So queried - appropriately enough - The Cars in their 1984 ballad which took on a significant change of meaning the following year. When Alex Kendall co-founded Wayve in 2017, he foresaw autonomous vehicles (AVs) with the intelligence to make their own decisions based on what they see with computer vision.
Fast-forward nearly a decade, and the start-up is pioneering an artificial intelligence (AI) led approach to AVs on a global scale, using the embodied intelligence of an end-to-end deep learning system that continually learns from driving data.
Alex Kendall describes himself as a ‘proud Kiwi’. A native of Christchurch, the third-largest city in New Zealand, Alex attended the University of Auckland.
His skills were so advanced that he directly entered the second year of Mechatronics Engineering from high school and graduated first in his class. Alongside his studies, he was elected by his peers to the board of the Auckland University Engineering Society 2011-13, and represented the university at hockey.
After graduating with those honours from engineering school, Alex completed his PhD in deep learning, computer vision and robotics at the University of Cambridge in 2017 and worked on drone algorithms at California start-up Skydio. Wayve has since attracted $65 million in investment, and Alex was featured on the Forbes 2020 30 Under 30 list.
Wayve - the R&D and business model
Wayve was founded in Cambridge in 2017 by Amar Shah and Alex Kendall, two machine learning PhD students at the University of Cambridge. Shah initially served as CEO while Kendall was CTO, and the pair set out to develop an unconventional self-driving car system using machine learning at every layer of the driving task.
It is a privately held company headquartered in London, with its primary research and development office in King’s Cross. The company was initially incorporated as Wayve Technologies Ltd in the UK. Wayve has also established a presence in Silicon Valley; and research hubs in Vancover, Canada, Yokohama, Japan, and Leonberg in Germany.
The leadership team includes research scientists and engineers with backgrounds in computer vision, robotics, and automotive systems. President Erez Dagan was hired in 2024, following two decades at Mobileye; chief scientist Jamie Shotton is formerly of Microsoft Research; CEO Alex Kendall, took over this role in 2020 after the departure of his co-founder, Amar Shah.
In May 2018, Wayve emerged from stealth mode with backing from early-stage investors. At this time, the company had around 10 employees, and its advisory investors included Uber’s Chief Scientist, Zoubin Ghahramani, who shared Wayve’s vision of a learning-centric driving AI.
In 2019, Wayve achieved a milestone by training a car to drive autonomously on public roads it had never seen before, using only cameras, a basic GPS map, and end-to-end deep learning control. The company moved its base to London and secured a $20 million Series A funding round in November 2019.
This investment enabled Wayve to launch a pilot fleet of autonomous electric vehicles in central London for real-world testing. During these trials, Wayve’s cars (such as retrofitted Jaguar I-Pace SUVs) began navigating the complex, narrow streets of London to prove the system’s ability to adapt to challenging urban scenarios.
In 2020, co-founder Amar Shah departed the company, and Alex Kendall assumed the role of CEO.
The startup joined the Microsoft for Startups: Autonomous Driving programme in 2020, leveraging Microsoft Azure’s cloud computing for training its machine learning models at scale. It is also committed to testing exclusively on electric vehicles and aims to reduce carbon emissions.
In 2021, Wayve entered pilot programmes with major UK retailers. It launched a 12-month autonomous delivery trial with supermarket chain Asda, and received a £10 million ($13.6 million) investment from online grocer Ocado Group as part of a partnership to develop self-driving grocery delivery vans. Ocado’s backing gave Wayve access to a fleet of delivery vans for data collection and testing on busy London routes to train its AI in urban traffic. At all times, human safety back-up drivers were present
In 2022, after a successful Series B funding round, the company extended road testing beyond the UK to other regions and, by 2023, to multiple countries. The company had begun operating in the United States and in continental Europe, in preparation for larger commercial deployments.
The following year, Wayve announced a collaboration with Nissan to integrate Wayve’s AI-driven software into its ProPilot ADAS system, slated to launch in 2027.
Most significantly, Wayve received strategic investment from Uber, in 2024, to jointly develop autonomous ride-hailing services. The two companies plan to trial a fully driverless robotaxi service in London, supported by a UK government programme to accelerate commercial self-driving pilots as early as this year.
To demonstrate the scalability of its technology, Wayve conducted an “AI-500” roadshow project, driving in dozens of cities across Asia, Europe, and North America using the same AI model. By mid-2025, it had completed autonomous driving demos in 90 cities without prior HD mapping.
In April 2025, Wayve opened its first Asian research hub in Japan, with investment from SoftBank, to improve the generalisation of its model using local driving data. That year, the company conducted driving tests in over 500 cities in Europe, North America and Japan without city-specific programming.
In February 2026, Nissan, Uber and Wayve announced their collaboration on robotaxi development, with the aim of launching a pilot programme in Tokyo by late 2026. Wayve also formed a ‘strategic alliance’ with Mercedes-Benz and Dutch-owned car manufacturer Stellantis on personal vehicle and robotaxi applications.
