AI from elite motorsport: Binnies, Williams Grand Prix Technologies and JuliaHub announce groundbreaking partnership to bring scientific machine learning to the UK water sector for the first time

In a transformative move for the UK water industry, Binnies – a leading water engineering services provider – has announced an exclusive partnership with Williams Grand Prix Technologies, the engineering consultancy of the Atlassian Williams Racing Formula 1 Team, and artificial intelligence (AI) pioneer, JuliaHub. Together, they are introducing scientific machine learning (SciML) to the UK water sector for the first time.

This pioneering collaboration brings cutting-edge AI from the motorsport, aviation and aerospace sectors to help water companies shift from reactive to predictive asset health to prevent failures – using largely the data they already have. It directly supports the direction set out in the recently released Cunliffe Review, which calls for water companies to get ahead of the failure curve by proactively assessing asset condition, even when data quality is limited.

"At Williams Grand Prix Technologies, we live by the same principles that fuel Formula 1– speed, precision, and relentless innovation. Scientific machine learning empowers us to predict complex system behaviours even from imperfect data, giving us the foresight that’s critical in high-stakes engineering. We’re thrilled to bring this capability to the UK water sector with Binnies and JuliaHub, transforming how asset health is monitored and helping the industry shift from reactive fixes to proactive resilience." Selin Tur, Managing Director & Chief Technology Officer, Williams Grand Prix Technologies 

Together, Binnies, Williams Grand Prix Technologies and JuliaHub are reshaping how the UK water industry approaches asset health. By combining high-performance AI from motorsport, precision engineering and deep sector expertise, they are introducing SciML for the first time. It’s a step change, enabling water companies to predict failures, optimise performance and invest with confidence, even with limited data. It’s a smarter, faster path to asset health.