LumiTrip

LumiTrip is a mobile-first, AI-powered travel concierge that generates fully personalized, multilingual itineraries in seconds, eliminating hours of manual research across blogs, Google searches, and generic AI tools.

Built by a flight attendant who lives the chaos of travel planning firsthand, LumiTrip transforms fragmented planning into a single, elegant experience.

Highlights

• Personalized itineraries generated in ~10 seconds
• Multilingual support across 6 global languages
• Mobile-first PWA built for travelers on the move
• 30–45% repeat usage within 7–14 days

Quick Facts

• Industry: Travel / Consumer SaaS
• Platform: Web App + PWA
• Users: Solo travelers, couples, frequent flyers
• Services: Product strategy, UX/UI, AI integration, full-stack development

Background

Travel planning is broken.

Even experienced travelers spend hours jumping between blogs, Google searches, maps, and ChatGPT prompts, often ending with generic recommendations that don’t reflect personal preferences, timing, or budget.

The LumiTrip founder, a professional air hostess, experienced this friction daily, both personally and through conversations with travelers worldwide. She envisioned a tool that could act like a digital travel concierge: fast, personalized, multilingual, and effortless.

The goal was clear:

Deliver a complete, personalized travel itinerary in seconds, without the research overload.

The Challenge

Business Challenges

• Travelers wasted hours researching fragmented information
• Existing tools lacked true personalization
• Generic AI outputs felt repetitive and unreliable
• No fast path from inspiration to execution

Technical Challenges

• Generating structured, high-quality itineraries using GPT
• Supporting multiple languages, including RTL layouts
• Delivering fast performance on mobile devices
• Balancing AI flexibility with consistency and reliability
• Enabling regeneration without destroying user edits

UX Challenges

• Designing a mobile-first planning experience
• Presenting dense itinerary data in a scannable format
• Allowing edits without overwhelming users

The Solution

LumiTrip was designed as a single-tenant consumer SaaS with a strong focus on speed, clarity, and personalization.

Core Product Experience

Users input:

• Destination
• Travel dates
• Travel vibe (Adventure, Wellness, Culture, Romance, etc.)
• Budget tier (Luxury, Mid-range, Budget)
• Preferred language

In return, LumiTrip generates:

• A day-by-day itinerary
• Morning / Afternoon / Evening activities
• Dining and local recommendations
• Optional local events
• Fully localized language output

All within seconds.

Architecture & Technical Decisions

Tech Stack

• Frontend: React JS (mobile-first, PWA-ready)
• Backend: Node.js with Express
• Database: PostgreSQL
• AI: GPT-4 via OpenAI API
• Localization: AI-level language prompts
• Auth: JWT-based authentication

Why This Stack Worked

• PostgreSQL ensured structured, relational storage for itineraries and user data
• Node.js allowed flexible API orchestration with AI calls
• GPT-4 provided high-quality, context-aware generation when paired with strong prompt design

AI & Prompt Engineering Strategy

LumiTrip does not rely on raw AI output.

Key decisions:

• Structured prompts enforce predictable itinerary formats
• Output is generated in consistent sections (by day and time)
• Regeneration logic allows:
  • Full itinerary rewrites
  • Selective regeneration
  • Preservation of locked sections
• Language preference is injected directly into prompts
• Outputs are generated on demand, then optionally stored

This approach ensured speed without sacrificing quality.

Workflows & Automation

What previously took users hours is now automated:

• Research across multiple sources → single AI request
• Manual structuring → automated day-by-day layout
• Language translation → native AI output
• Revisions → instant regeneration

Users can:

• Edit itineraries inline
• Save favorites
• Generate shareable public links
• Revisit and regenerate plans anytime

Results & Impact

Early Adoption Metrics (early-stage live usage)

• DAU: 50–300 users/day
• MAU: 500–2,500 users/month
• Itineraries generated: ~2,000–10,000/month
• Session time: 4–8 minutes
• Repeat usage: 30–45% within 7–14 days

Business Signals

• 20–35% of itineraries lead to downstream booking intent
• Strong engagement during peak travel seasons
• Clear monetization paths via subscriptions and affiliate partnerships

User Value

• Complete itinerary in seconds
• Reduced planning fatigue
• Personalized, culturally relevant recommendations