Wayve - the technical journey
January 2022 marked an important milestone for Wayve CEO Alex and his team, as the London-based start-up announced it had secured investment of $200 million in its Series B funding round to accelerate the development of AV2.0 – the next wave of AVs.
Wayve is reimagining autonomous mobility. Its AI software, lean camera-first sensing suite, and fleet learning platform for AV2.0 are designed to be the most adaptable AV system for fleet operators, one that can quickly and safely adapt to new driving domains anywhere in the world.
During his PhD in Deep Learning, Computer Vision and Robotics, under the supervision of Professor Roberto Cipolla in the Machine Intelligence Laboratory, the groundwork for what would become Wayve began to take shape.
In 2015, Alex contributed to developing a deep learning algorithm for semantic segmentation – SegNet – a practical algorithm that achieves accurate, real-time pixel-level recognition on real driving sequences. The research was published in the journal IEEE Transactions on Pattern Analysis and Machine Intelligence and is one of the journal’s and research field’s most quoted papers.
The early work that led to this paper was first funded by Toyota in 2007 and resulted in Professor Cipolla’s team building a fully labelled/annotated database (CamVid) of urban road scenes and driving videos, with each pixel in every image labelled by hand as belonging to one of 12 classes of object or background (Brostow et al; 2009).
Using this data, the Cambridge team then trained state-of-the-art machine learning algorithms to segment and label each pixel (Shotton et al., 2008; Badrinarayanan et al., 2015). In later years, Vijay Badrinarayanan and Jamie Shotton both joined Alex at Wayve as VP Autonomy (2020) and Chief Scientist (2021), respectively.
Alex Kendall and Professor Roberto Cipolla
In a blog post of 2022, Alex said: “I was fortunate enough at this time (2014-2017) to be studying computer vision and deep learning for my PhD at the University of Cambridge, with a supervisor and an environment which encouraged entrepreneurship. Our award-winning research showed for the first time that it was possible to use deep learning to teach a machine to understand where it is and what’s around it, plus crucially, understand what it doesn’t know.
“With this breakthrough technology, I imagined we could now move away from what we predicted to be the prohibitive hurdles to scale, such as HD-maps, LiDAR and rules-based autonomy, towards machines that have the intelligence to make their own decisions based on what they see with computer vision.
“Wayve began in a garage, developing a Driving Intelligence. The results were quickly promising. For the first time in the world, we showed a reinforcement learning system learning to drive a real-life autonomous vehicle from computer vision. In our first year, we demonstrated model-free and model-based reinforcement learning, driving our car, sim2real and more.
“In five quick years, we established the necessary ingredients to pioneer AV2.0: data, compute, partnerships, operations and – most importantly – our team. We’ve solved the fundamental technical challenges and earned the right to build AV2.0 at scale.”
Wayve – the Raison d’Etre
Self-driving vehicles are “the space race of my generation”, Alex Kendall told the University of Auckland in 2024. The highly respected institution is understandably proud of this one alumnus. “And will completely change society”. They’re certainly one of the great technical challenges of the age, and Alex is at the forefront of what could become a robotic revolution.
Alex and the team at Wayve are pioneering a new approach to autonomous vehicle systems called end-to-end learning. Instead of a rules-based approach that becomes increasingly more complex, “end-to-end machine learning allows the algorithm to learn the entire problem from input to output,” says Alex. “It is the most flexible and powerful tool we have to overcome insanely challenging problems with large amounts of data, such as self-driving cars.”
You can see the cars “learning” how to drive on the Wayve website; it’s like a child copying a parent. The vehicle “learns to drive with computer vision by both observing human driving and by using reinforcement learning.”
Alex also believes that this approach is a historic milestone because “it is the first time we are giving robots a physical interface to interact with us. There are prolific examples of artificial intelligence interacting with society through software – newsfeeds, dating apps and e-commerce, for example – but with self-driving cars, we will see the first physical interface between humans and machines.
“It’s an approach that will power the robots of the future, everything from cars to planes to ships to domestic robots or warehouse robots.”
Alex has been on the fast track since he went into the second year of mechatronics engineering from high school. His career reflects his childhood in Christchurch, with an engineer dad and a small-business-owning mum. His family is “one to chase excellence”, he says, and were inspirational and supportive.
“I feel very fortunate to have the confidence to be a tall poppy and live a unique life because of my family.”
As a child, he designed a solar-heating roof system with his dad, built tree houses, and made video games and Lego stop-motion movies. He loved learning and “pushing my comfort zone” and gave everything, from debating to music, a go.
Alex says he grew as a leader at university, and it was where he made friends and memories, not to mention being challenged academically and the lasting effect of “first principles knowledge across engineering”.
“I was able to surround myself with exceptional people who could teach me so much.” Alex’s future, for now, is in autonomous vehicles and the challenges of driving in one of the most complex urban environments in the world: London. But Wayve doesn’t plan to stop there.
“It is important that this technology is scalable, so everyone everywhere can benefit,” says Alex. “We aim to be the first to deploy our technology in a hundred cities. The ability to move is so central to our happiness, and self-driving cars will make this safe, sustainable, accessible and efficient.”
