Albion VCTs invest in UK machine learning startup Seldon

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Albion Capital Group‘s technology investment arm has jointly led a GBP7.1mln investment round into a UK-based machine learning startup.


Seldon, which is based in London, is a machine learning deployment specialist that works in partnership with the likes of Google, IBM and Amazon Web Services.


With its technology designed to help to ensure decisions made by machine learning algorithms are transparent and ethical, Seldon says its customers have experienced productivity gains of 92% as a result of using its products.


It has won contracts in various sectors, most notably in financial services, including a US stock exchange and credit card companies including Capital One.


Founded in 2014, it has reported average month-on-month revenue growth of 38% since September 2018.


AlbionVC, Albion’s specialist technology investment arm which also invests on behalf of the group’s six venture capital trusts (VCTs), co-led the series-A investment with Cambridge Innovation Capital, which also included investments by existing investors Amadeus Capital Partners, Global Brain and other existing shareholders.


Seldon said it will use the GBP7.1mln of new cash to accelerate research and development and drive commercial expansion, principally taking its new Seldon Deploy enterprise solution to market.


The startup’s aim is to more than double the size of its team over the next 18 months, and make several strategic hires in data science research and engineering to support further rollouts, plus a new ‘go to market team’ in the US, an engineering team in Asia and a new R&D lab in Cambridge, UK.


“Seldon is at the forefront of the next wave of tech innovation, and the leadership team are true visionaries,” said AlbionVC investment manager Nadine Torbey.


“Seldon has been able to build an impressive open source community and add immediate productivity value to some of the world’s leading companies. Seldon’s thorough understanding of market dynamics and customers’ commercial needs places them in a unique position to support users as they deploy machine learning models at scale.”

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