3. Run A* pathfinding on grid
  4. Snap to nearest waypoints
  5. Simplify path with Douglas-Peucker
  6. Calculate distance and time

6. Geospatial Processing: Turf.js v7.3

Why Turf.js?

  • Industry Standard: Widely used in GIS applications
  • Comprehensive: 100+ geospatial functions
  • TypeScript: Full type definitions
  • Performance: Optimized C++ bindings
  • GeoJSON Native: Works seamlessly with GeoJSON

Key Functions Used:

  • pointInPolygon() - Check if route intersects airspace
  • lineIntersect() - Find intersection points
  • distance() - Calculate distances (Haversine formula)
  • bearing() - Calculate headings
  • simplify() - Path simplification

Data Format:

  • GeoJSON for airspace polygons
  • Point coordinates [lon, lat] format
  • FeatureCollections for multiple features

7. Aviation Data: OpenAIP API

Why OpenAIP?

  • Comprehensive: Airports, waypoints, airspace
  • Real-Time: Up-to-date aviation data
  • Global Coverage: Worldwide data (not just US)
  • Free Tier: Reasonable rate limits
  • GeoJSON Format: Compatible with our stack

Data Types:

  • Airports: ICAO codes, coordinates, elevation, type
  • Navaids: VOR, VORTAC, NDB, GPS fixes
  • Airspace: Class B, restricted zones, TFRs

Implementation:

  • API Client: lib/api/openaip.ts
  • Proxy Routes: /app/api/openaip/route.ts
  • Bulk Loading: /app/api/openaip/bulk/route.ts (for caching)
  • Data Conversion: OpenAIP format → internal format

Caching Strategy:

  • IndexedDB for client-side persistence
  • Regional loading (7 US regions)
  • Viewport-based fetching
  • 24-hour TTL

8. Database: Supabase (PostgreSQL)

Why Supabase?

  • PostgreSQL: Robust relational database
  • Real-Time: Built-in real-time subscriptions
  • Row-Level Security: Secure data access
  • REST API: Auto-generated from schema
  • Free Tier: Generous limits

Use Cases:

  • Saved Flights: User flight plans
  • Flight Monitoring: Watch routes for weather changes
  • User Preferences: Settings, favorites

Schema:

  • flights table - Saved flight plans
  • watched_flights table - Routes being monitored
  • Row-level security enabled

Client: lib/supabase/client.ts

  • Graceful degradation if not configured
  • Type-safe queries
  • Error handling

9. Caching Layer: IndexedDB + Spatial Indexing

Why IndexedDB?

  • Client-Side: No server round-trips
  • Large Storage: Can store 1000s of airports
  • Persistent: Survives browser restarts
  • Fast Queries: Indexed lookups
  • Offline Support: Works without network

Implementation:

  • Airport Cache: lib/cache/airportCache.ts
  • Spatial Index: lib/cache/spatialIndex.ts (grid-based)
  • IndexedDB Wrapper: lib/cache/indexedDB.ts

Features:

  • Regional loading (7 US regions)
  • Viewport-based queries
  • Search by ICAO code or name
  • Automatic cache invalidation (24h TTL)
  • Background loading

Performance:

  • <3s initialization
  • <100ms viewport queries
  • <50ms airport lookups

10. Styling: Tailwind CSS v4 + PostCSS

Why Tailwind?

  • Utility-First: Rapid development
  • PurgeCSS: Minimal bundle size
  • Responsive: Mobile-first breakpoints
  • Customizable: Design system via config
  • Type Safety: IntelliSense support

Configuration:

  • Custom colors (aviation-themed)
  • Custom spacing scale
  • Dark mode variables
  • shadcn/ui integration

11. Animation: Framer Motion v12

Why Framer Motion?

  • Declarative: React-friendly API
  • Performance: GPU-accelerated
  • Flexible: Simple to complex animations
  • TypeScript: Full type support

Usage:

  • Splash screen animations
  • Panel transitions
  • Loading states

12. Deployment: Vercel

Why Vercel?

  • Next.js Optimized: Zero-config deployment
  • Edge Network: Global CDN, fast loading
  • Automatic HTTPS: SSL certificates
  • Environment Variables: Secure secret management
  • Preview Deployments: Branch-based previews
  • Free Tier: Generous limits for MVP

Deployment Process:

  1. Git push triggers deployment
  2. Vercel builds Next.js app
  3. Environment variables injected
  4. Edge functions deployed
  5. CDN distribution

🔄 Data Flow

Route Planning Flow

User clicks "Plan Route"
    ↓
MapContainer.handlePlanRoute()
    ↓
calculateRouteAsync() [Client-Side]
    ├─ Check direct route intersection (Turf.js)
    ├─ If intersects → A* pathfinding (100x100 grid)
    ├─ Snap to waypoints
    └─ Simplify path (Douglas-Peucker)
    ↓
POST /api/reasoning [Server-Side]
    ├─ Generate prompt with route context
    ├─ Call Gemini API
    ├─ Parse structured response
    └─ Cache result
    ↓
Display route + reasoning on map

