QGO UK is an ambitious tech start-up based in Colchester, Essex. Our tight-knit team draws on expertise from a range of backgrounds, including the technology and transport sectors.
We have been drawn together by a shared passion for finding innovative ways to use technology to make a positive difference. QGO Logistics is born of our belief in the value of green tech and in using data-driven intelligence to make services more efficient and effective.
We set ourselves the task of solving a decades-old problem in the logistics and transportation sectors – the under-utilisation of vehicles.
Take taxis, for example. Typical utilisation for a driver who owns their own vehicle is around 10%. They might only be driving 30 hours worth of fares a week. If the car is not full with passengers and their belongings on every fare, that means there is space going free that could be used for other fares or for transporting goods.
There is no business sense in allowing 90% of the value of an available asset to go unused. With transport, it also means there are more vehicles on the road making more journeys than are necessary.
Digital Problem Solvers
Our solution relies partly on technology, partly on thinking outside the box. First of all, why should space in a taxi driver’s car go unused so often? Replacing single fares with a rideshare model helps, but we wanted to go even further. Drivers can get even more out of their vehicles if they are also taking on other types of job, such as courier services and food delivery.
Second, how can you coordinate drivers taking on more than one job at once so it maximises utilisation while still guaranteeing a high quality, efficient service? This is where our expertise in digital technology comes to the fore. Using Machine Learning, a form of Artificial Intelligence, our platform can triangulate a driver’s present location with pick-up points and end locations to identify who is best placed to take on a new job.
By applying this to multiple journeys at once, our platform can dynamically calculate the best solution for every new job that comes in, taking a split second to allocate a task based on considerations such as current location, on-going jobs, available space, speed, efficiency and maximum utilisation.
So what’s next?
How can we help?