The London-based AI startup Cytora has just raised £2.4 million in Series A funding led by Parkwalk with participation from Cambridge Enterprise, iLexIR and a high-profile group of angels including Alan Morgan, Paul Forster and Matthew Grant, a former executive at RMS.
The a three-year-old company is focused on capturing hidden economic insights that exist in online data, giving clients a comprehensive overview of what is changing in the world and an unparalleled ability to unearth leading indicators and opportunities.
Alan Morgan, chairman of MMC Ventures stated: “Cytora is meeting a real need in a rapidly changing world, it delivers data and analytics to enable real insights and inform decisions, especially around the pricing of risk.”
With a background in geopolitical and supply chain risk, the 20-person startup now works with global companies in finance and insurance and has deep relationships in asset management. Asked how Cytora’s fresh capital will be used, CEO and co-founder Richard Hartley said the company plans to commercialise heavily in one of these areas over the next six months.
“We help businesses gain a comprehensive understanding of risk, particularly in new and emerging markets, by leveraging the observation power of the internet,” says Hartley. “In the right hands, our data provides an information advantage which can drastically impact underwriting and trading decisions.”
Using machine learning, Cytora connects billions of data points together, automatically assembling vast datasets that humans are unable to generate because of the huge volume and velocity of data on the web. Insurers use this data, for example, to quantify the number of losses across insurance lines such as Cyber and Product Recall to optimise their underwriting strategy and risk pricing.
Cytora is the first company to be funded by the Judge Business School at Cambridge University, and the AI startup is also a member of the Plug and Play accelerator in California. Check out the startup’s recent pitch, performed at the Plug and Play winter summit: