Oriole Networks raises £10m in seed funding to advance optical artificial intelligence networking.
The seed round was co-led by UCL Technology Fund, Clean Growth Fund, XTX Ventures, and Dorilton
Oriole Networks develops optical networking technology designed to connect artificial intelligence chips and reduce energy consumption. The company emerged as a spinout from University College London to address performance bottlenecks in large scale machine learning.
Oriole Networks has secured £10m in seed funding to support its optical networking technology designed for artificial intelligence infrastructure. The round was co-led by UCL Technology Fund, Clean Growth Fund, XTX Ventures, and Dorilton Ventures, with additional backing from Innovate UK Investor Partnership.
Founded by a team of university scientists and industry veterans, the London-based startup uses light to connect multiple graphics processing units into unified processing clusters. The approach aims to accelerate the training of large language models while significantly lowering power usage in data centres.
From the founder
"AI computational needs are increasing by 10 times every 18 months. This leads to distributed training and inference across large numbers of xPUs. Collective data movement across the servers in the data centre becomes a bottleneck which in turn limits the training and inference completion time. This requires a fundamental shift in the co-design of next generation networked systems."
George Zervas
CTO at Oriole Networks
Investor perspective
"It’s rare to have such depth of innovation over many years at UCL combined with an experienced entrepreneur with domain knowledge and a massive market that is looking for this solution. This is going to be an exciting journey."
David Grimm
Partner, UCL Technology Fund
Investors
David Grimm
UCL Technology Fund

Beverley Gower-Jones
Clean Growth Fund
XTX Ventures
Daniel Freeman
Dorilton Ventures
Categories
About the company
Oriole Networks
Oriole Networks builds optical networking technology to connect artificial intelligence chips and reduce energy consumption.