British entrepreneurs have accounted for seven of the 50 startups set to feature at CODE_n, the international enterprise startup awards competition.

The annual event will be held at CeBIT 2014 in the Deutsche Messe exhibition centre in Hanover next March, and participating early-stage companies are expected to have business plans around harnessing the power of big data, this year’s theme.

Around 450 companies from 60 countries applied for spaces at CODE_n, which is run by financial services IT solutions firm GFT, and Germany, the UK, the US, Brazil and Holland are some of the 16 countries which will be represented by the successful 50 startups.

UK finalists include healthcare solutions firm SOMA Analytics, location analytics startup Viewsy and cloud computing solutions company Sefaira.

GFT’s UK MD, Christopher Ortiz, said: "This year marked the most UK CODE_n entrants ever and it is very impressive to see so many UK finalists in the year that the UK is CeBIT’s country partner.

"Secondly, we are seeing a lot of exciting big data finalists with a financial services offering. We’ll be working closely with them to better understand the benefits they offer to our clients."

The finalists span from offering tools aimed at preventing traffic jams to software that creates a 3D map of the brain to spot tissue abnormalities.

One thing many have in common is the use of predictive analysis techniques to identify things like market trends.

Oliver Frese, Head of CeBIT at Deutsche Messe, said: "IT is pervasive across all industries and has fundamentally changed the face of how business is conducted these days.

"That is why we are so pleased, as the trade show hosts, to address users from all of these application areas, and let the young innovators from CODE_n provide new insights for these target groups."

The five-day initiative will also host an all day conference programme from Monday to Friday, and boasts an art installation by acclaimed designers Clemens Weisshaar and Reed Kram that visualises the concept of real, anonymised big data.

Photo: David Levene