Edinburgh University spinout firm Expanse, the AI infrastructure company, announced a $5.3 million seed funding round led by Crane Venture Partners with participation from PXN Ventures and angel investors including former DeepMind researchers “and leaders from AI infrastructure teams.”
Expanse will use the funding to expand its engineering team, accelerate product development and bring its platform to more organisations across AI infrastructure, quantitative finance, life sciences, research and high performance computing.
Expanse was founded by four University of Edinburgh graduate engineers who previously built and operated large-scale compute infrastructure across quantitative finance and national supercomputing facilities.
Expanse said that while at the Edinburgh Parallel Computing Centre (EPCC), part of the University of Edinburgh, co-founder Ismaeel Bashir developed “a multimodal HPC resource prediction system that set a new benchmark for predicting resource requirements across HPC workloads.”
Together, Bashir and co-founders Nikodem Bieniek, Eren Mendi and Yafet Melaki “recognised that even the world’s most sophisticated compute environments still relied on manual estimation to allocate resources efficiently.”
That experience has already translated into measurable customer outcomes. In one production deployment, Expanse identified nearly $8 million of idle compute capacity in a single month, highlighting the scale of untapped infrastructure sitting inside many organisations.
“GPUs (graphics processing units) have become one of the world’s most constrained resources, yet much of that capacity sits underutilised,” said Expanse.
“Every AI workload begins with uncertainty. Engineers must estimate how many GPUs, CPUs (central processing units), how much memory and how long their code will run before execution begins.
“Those estimates determine how billions of dollars of infrastructure are allocated every day. Industry estimates suggest approximately 30% of cloud spend is lost through over-allocation, while Microsoft Research has reported GPU utilisation of around 50% across many internal deep learning workloads …
“Expanse eliminates that guesswork …
“Its software predicts exactly what an AI workload requires before it runs, recommending the optimal GPU, CPU, memory and runtime configuration before any resources are committed.
“By right-sizing workloads ahead of execution, organisations can complete significantly more work using the infrastructure they already own, reducing failed jobs, increasing utilisation and avoiding unnecessary investment in additional compute.
“Unlike traditional monitoring and observability platforms, which explain what happened after a workload has finished, Expanse works before execution begins.
“Installed directly into an organisation’s cloud or on-premises infrastructure, its models analyse workloads without code or telemetry ever leaving the customer’s environment, allowing organisations to optimise performance while maintaining complete data sovereignty.”
Ismaeel Bashir, co-founder and CEO of Expanse, said: “Today, every AI workload begins with an educated guess.
“Engineers shouldn’t have to predict exactly how much compute their code will need before they press run. The machine should carry the uncertainty, not the person.”
Scott Sage, co-founder and partner at Crane Venture Partners, said: “The future of AI won’t be defined only by who builds the biggest clusters, but by who uses them most intelligently.
“Expanse gives organisations something they don’t have today: certainty. By predicting exactly what every workload needs before it runs, customers recover existing capacity, reduce waste and extend the life of some of the world’s most valuable infrastructure. We believe that’s a new and important category in AI infrastructure.”
Andy Barrow, Managing Director of PXN Ventures, said: “The widespread adoption of AI by businesses and everyday users has led to an unprecedented focus on the infrastructure required to service this technology and many of the challenges that engineers face.
“As Expanse has identified, one of those challenges is optimisation and helping businesses to make better use of their compute resource, which can lower running costs and increase scalability. PXN is proud to be backing Ismaeel and the team, who are tackling this head on.”