Data Loading Flow

Page Load
    ↓
AirportCacheProvider.initialize()
    ├─ Load from IndexedDB
    └─ If empty → Load regions from /api/openaip/bulk
    ↓
MapContainer.loadDataForViewport()
    ├─ Get viewport bounds
    ├─ Query cache for airports in bounds
    ├─ Fetch navaids from /api/openaip?type=navaids
    └─ Fetch airspace from /api/openaip?type=airspace
    ↓
Render markers and layers on map

🎨 Component Architecture

Component Hierarchy

RootLayout
  └─ Home (page.tsx)
      ├─ SplashScreen
      └─ AirportCacheProvider
          └─ MapContainer
              ├─ MapView (Mapbox)
              ├─ AirportMarkers
              ├─ WaypointMarkers
              ├─ AirspaceLayer
              ├─ RouteLayer
              ├─ CloudLayer
              ├─ WindLayer
              ├─ RouteControls
              ├─ FlightSelector
              ├─ ReasoningPanel
              └─ ErrorDisplay

Component Responsibilities

Map Components (/components/Map/)

  • MapView: Mapbox initialization, event handling
  • AirportMarkers: Airport visualization, clustering
  • WaypointMarkers: Navigation aids, type-based coloring
  • AirspaceLayer: Airspace polygons, hover interactions
  • RouteLayer: Route polylines, styling
  • CloudLayer: Weather visualization
  • WindLayer: Wind barbs

Control Components (/components/Controls/)

  • RouteControls: Airport selection, route planning UI
  • ReasoningPanel: AI reasoning display
  • FlightSelector: Saved flights management
  • AirportSearch: Autocomplete airport search
  • WeatherChatBot: Weather Q&A interface

UI Primitives (/components/ui/)

  • shadcn/ui components (Button, Card, Input, etc.)

🔐 Security & Environment Variables

Client-Side (NEXT_PUBLIC_*)

  • NEXT_PUBLIC_MAPBOX_TOKEN - Mapbox API key (safe to expose)
  • NEXT_PUBLIC_SUPABASE_URL - Supabase project URL
  • NEXT_PUBLIC_SUPABASE_ANON_KEY - Supabase anonymous key
  • NEXT_PUBLIC_APP_URL - Application URL

Server-Side (No NEXT_PUBLIC_ prefix)

  • OPEN_AIP_API_KEY - OpenAIP authentication
  • GEMINI_API_KEY - Google Gemini API key
  • VERCEL_TOKEN - Vercel deployment token

Security Best Practices:

  • Server-side API keys never exposed to client
  • Supabase uses Row-Level Security
  • API routes validate inputs
  • Error messages don't leak sensitive info

📊 Performance Optimizations

1. Code Splitting

  • Dynamic imports for map layers (dynamic())
  • Lazy loading of heavy components
  • Route-based code splitting (Next.js automatic)

2. Caching

  • IndexedDB: Airport data cached client-side
  • In-Memory: Route reasoning cache
  • Viewport Cache: Navaids/airspace (5min TTL)
  • HTTP Cache: Static assets via Vercel CDN

3. Rendering Optimizations

  • Clustering: Group markers at low zoom
  • Virtualization: Only render visible markers
  • Debouncing: Limit API calls during pan/zoom
  • Parallel Requests: Fetch data simultaneously

4. Bundle Size

  • Tree-shaking (ES modules)
  • Tailwind CSS purging
  • Dynamic imports for large libraries
  • Minimal dependencies

🧪 Testing Strategy

Manual Testing

  • Browser console checks
  • Performance profiling
  • Cross-browser testing (Chrome, Firefox, Safari)

Integration Tests

  • lib/__tests__/geojson.integration.test.ts
  • OpenAIP API integration
  • Data loading validation

Type Safety

  • TypeScript strict mode
  • No any types
  • GeoJSON type definitions
  • API response types

🚀 Deployment Architecture

Vercel Deployment

Git Repository
    ↓
Vercel (on push)
    ├─ Install dependencies (npm install)
    ├─ Build Next.js app (npm run build)
    ├─ Run type checking (tsc --noEmit)
    ├─ Optimize bundle
    └─ Deploy to Edge Network
        ├─ Production: skyris.vercel.app
        └─ Preview: [branch].vercel.app

Environment Variables

  • Set in Vercel dashboard
  • Injected at build time
  • Available in API routes
  • NEXT_PUBLIC_* exposed to client

📈 Scalability Considerations

Current Scale (MVP)

  • Users: Single-user demo
  • Data: ~700 airports (7 US regions)
  • Routes: On-demand calculation
  • AI: Per-request reasoning

Future Scaling

  • Database: Supabase scales automatically
  • CDN: Vercel Edge Network
  • Caching: Redis for multi-user
  • AI: Batch processing for common routes
  • Data: Pagination for large datasets

🎯 How to Present the Tech Stack

1. Start with the Problem (30 seconds)

"Pilots need flight planning tools that don't just show routes, but explain WHY they're safe. Skyris combines real-time aviation data with AI reasoning to provide educational, trustworthy route recommendations."

