Public transport app designed to plan journeys using real time data, scientific algorithms and machine learning
Our combination of scientific algorithms, real time processing of traffic situations and crowd-sourced reports allows us to predict journey durations and arrival times 200% more accurately than our competitors and local transit authorities. Data quality and accuracy is the critical component in this business and we’re not compromising on it whatsoever
A self-learning algorithm helps us to understand the local commuting experience. Machine learning works by understanding local patterns and provides unique results and preferences for different cities and different users without the need for manual data tuning
The beauty here is not only that we allow users to create any public transport related content, but also that our search algorithm filters and takes into account what’s important to them, so we can notify other fellow commuters and dynamically adjust routing. Crowd-sourcing at its best!
Martynas, the first of his name, is the King of TRAFI and protector of the realm. ‘GoT’ fan obviously, snowboarder and aviation geek. Believes he can land an A380 safely...
Few keywords to describe Jurgis: International computer science competitions, MIT, theoretical physics, PhD, CTO, string theory, squash, Belgium beer, enough?
During his spare time when Mantas is not wakeboarding, snowboarding, skydiving or riding superbikes, he heads up our business development and boy, is he the master!
Tadas is our iOS Champion: 6 times featured in App Store and has '2014 app of the year’ award under his belt. Veggie & old motorcycle racer.
Dreamed about being MC after finishing Cambridge but eventually ended up at Google. Now back-end architect at TRAFI as well as a hipster. Still can rhyme though.
Our own Simonas develops Android, robotics, drones, but mostly Android. Riding electric bike and dreaming about Tesla.