Inspiration
Urban mobility today is often fragmented, inefficient especially for users navigating different transportation options. We were inspired to create a solution that simplifies how people move by combining technology, accessibility into one platform. NaikLAH aims to reduce friction in daily travel and improve the overall commuting experience for both local and international users.
What it does
NaikLAH is a smart mobility platform that helps users plan and optimize their journeys efficiently. It provides intelligent route suggestions, compares transportation options, helps users make faster, more informed travel decisions.
How we built it
We developed NaikLAH using a collaborative, agile approach during the hackathon. We designed the user interface to be simple and intuitive while implementing backend logic to process travel options and generate optimized recommendations. We combined programming, UI/UX design, and problem-solving techniques to a functional solution within a limited timeframe.
Challenges we ran into
One of the main challenges was integrating multiple ideas into a cohesive system within the hackathon time constraints. Ensuring clear communication among team members and balancing feature ambition with technical feasibility required constant adjustment. We also faced challenges related to debugging, time management quickly.
Accomplishments that we're proud of
We successfully built a working prototype that demonstrates the core concept of smarter mobility. The team collaborated effectively despite time pressure, and we managed to deliver a clear user flow and functional features.
What we learned
Through this hackathon, we learned the importance of teamwork, rapid prototyping, and prioritizing key features. We gained experience in problem-solving under pressure, adapting quickly to new ideas.
What's next for PlymHack Hackathon 2026_TeamTapau
Moving forward, we plan to enhance NaikLAH by improving scalability, integrating real-time data sources based on feedback. Future development may include AI-powered recommendations, expanded transport integrations, and stronger localization for different regions.