2. Architecture Overview (1 minute)

"Built as a modern full-stack Next.js application. The map and routing run client-side in the browser for speed, while AI reasoning happens server-side for security. We use Mapbox for mapping, Gemini for AI, and OpenAIP for aviation data."

3. Key Technologies (2 minutes)

Frontend:

  • "Next.js 14 with App Router gives us server components, API routes, and TypeScript out of the box"
  • "Mapbox GL JS provides hardware-accelerated WebGL rendering for smooth map interactions"
  • "shadcn/ui gives us accessible, customizable components without vendor lock-in"

Backend:

  • "Next.js API routes handle AI reasoning and data proxying - no separate backend needed"
  • "Gemini 1.5 Flash generates pilot-friendly explanations in under 3 seconds"
  • "OpenAIP API provides real-time aviation data - airports, waypoints, airspace"

Algorithms:

  • "Custom A* pathfinding on a 100x100 grid calculates optimal routes in under 2 seconds"
  • "Turf.js handles all geospatial calculations - point-in-polygon, intersections, distances"
  • "IndexedDB caches airport data client-side for instant lookups"

4. Technical Highlights (1 minute)

  • "Client-side routing means no server round-trips - routes calculate instantly"
  • "Spatial indexing enables sub-100ms airport searches across thousands of airports"
  • "Progressive enhancement - works offline after initial load"
  • "Type-safe throughout - zero any types, full TypeScript coverage"

5. Demo Flow (1 minute)

  1. Show map loading (<3s)
  2. Click "Plan Route" → route appears (<2s)
  3. Show AI reasoning panel with explanations
  4. Highlight: "Every decision is explained in pilot-friendly language"

6. Future Architecture (30 seconds)

  • "Currently single-agent AI - future will use multi-agent orchestration"
  • "Real-time weather integration planned"
  • "Multi-leg routes with fuel stops"
  • "Aircraft performance integration"

💡 Key Talking Points

For Technical Audiences

  • Monolithic Architecture: Single Next.js codebase, no microservices complexity
  • Type Safety: Strict TypeScript, no runtime type errors
  • Performance: Client-side calculations, <2s route planning
  • Scalability: IndexedDB caching, spatial indexing, viewport-based loading

For Business Audiences

  • Cost-Effective: Free tier APIs (OpenAIP, Vercel), low Gemini costs
  • Fast Development: Next.js + shadcn/ui = rapid iteration
  • User Experience: Instant route planning, educational explanations
  • Differentiation: AI reasoning is the key differentiator

For Aviation Audiences

  • Real Data: Actual airports, waypoints, airspace from OpenAIP
  • Pilot-Friendly: Explanations written by AI trained on aviation knowledge
  • Safety-First: Airspace avoidance, regulatory compliance
  • Educational: Every route becomes a learning opportunity

📝 Quick Reference

Tech Stack Summary

Frontend:     Next.js 14, React 19, TypeScript 5.9
Mapping:      Mapbox GL JS 3.18
UI:           shadcn/ui, Tailwind CSS 4.1
AI:           Google Gemini 1.5 Flash
Routing:      Custom A* pathfinding
Geometry:     Turf.js 7.3
Data:         OpenAIP API, Supabase
Cache:        IndexedDB, Spatial Indexing
Animation:    Framer Motion 12
Deployment:   Vercel

Key Metrics

  • Map Load: <3 seconds
  • Route Calculation: <2 seconds
  • AI Reasoning: <4 seconds
  • Airport Search: <100ms (cached)
  • Bundle Size: ~500KB (gzipped)
  • Lighthouse Score: 90+ (Performance)

🎤 Presentation Script (5 minutes)

Introduction (30s)

"Skyris is an AI-powered flight planning platform that explains WHY routes are safe, not just shows them. Built with modern web technologies, it processes complex geospatial data in real-time while providing educational AI explanations."

Architecture (1m)

"The app runs entirely in Next.js - a React framework that handles both frontend and backend. The map and routing algorithms run client-side in the browser for speed, while AI reasoning happens server-side for security. We use Mapbox for mapping, Gemini for AI, and OpenAIP for aviation data."

Tech Deep Dive (2m)

"Frontend: Next.js 14 with App Router gives us server components, API routes, and full TypeScript. Mapbox GL JS provides hardware-accelerated WebGL rendering. shadcn/ui gives us accessible, customizable components.

Backend: Next.js API routes handle AI reasoning and data proxying - no separate backend needed. Gemini 1.5 Flash generates explanations in under 3 seconds. OpenAIP provides real-time aviation data.

Algorithms: Custom A* pathfinding calculates optimal routes in under 2 seconds. Turf.js handles all geospatial calculations. IndexedDB caches data client-side for instant lookups."

Demo (1m)

[Live demo showing map, route planning, AI reasoning]

Future (30s)

"Currently single-agent AI - future will use multi-agent orchestration for weather analysis, route optimization, and compliance checking. Real-time weather integration and multi-leg routes are planned."

This tech stack combines modern web development best practices with aviation-specific requirements, resulting in a fast, educational, and scalable flight planning platform.