Location
Year Founded
2020
Company Size
11 - 50 People
Hiring
About Hypermile
Hypermile is on a mission to improve trucking efficiency, sustainability and safety by developing an AI driver assistance system 🚛 🌎🌱.
Today, fuel is the main cost component for logistics operators, accounting for >1/3 of all operating costs. Driving behavior is a key factor affecting overall fuel consumption and can increase fuel use by up to 35%. However, current solutions are not cost effective, so logistics operators are constantly looking for new solutions.
In addition, logistics operators are under huge sustainability pressure, as Heavy Goods Vehicles (HGVs) are responsible for 16% of the UK's transport emissions but only 5% of the miles travelled. While electric vehicle sales for passenger vehicles are on the rise, the same can't be said for long-haul HGVs due to high initial cost and limited range, making it impractical for logistic purposes.
With this problem in mind, we aim to leverage the latest AI techniques to improve the fuel efficiency of diesel trucks today, and increase the range of zero-emission trucks of the future.
Our product Hypermile Co-Pilot is a retrofittable AI cruise control for commercial vehicles focused on controlling the speed of the truck efficiently. We have trained the AI algorithms to learn the best techniques for saving fuel: anticipating how traffic flow will change, optimising speed based on the road gradient and maximizing vehicle coasting. As a result, we can reduce diesel consumption by 11% and extend the range of battery-electric vehicles by 15%. The long term vision is to incrementally build higher levels of autonomy with the next milestone being a Level-3 autonomous trucking solution.
The company was founded in May 2020 and raised a $1.5M pre-seed round in May 2021 from Y Combinator, Greg Brockman (CTO of OpenAI), Luc Vincent (former Executive VP of Autonomous Driving at Lyft Level 5) and others. We’ve received a number of R&D grants from Innovate UK, Department for Transport and Horizons 2020. We’re currently a team of 10 across Commercial, Product and Engineering (including 4. sub-teams cloud software, machine learning, automotive software and electronics).
Today, fuel is the main cost component for logistics operators, accounting for >1/3 of all operating costs. Driving behavior is a key factor affecting overall fuel consumption and can increase fuel use by up to 35%. However, current solutions are not cost effective, so logistics operators are constantly looking for new solutions.
In addition, logistics operators are under huge sustainability pressure, as Heavy Goods Vehicles (HGVs) are responsible for 16% of the UK's transport emissions but only 5% of the miles travelled. While electric vehicle sales for passenger vehicles are on the rise, the same can't be said for long-haul HGVs due to high initial cost and limited range, making it impractical for logistic purposes.
With this problem in mind, we aim to leverage the latest AI techniques to improve the fuel efficiency of diesel trucks today, and increase the range of zero-emission trucks of the future.
Our product Hypermile Co-Pilot is a retrofittable AI cruise control for commercial vehicles focused on controlling the speed of the truck efficiently. We have trained the AI algorithms to learn the best techniques for saving fuel: anticipating how traffic flow will change, optimising speed based on the road gradient and maximizing vehicle coasting. As a result, we can reduce diesel consumption by 11% and extend the range of battery-electric vehicles by 15%. The long term vision is to incrementally build higher levels of autonomy with the next milestone being a Level-3 autonomous trucking solution.
The company was founded in May 2020 and raised a $1.5M pre-seed round in May 2021 from Y Combinator, Greg Brockman (CTO of OpenAI), Luc Vincent (former Executive VP of Autonomous Driving at Lyft Level 5) and others. We’ve received a number of R&D grants from Innovate UK, Department for Transport and Horizons 2020. We’re currently a team of 10 across Commercial, Product and Engineering (including 4. sub-teams cloud software, machine learning, automotive software and electronics).
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