Three spin-offs make the finals of a deep tech startup competition
Three EPFL spin-offs – CompPair, Hydromea and Nanogence – have made it through to the finals of the Hello Tomorrow Global Challenge, an international startup competition that is being held virtually this year. The teams will have three minutes to pitch their business ideas to a panel of experts.
Just six years after its launch, the Hello Tomorrow Global Challenge has become one of the most prestigious competitions on the international startup scene. Three EPFL spin-offs, including two from the School of Engineering – CompPair, Hydromea and Nanogence – have made it through a global field of 5,000 deep tech startups and onto the list of just 80 finalists. The teams will have three minutes to pitch to a panel of experts: investors, corporates, other startups, researchers and specialized journalists. The exposure they gain could prove invaluable as they look to grow their businesses and raise funds from investors.
The finalists will get their first chance to impress this week – and take away a €10,000 prize – as they battle it out to be crowned the winner in one of 14 industry tracks. In normal times, the competition takes place front of a live audience in Paris. But circumstances this year meant the teams had to pre-record their pitches. The winning startups from each track will get one minute to make a final pitch for the Grand Prize: €100,000 and unparalleled global exposure.
Deep tech startups develop systems that can potentially revolutionize a sector or industry. One example is GTX Medical (formerly G-Therapeutics), an EPFL spin-off that won the first Hello Tomorrow Grand Prize back in 2014. After raising €36 million in 2016 and merging with a US-based competitor in 2019, the company is further developing its implantable neuromodulation therapy to help people with spinal cord injuries walk again. Disruptive technologies like these are the culmination of years of lab-based research. And even once a startup has been founded, there’s a lot of testing and development work to be done before a product can be brought to market. The deep tech business model requires heavy upfront investment and a great deal of patience – it can be years before investors see a return on their money.