Welcome to our X-Europe startup interview series. We have virtually sat down with a number of our founders from past cohorts to hear all about their solutions, vision for the future, and what made them tick during our X Europe programme. So whether you are a deep tech founder looking for startup support, an eagle-eyed investor, or simply interested in the possibilities that technology can bring to society, then we welcome you to take a read. Please meet Deepnews, a startup that uses machine learning to find, analyse and score news quality.
Can you briefly explain what your solution is all about? What’s unique about it?
Deepnews helps solve the problem of there being too much content with too little knowledge about it. Our model scores articles from 1-5 for journalistic quality and depth, which previously has required the expensive, time-intensive involvement of human editors. Now, for the first time ever, instead of only relying on the amount of engagement an article receives, companies that work with content can know more about it through the power of machine learning. Our research has shown that the higher-quality articles that Deepnews spotlights are up to 2.8x more likely to lead readers to subscribe.
What business sectors do you target? How does the technology make an impact?
The innovation that our scores represent means that they can be used in all sorts of companies that process news or content. This includes publishers who are able to immediately understand what sort of articles they have and where to use them to better engage readers, media monitoring companies who want to be able to sort through huge volumes of articles more efficiently, and analytics companies that want to help their clients better understand how information moves around.
The technology makes an impact by taking a dramatic step away from the internet where the primary metrics used are engagement-based and helps companies focus on *better* engagement. In the future, we will look back on the time when everything was measured in clicks and wonder what we were doing.
What’s the biggest milestone your startup has achieved so far, and what challenges are you still trying to overcome?
Our biggest milestones to date have been the launch of our Version Two model, which has used a much larger amount of data to achieve an impressive accuracy, as well as the signing of our first clients, who use our Deepnews quality scores to monitor in-depth news about topics including artificial intelligence and economic trends.
Our next challenge is to raise awareness of our solution so that everybody knows what is possible and the benefits they can see by being able to sort through the mass of content online at scale.
How has X-Europe helped you during the past few months?
X-Europe has helped Deepnews hone its core message, with the training giving us the knowledge to redesign our website and make it more effective at showing what we offer. It has been quite useful to bounce ideas off of the trainers and mentors, as well as the fellow participants that come with their own wealth of ideas and knowledge.
After joining and benefiting from the services X-Europe has provided, what next steps do you envision?
As we have refined our message with X-Europe, we have also been moving various companies through our sales pipeline. We look forward to beginning more partnerships throughout this year and to further developing our model into more languages.
What advice would you give to an entrepreneur trying to pave his/her way in the artificial intelligence / machine learning landscape?
To remember that AI and ML technologies are simply another tool or means to develop and deliver your solution, albeit it a rather cool and exciting one! All the usual steps apply if you want your idea to be a success: identify the problem, research, product/market fit, go-to-market, etc.
Your future customers won't care what AI tech your solution uses, just whether it will solve their problem and at what cost.
What’s unique about the X-Europe programme?
Rather than focusing only on one sector, I think that X-Europe’s decision to have an AI-ML cohort was a wise one. While our colleagues at various companies are all doing something different, they are also experiencing a lot of the same ups and downs that we have developing technology and bringing it out into the world.
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