Made by Team Escaped Characters

The Team

Imran Hussain

Imran, from Birmingham, has a background in biology and…

previously worked as a logistics coordinator for five years before transitioning into software development. He enjoys problem-solving and building practical solutions that make a difference. Outside of tech, Imran is passionate about family, financial markets, chess, and DIY projects. He values continuous learning, exploring new ideas, and finding ways to apply his skills to real-world challenges.

Alex Schubert

After five years working in fast-paced kitchens, Alex…

decided to trade his chef’s knife for a keyboard, and I hasn’t looked back since! He’s definitely the guy with the burning questions. He also holds degree in Shrekology (First-class Honours). Leeds, UK

Shams Ali

10-year career in accountancy & tax consultancy, from…

bootcamp probably back to book-keeping. Enjoy sport shooting, hockey and dessert.

Josh Faichney

Has a degree in Google Maps

Braima Djassi

A future crypto millionnaire

Nicolas Traver

Dreams to make it in Silicon Valley!

Tech Stack

We used: React, React Router, PSQL, Express.js, Supabase, Google Places API, Google Route API, Jest/Supertest, React We chose React because it allows us to build a fast, interactive, and reusable component-based UI. It also has a large ecosystem and excellent community support. React Router Used to handle navigation within the app, ensuring seamless transitions between pages without full-page reloads. Express.js A lightweight and flexible Node.js framework that makes it easy to set up API endpoints, handle requests, and interact with the database. PostgreSQL (PSQL) A powerful, relational database used to store user profiles, saved itineraries, and location-based data efficiently. Supabase Chosen for authentication (Google OAuth & email login) and database management. It provides a PostgreSQL-backed solution with built-in authentication, reducing the need for a custom auth setup. Google Places API Used to fetch location-based recommendations for attractions, restaurants, and experiences based on user preferences. Google Route API Helps optimise travel routes by calculating the most efficient way to visit selected locations. Jest / Supertest Used for unit and integration testing of the backend. Supertest ensures that our API endpoints function as expected before deployment.

Challenges Faced

Managing Authentication & User Roles Challenge: Implementing authentication with Supabase while ensuring users could log in via email/password and Google OAuth. Additionally, differentiating between tourists and tour guides in user profiles. Solution: We used Supabase Auth for authentication and stored user roles in our PostgreSQL database. This allowed us to dynamically control access to certain features based on the user’s role. Fetching and Handling Google API Data Challenge: The Google Places API provides a vast amount of data, but not all of it was structured in a way that fit our use case. Filtering relevant locations while avoiding unnecessary API calls was tricky. Solution: We set up query parameters to filter out unnecessary data, reducing API usage costs and improving performance. We also cached API responses where possible to limit redundant calls. Optimising Route Planning Challenge: The Google Route API provides multiple route options, but ensuring we optimised the order of locations efficiently without overly complex logic was a hurdle. Solution: We used the optimisation feature within the API, which calculates the most efficient order of stops, minimising travel time. Additionally, we allowed users to manually reorder stops if they preferred a different route. State Management & Navigation Challenge: Managing user-selected locations and preferences across multiple pages while ensuring a smooth user experience. Solution: Initially, we considered Redux, but it felt like overkill for this project. Instead, we used React Context API. Handling Backend & Database Queries Challenge: Querying and storing user itineraries efficiently while ensuring the database structure allowed for easy retrieval. Solution: We structured our PostgreSQL database with relational tables, ensuring indexed queries for faster lookup times. We also optimised our Supabase queries to return only necessary data, reducing backend load.