We partnered with Wayve AI to design a scalable GUI and design system supporting AI training and autonomous driving. Through speculative design and dynamic data visualisation, the platform unites engineering and design while making AI-powered mobility more transparent and trustworthy.

The success of autonomous driving depends on adaptability and trust. Rule-based systems struggle to manage unpredictable traffic and varied conditions, limiting scalability. For AI-driven approaches, the challenge lies in training models that can continuously learn and adapt across geographies, vehicles, and environments. This requires a two-way interface that not only enables machine learning teams to collect and visualise data but also provides an intuitive, real-time user experience. Without a clear, scalable GUI, development risks stalling in complexity and misalignment.

We designed a comprehensive GUI design system serving two critical functions: training AI models and supporting future driverless interactions. Through speculative design and agile sprints, we established a GUI “north star” to align teams and ensure long-term scalability. The system incorporated dynamic data visualisation, enabling ML engineers to collect, interpret, and refine real-world driving data with clarity. For end users, we prioritised safety, trust, and real-time feedback, ensuring the interface would remain approachable as the technology matures. Built on reusable components, the system accelerated iteration and provided a robust foundation for scaling embodied AI across multiple vehicle platforms.

The GUI design system became a foundational enabler for Wayve’s embodied AI approach, improving internal alignment and accelerating model development cycles. By delivering clarity for engineers and usability for future drivers, the system positioned Wayve as a leader in next-generation autonomous technology. These advancements supported the company’s rapid growth and contributed to its landmark $1.05 billion Series C funding round, led by SoftBank Group, to scale AI-powered autonomous driving globally.