Geovea : Dynamic AI Assistant for Tailored Travel Itineraries

Hospitality & Travel

Geovea – AI Travel Assistant for Personalized Itineraries

Geovea reimagined trip planning with our AI-powered virtual travel assistant built for dynamic itinerary generation. The system takes a user’s travel interests and automatically generates tailored destination suggestions, day-wise plans, and real-time route optimization. It includes multilingual support and adapts itineraries on the fly based on weather, traffic, or changes in availability. Our recommendation engine surfaces local gems, ideal lodging, and activity combos users often miss. From solo travelers to group adventurers, the assistant acts as a 24/7 travel concierge. Engagement and itinerary completions rose sharply after launch.

Project Overview

Client: Geovea (Smart travel planning platform catering to global users)
Challenge: Users overwhelmed with planning logistics and fragmented travel tools
Goal: Build an intelligent itinerary engine to:
- Auto-generate personalized day-wise travel plans
- Adapt recommendations in real time based on external variables
- Integrate booking, maps, and reviews into a seamless user flow
Team: 7 (3 AI Engineers, 2 Backend Devs, 1 UX Researcher, 1 QA Lead)
Timeline: 5.5 months (Prototype → Closed Beta → Public Launch)

“GenX delivered more than just a product—they built a smart travel companion. This AI is a true game-changer for dynamic itinerary planning.”

CEO, Geovea

The Challenge

Critical Pain Points:

Travelers found it difficult to convert destination ideas into actionable plans
Rigid itineraries lacked adaptability for disruptions and cancellations
Most travel apps lacked smart suggestions for lesser-known spots and local insights

Technical Hurdles:

Building dynamic, editable plans that react to live weather, traffic, and events
Personalizing routes for solo vs group vs family travelers
Integrating third-party APIs for maps, attractions, reviews, and multilingual content

Tech Stack

Component	Technologies
Recommendation Engine	XGBoost, TensorFlow, GPT-4 (API layer)
Travel Data Processing	AWS Glue, Athena, PostgreSQL
Backend Infrastructure	Node.js, GraphQL, MongoDB
Integration & APIs	Google Maps, TripAdvisor, Booking.com, WeatherStack
Multi-Language Layer	DeepL, OpenAI Translation, i18n libraries
Monitoring & Alerts	Datadog, GA4, Firebase Analytics

Key Innovations

The assistant dynamically generated day-wise plans that adapted based on traffic, weather, or cancellations. It recommended offbeat places using user preferences and real-time travel signals. This personalization increased trip completion rates and user delight.

Hyper-Personalized Day Planner

Itineraries adapted in real time to events, closures, and local weather

Result: 41% increase in completed itineraries

Local Gems Discovery Engine

Surfaced lesser-known attractions based on user interests

Result: 26% longer average session time per user

Multilingual Conversational Support

- AI offered in 9 languages with localized content hints

Result: 33% rise in engagement among non-English travelers

Our AI/ML Architecture

Core Models

Dynamic Itinerary Generator:
- Graph-based pathfinding for optimal routes by interest + constraint
- Context-aware recommendation prompts for day-part planning (morning, lunch, evening)
Traveler Persona Matching Engine:
- Classification of users into 6+ travel styles (e.g., cultural explorer, thrill-seeker)
- Adaptive filtering to match preferences with events, stays, activities
Real-Time Disruption Handler:
- LSTM + decision tree hybrid for live plan reshuffling
- Multi-lingual fallback handling with GPT-4 API support

Data Pipeline

Sources
- User travel preferences, geo-location data, past trip logs
- Connected services: Weather feeds, Google Maps, TA reviews, Booking.com
- Local tourism datasets and event calendars