Reimagining travel planning with AI




2 min read
Problem
Trip details are scattered across different channels, resulting in inefficient and time-consuming trip planning.
Solution
Developed an AI-powered travel app that parses travel links, auto-generates itineraries, and provides interactive map navigation, helping users plan trips faster and more efficiently.
Role
Product Designer
Contribution
Feature Scoping
UX/UI design
A/B Testing
Accessibility Design
Timeline
Jan 2025 - Present
Team
2 UX designer
1 UX researcher
1 Product Manager
3 Software Developers
Overview
Key Design Solutions
Triple is a intelligent travel-planning App featuring smart link parsing, automated itinerary generation, and interactive map-guided navigation to reduce trip planning time and increase efficency.

Designing smart link recognition
We use AI to analyze uploaded screenshots, links, or short videos and automatically extract key details like destinations and bookings. This enables users to manage all reservations and itineraries in one unified interface.
Visualizing travel destination and itinerary
Designed a flexible itinerary system that integrates location, transportation, and trip types. This gives travelers the ability to personalize their plans and manage reservations all in one place.


Adding AI-powered realtime travel suggestions
Developed an AI-driven feature that provides instant itinerary updates based on weather and trip context, helping travelers adapt their plans seamlessly and discover new opportunities.
Trip details are scattered across different channels, resulting in inefficient and time-consuming trip planning.
User research
Explore Problem Space
20+
Interviews
350+
Surveys
100+
Articles
Understanding users
Dynamic User Journey Map
My Design Process
1.Layout
2.Intercation Design
3.Design Validation
Iteration
Iteration towards Layout
Information Architecture
How to absorb content on Place Detail Page effectively?
Designed a flexible information architecture to support users’ dynamic mindset shifts across planning stages, enabling seamless transitions between creation, overview, and day views.

A/B Testing on Layout
Balancing information density vs. clarity in mobile interface
User Feedback
Users showed a clear preference for the time-segmented layout, which better supports mental organization, task anticipation, and real-time decision making.
Interaction Design
Iteration towards Interaction
Solution 1:
Prioritize displaying the map, with the itinerary fixed in a dedicated window
Solution 2:
Prioritize displaying the priority
AI Exploration
Exploration in Leveraging AI
Even with thorough planning, unexpected disruptions can ruin expectations and lead to frustration.
Opportunity 1
AI Travel Tips
I designed the AI-generated Travel Tips module to proactively surface context-aware recommendations, combining:
Location-specific advice(e.g., NY tap water is cold, dry air in March)
Seasonal considerations(e.g., layering in winter)
User intent recognition(e.g., camera gear for content creators)
Packing psychology(essentials vs bonus)
Instead of giving generic tips, we deliver personalized and purposeful suggestions that align with user mindset: “What will I actually need there?”


Opportunity 2
Adaptive Planning: Weather-Aware Itinerary Updates
AI + crowd insights (“80% of users recommend this”) builds trust
Minimal interruption via one-screen, two-option UI
Flexible control — no forced changes, user decides
Map-based visualization grounds the recommendation in real context

Impact
Design Validation
Iteration towards Feasibility
Evaluating concepts
Technical constraint: Balance performance & cost constraints
Infinite scroll caused performance issues and high backend costs due to frequent API calls under real-time data.
We replaced it with a lightweight paginated view to improve stability and reduce server load.