Wayve

Wayve has secured $1.5B to deploy our embodied AI platform globally. Autonomy should work everywhere, in every condition, across every type of vehicle. We are building a driving intelligence that learns to drive in places it has never seen before.

Wayve's new research unit, Wayve Labs, seeks to leverage AI for broader robotic applications. Chief scientist Jamie Shotton leads the charge beyond self-driving cars with fresh funding and top-tier talent. bit.ly/4vg2hsO

Learn more about our work and what this means for the future of Embodied AI 👇 wayve.ai/thinking/build…

While driving has been the right place to start, it was always only the beginning. Wayve Labs will be key to generalizing world modelling, spatial intelligence, and policy learning systems across many different robotics platforms and environments.

Introducing Wayve Labs - our frontier research unit dedicated to advancing embodied AI and solving the hardest and most important open problems in machine learning. wayve.ai/labs

Proud to join @NissanMotor and @Uber as the first members of @PAVEUK_, collaborating on open, transparent public engagement around the deployment of self-driving vehicles in the UK. Read the full announcement 👇 bit.ly/3S7bSUs

@alexgkendall joined Peter Sigal and Simon Monske from @CapgeminiInvent on the latest episode of Eurostars Speak to discuss our unique AV 2.0 approach and the future of autonomous mobility. Watch the full episode ⬇️ autonews.com/sponsored/in-t…

The launch of UK’s self driving vehicles pilot scheme is an important step towards realising widescale self-driving passenger services in the UK. We’re proud to support the UK government and @transportgovuk in shaping this regulation, helping unlock the generational opportunity of self-driving technology across the UK, starting with our first commercial deployment in London later this year.

Wayve’s self-driving tech is headed to US cars made by Stellantis techcrunch.com/2026/05/21/way…

I'm in Detroit today for some big news! Excited to work with @Stellantis to integrate our @wayve_ai Driver into their vehicles, starting in North America in 2028. Stellantis’ scale + Wayve’s global AI = magic for customers.

Today, we’re announcing a strategic technology partnership with @Stellantis, bringing the Wayve AI Driver to the STLA AutoDrive platform. The collaboration will enable hands-free, door-to-door supervised automated driving across both urban streets and highways. ➡️ Launching in 2028 in North America. 📈 Built on an AI architecture that can scale across vehicle platforms and markets over time. Learn more 👇 wayve.ai/press/stellant…

Last week, we hosted our first Wayve Open Day in our Tokyo office! Demo rides, talks from @alexgkendall and the team, and the chance to learn more about our partnership with @NissanMotor. Our Japan team is growing fast! wayve.firststage.co/jobs?location=…

Two robotaxi companies are taking different approaches to training AI. Waymo builds a detailed 3D map to train its AI before operating in a new area, while Wayve trains its AI without mapping. cbsn.ws/49ariNI

1 → 100 in a year Our Japan team is scaling fast, now in production programs with @NissanMotor across consumer vehicles and robotaxis Japan is emerging as a major market for embodied AI. We’re just getting started I was in Tokyo today to host AI Open Day - we're hiring! 🇯🇵

Wayve and @biztradegovuk have signed a partnership to help put Britain at the forefront of self-driving technology. The collaboration will support shared research, future deployment and the growth of a world-leading UK ecosystem for AI-enabled mobility. wayve.ai/press/wayve-si…

Our AI Driver has driven in over 500 cities with little to no training data. Behind every deployment is Wayve’s rigorous Fleet Operations team, ensuring exposure to real-world complexity happens deliberately, effectively, and above all, safely. Meet the team 👇 wayve.ai/thinking/life-…

We're here in listening mode... Watch @alexgkendall and @MeryemArik9 discuss how Sovereign AI can be the best partners for AI startups with @KanishkaNarayan.

4/4 - long, winding roads through rural Germany. This is only the beginning. Our team has already identified ways to scale LA-Pose further, enabling the model to learn richer representations of motion and generalise more effectively across new environments. But the core idea holds: motion is the signal. And it’s already everywhere. We’re excited to be bringing this work to CVPR and to share more of what LA-Pose is capable of very soon. The full paper, interactive latent space demos, and in-the-wild videos can be found here: la-pose.github.io

3/4 - a narrow road through a village in Germany. 🇩🇪 The important question is: why does this matter for autonomy? Wayve vehicles have driven in hundreds of cities across vastly different conditions. That data exists. The question has been whether that experience can generalize to a new city or scenario without running another LiDAR rig or building another labeled dataset from scratch. Most 3D perception systems can’t. They’re trained on curated datasets and calibrated hardware. That keeps them accurate in conditions they’ve seen and fragile in the ones they haven’t. LA-Pose is a different bet: that unlabelled video at scale contains enough signal to build rich geometric priors, and that a small amount of targeted supervision can ground those priors in metric reality. That changes both the economics and the trajectory of improvement.

Meet LA-Pose. Our latest model taking Wayve another step towards generalization at scale. LA-Pose employs large-scale self-supervised learning, building strong motion representations for 3D perception from 10.2 million unlabeled driving video snippets, unlike today's strongest approaches that often depend on expensive, carefully curated 3D supervision. With only a lightweight pose head and limited labelled data, LA-Pose achieves: 📷 State-of-the-art camera pose estimation 🌎 Strong zero-shot generalization across diverse driving scenarios 🏷️ Orders of magnitude less labelled data than fully supervised 3D approaches Our full blog post: wayve.ai/thinking/la-po… Explore the full paper here: la-pose.github.io