ACE3 combines deep systems research with product, venture, and commercial leadership to address a core issue in modern AI: how to deliver more capability from every unit of compute.
To translate advanced systems optimisation into commercial infrastructure that makes AI workloads faster, more cost-efficient, and easier to deploy at scale.
A future where compute efficiency becomes an enabler of AI adoption rather than a constraint on product quality, deployment speed, and margin.
ACE3 was formed around a clear market shift: model innovation is accelerating, but the infrastructure required to run modern AI remains expensive, complex, and operationally demanding. The company exists to improve that layer with focused systems technology.
ACE3 draws on academic strength in distributed systems, optimisation, and AI acceleration, while also bringing in leadership experienced in venture creation, enterprise growth, product strategy, and company building.
ACE3 operates close to the runtime and hardware layer, where targeted optimisation can affect every workload that runs above it.
The company is aimed at real deployment environments, from research clusters to enterprise and cloud-based AI operations.
Improving throughput and reducing compute cost matter because they influence product margins, responsiveness, and the viability of AI at scale.
The leadership group combines technical founders with operators, venture builders, and product leaders who understand commercial execution.
ACE3 is being built at a time when inference growth, infrastructure spending, and pressure on AI economics are making efficiency more strategic.
A stronger software layer can create more output from the same compute estate, improving both cost discipline and infrastructure utilisation.
Technical founders and operators with experience across distributed systems, venture creation, enterprise growth, and AI product commercialisation.
Research Fellow at the University of Leeds, specialising in optimisation for large AI models, machine learning acceleration, and advanced computing architectures.
Senior technology executive with more than 20 years of leadership experience across digital businesses, including Monster.com, PrismaStar, and Centrica's digital division.
Professor of distributed computer systems at the University of Leeds, Executive member of the UKCRC, and Turing Fellow in Data Science.
Professor of distributed computer systems at the University of Leeds, Royal Society Industry Fellow, and recognised among the Top 2% Scientists from 2020 to 2024.
Head of Ventures
Head of Ventures at Leeds TTO with a technical background in electronics and applied laser physics, and experience supporting the formation of more than 25 deep-tech spinouts.
Product leader focused on AI product development, market positioning, and translating technical capability into clear commercial value.
Senior Software Engineer
Software engineer focused on AI acceleration and distributed systems optimisation in performance-critical environments.
Software Engineer
Software engineer focused on machine learning and CUDA programming.
ACE3 welcomes conversations around strategic partnerships, customer deployments, commercial collaboration, and investment in the infrastructure layer of AI.