Wanderlyst
AI itinerary planning and a concierge chatbot that turned browsers into booked travelers in one sitting.
Project Snapshot
- Client
- Wanderlyst Travel Group
- Industry
- Travel & Tourism
- Platform
- Web App
- Timeline
- 5 months
- Our Role
- Full-stack web development, AI integration, and UI/UX design
The Challenge
Wanderlyst Travel Group ran a booking site built the way most travel sites are: a search form up top, a wall of destination cards below, and a checkout flow bolted onto flights, stays, and tours as three separate carts. Travelers arrived with a vague idea — "somewhere warm," "food-focused," "a week in Japan" — and left the interface to do the work of turning that vibe into a real plan. Most didn't. Session data showed travelers bouncing between 15+ destination pages without ever assembling a single itinerary, and cart abandonment across the three-part checkout ran above 60%.
Their support team absorbed the gap. The same pre-booking questions — visa rules, what a "moderate" budget actually bought, whether a hotel was walkable to the sights — flooded email and chat, most of them arriving after hours when no agent was on shift. Wanderlyst needed a planning experience that did the assembly work itself, turning a destination and a vibe into a day-by-day plan without fifteen browser tabs, and it needed a concierge that could answer real questions and touch real bookings, not a support ticket queue with a chat window bolted on.
There was a trust dimension too: travelers don't hand a stranger their week off work. An AI-generated itinerary had to read like it was built by someone who actually knew Kyoto or Patagonia, with specific times, real neighborhoods, and reasoning a traveler could sanity-check — not a generic listicle with the city name swapped in.
The brief: rebuild search and discovery around an AI trip planner that outputs a bookable day-by-day itinerary in seconds, add a conversational concierge available before and during the trip, and unify flights, stays, and experiences into one checkout.
Our Solution
We rebuilt Wanderlyst as a Next.js application on top of a unified trip graph — a data model that ties destinations, lodging, experiences, and flight inventory together so a single itinerary can pull from all three instead of stitching together separate booking flows. The homepage keeps the location/dates/travelers search travelers already understand, but every query now feeds a planning layer instead of a static results grid.
The centerpiece is the AI Trip Planner: travelers set a destination, dates, budget band, and a handful of interest tags (food, culture, nature, nightlife), and the planner returns a full day-by-day itinerary — timed activities, meal suggestions, and transit notes — assembled from real bookable inventory rather than generic advice. Every plan stays editable and regenerable, and a "Save Itinerary" action carries it straight into checkout with flights, stays, and experiences already bundled.
Behind the planner sits an LLM pipeline (via the OpenAI API) grounded with retrieval over our destination content library — verified neighborhood guides, seasonal notes, and real operator inventory — so the model is composing a schedule from facts we've vetted, not inventing one. A lighter-weight ranking pass sequences activities by geography and opening hours so a generated day doesn't zigzag across a city. The same foundation powers the second AI feature, the Wanderlyst Concierge: a chat assistant available on every trip that answers visa and packing questions, rearranges bookings, and can rewrite the itinerary mid-conversation when a traveler changes a flight or adds a day.
We layered a destination detail experience on top — pricing, inclusions, and a single "Book This Trip" checkout that replaces the old three-cart flow — and gave the concierge write access to the booking system so schedule changes made in chat show up instantly in the traveler's saved itinerary, with no separate confirmation step required.
The Impact
Since launch, travelers who complete the AI Trip Planner flow convert to a booking at more than double the rate of those browsing destination pages alone, and median time from landing on the site to a saved itinerary dropped from several sessions to under four minutes. The concierge now resolves the large majority of visa, packing, and itinerary-change questions without a human agent, including a meaningful share handled outside business hours. Combined checkout adoption has cut cart abandonment sharply versus the old three-part flow. We're now scoping a group-trip planning mode and a multilingual concierge rollout for Wanderlyst's international markets.
Key Features
What We Built
AI Trip Planner
Turns a destination, budget, and interests into a bookable day-by-day itinerary in seconds.
AI Concierge Chatbot
Answers visa, weather, and packing questions and rewrites bookings directly in chat.
Unified Trip Search
One search bar spans flights, stays, and experiences instead of three separate flows.
Live Itinerary Editing
Regenerate or adjust any day of a generated plan without starting the trip over.
One-Click Trip Checkout
Flights, stays, and experiences book together in a single confirmed reservation.
Destination Detail Pages
Pricing, inclusions, and highlights for every package, ready to book on the spot.
Tech Stack
- Next.js
- Node.js
- PostgreSQL
- OPOpenAI API
- RERetrieval-Augmented Generation
- Redis
- Stripe
- GOGoogle Maps SDK
Screenshots
App in Action
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“Travelers used to leave with forty tabs open and no plan. Now they answer a few questions and get a real itinerary, timed and bookable, in under a minute — and our concierge is handling the 11pm visa questions we used to lose sleep over.”
Wanderlyst
Illustrative Example, Concept project — not an actual client engagement
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