Finchetto to develop photonics integrated circuits manufacturing in partnership with Cardiff University, UKRI and Development Bank of Wales 

Programme will establish thin-film lithium niobate photonic integrated circuit manufacturing to carry Finchetto’s fully optical switching technology for AI and data communications 

Cardiff, Wales – 13 October, 2026 // Finchetto, the company developing the world’s first fully optical packet switch for energy-efficient AI, today announced that it has commenced a ten-month programme of work to establish a manufacturing process for photonic integrated circuits (PICs) in Cardiff University’s sbarc|spark innovation building. The company secured a grant through the Investor Partnerships Programme, alongside private investment from Development Bank of Wales. It will enable Finchetto to utilise Cardiff University’s Institute for Compound Semiconductors cleanrooms.  

The company will develop thin-film lithium niobate (TFLN) photonics integrated circuits to carry its patented fully optical packet switching technology, capable of greatly reducing latency by 700x and power by 20x compared with traditional electro-optical network switches.  

Finchetto already has an established office in Cardiff—in addition to an office and lab in Guildford, Surrey—and has continued to hire in the area. The company’s participation in the programme represents a step forward for the development of sovereign manufacturing capacity for photonic technologies in the United Kingdom.  

Jack Christopher, Senior Investment Executive from Development Bank of Wales, said, “Wales has strong capabilities in compound semiconductors and photonics, which is why we’re delighted to support Finchetto’s work at Cardiff University. Bringing specialist process engineering to Cardiff will strengthen the region’s competitiveness and deepen the growing cluster of photonics innovation.” 

“This programme takes our fully passive optical networking technology towards a manufacturable product and builds upon the UK’s strong photonics manufacturing capabilities at the same time,” said Mark Rushworth, CEO of Finchetto. “Photonics is emerging as a pathway to radically more efficient AI and data communications; sovereign capacity will be crucial if the UK is to compete, and we’re delighted to be contributing to that.” 

About Finchetto:  

Finchetto is developing the world’s first patented fully optical passive packet switch for data centres, hyperscalers, high-performance compute and telecommunications.  

Designed from first principles to enable energy-efficient AI, Finchetto’s groundbreaking architecture reduces latency by 700x and power consumption by up to 20x compared to traditional network switches.  

Enabling super-low power, ultra-low latency packet switching at the speed of light with massive throughput, Finchetto’s network switch will accelerate AI efficiently and sustainably and reduce global data centre energy demands by up to 20%.  

www.finchetto.com  

Media contact: 

ThoughtLDR for Finchetto 

finchetto@thoughtldr.com 

+44 7553600128 

Editor’s Notes 

• In March 2026, the Council for Science and Technology advised that more than 60 per cent of the UK economy could depend directly on photonics by 2035 and that the sector could reach £50 billion in value and support up to 150,000 additional jobs.  

• The Government’s UK AI Hardware Plan, published in June 2026, committed to building sovereign capability in “emerging paradigms such as photonics.” 

Originally published in TechRadar Pro

The world is rushing to capitalise on the commercial and societal promise of AI. In the northeast of England, the recently announced Teesworks data centre project promises to be Europe’s largest data centre. Across the Atlantic, Amazon’s sprawling facilities in Indiana underscore how enterprises and governments are sprinting to build infrastructure for the AI era. The UK government’s new Compute Roadmap, for example, calls for at least 6GW of AI-ready data centre capacity by 2030—triple the current national footprint—to keep pace with the US and other leading markets. 

But beneath this breakneck growth, a quieter crisis is emerging. AI’s computational demands may be racing ahead, but the infrastructure required to support it—above all, power—is trailing behind. An urgent question must be answered: how can the grid keep up with our desire to scale AI? 

AI’s Boom Is Powering Up, But Can the Grid Keep Up? 

Projects like Teesworks and Amazon’s Indiana buildout are part of a global rush to shore up data centre capacity. Yet this rapid buildout is exposing a fundamental mismatch. Even as AI’s hunger for computing resources grows exponentially, there are high-profile harbingers of the potential bottlenecks introduced when national grids can’t keep up. 

In Northern Virginia – the world’s densest cloud hub – new AI and cloud projects have had to be paused due to a lack of electricity. Over in Ireland, data centres now consume more than 20% of national electricity, prompting proposals that they build their own private power lines. The UK, meanwhile, is relaxing planning rules for new transmission towers to speed up grid upgrades.  

This isn’t a problem inherent to regional infrastructures – it’s a global phenomenon brought about by putting the AI cart before the energy horse. And with AI’s runaway growth unlikely to slow down anytime soon, the focus must be on finding solutions to reduce energy demands as much as expanding grid capacity. 

The Looming Power Surge 

The data backs up the anecdotes. According to a Deloitte survey, 72% of US energy and data centre executives view power capacity as extremely challenging as a result of widespread AI adoption, and 82% see innovation – not just grid expansion – as the only viable solution. Bloomberg Intelligence reports that there’s now a 12–24 month gap between when data centres need power and when the grid can deliver it, a delay that is stalling growth in key markets. 

The issue is both technical and systemic. Even when renewable energy is available – such as wind power from Scotland – it often cannot reach the data centres that need it most, thanks to constrained transmission infrastructure. We face a kind of energy Catch-22: the need for more energy is desperate, but the energy we generate cannot always be used where it is required. The problem is compounded by the fact that conventional data centre hardware is not designed to be energy-efficient at the scale now demanded by AI workloads. 

Scaling Responsibly Versus Collapsing Under Demand 

The solution is not simply to build more data centres and expand the grid accordingly, but to also rethink the fundamentals of computing infrastructure. The investment gap is threefold: we need more data centres, yes, but also better grid access, accelerated renewable integration, and – critically – a new generation of energy-efficient hardware within the data centres themselves. 

Moore’s Law, which drove decades of exponential growth in computing, is reaching its limits. AI demands something more radical. The industry must look to technologies such as analogue computing, neuromorphic chips, and especially light-based (all-optical) architectures that eschew the costly energy conversions of current electro-optical networks. These innovations promise not just marginal gains, but step changes in energy efficiency—delivering the performance needed for AI workloads while slashing the electricity required per calculation. 

Rethinking Growth: Why More AI Shouldn’t Mean More Megawatts 

 At the moment, we measure AI progress in benchmarks, parameters, and flops. But this is a flawed metric if we ignore the energy cost of each inference. The industry must now prioritise “watts per task” as much as it does “exaflops”. This is not just about engineering, but about ethics: as AI becomes central to fields from healthcare to climate science, unchecked growth in energy demand risks both the planet and the public’s trust in AI’s benefits. 

Solving the energy challenge is not optional—it is existential for the AI industry. The International Energy Agency (IEA) warns that electricity demand from data centres worldwide is set to more than double by 2030, with AI at the heart of the surge. Without a shift towards smarter, more efficient infrastructure, we risk both environmental harm and the slowing of AI’s transformative potential. 

A Smarter Future Demands Smarter Foundations 

Every week, new forecasts predict exponential AI growth and the accompanying environmental strain. The answer is not to slow progress, but to accelerate investment in the technologies that can break the link between AI expansion and energy consumption. 

This is a call to action for the entire industry—for tech leaders, policymakers, and researchers to collaborate on global standards for efficiency, to back breakthrough research in energy-efficient hardware, and to ensure that the infrastructure of the future is designed for the demands of the present. The question is no longer if AI will change the world, but whether we have the world to sustain AI’s rise. 

The time to invest in smarter, not just bigger, foundations is now.