Company builder and early-stage investor Entrepreneur First’s Demo Day for its seventh London cohort has just taken place. The event, held in Kings Cross, saw 18 newly outed startups pitch their wares onstage to investors, press and other actors in the European tech scene.
But before I give a rundown of the presenting companies, including our top three picks, here’s a quick reminder of how EF works and what has made it a major player in the U.K. tech startup scene.
Founded back in 2011 by Alice Bentinck and Matt Clifford, the so-called “talent first” investor targets the best technical talent in Europe and beyond — both recent graduates and, increasingly, people already working at tech companies — and invites them to apply to its six-month program where they form teams and in turn found startups.
The EF program includes financial support in the form of a monthly stipend for living costs while founders find their co-founders and decide on an idea. This is then followed by £10,000 in pre-seed funding, in addition to office space, legal and administrative support and mentoring and advice from the EF team and external entrepreneurs from the wider U.K. startup scene.
Upon graduation from EF there is further support in the form of a £70,000 convertible note to help each company bridge the gap to a next funding round.
It is this “pre-team, pre-idea” approach that sets EF apart from other accelerators, while, as we’ve noted previously, the emphasis on technical talent is producing some very interesting results.
EF’s biggest (albeit only significant) exit to date was Magic Pony, sold to Twitter for a reported $150 million and creating a huge return for EF itself and the 1-year-old startup’s other early investors.
EF has also raised two funds of its own. Last year it announced its £40 million “Next Stage Fund” to add to the £8.4 million previously raised.
The new investment vehicle, which is majority backed by the U.K. taxpayer-funded British Business Bank and also counts LPs such as Imperial College, Sir Charles Dunstone’s Freston Ventures and Isomer Capital, is charged with co-investing in graduating companies at the seed and Series A stage.
Since 2011, EF says it has worked with 450 individuals to build more than 100 startups that are now valued in excess of $500 million, apparently.
Onstage, Alice Bentinck, co-founder of Entrepreneur First, revealed that cohort seven also sees a third of its teams having female founders, which, let’s just say, is a significant improvement on previous years. That’s something EF is working hard on, including via its sister organization Code First: Girls.
Commenting on EF’s seventh London Demo Day, Bentinck says: “This cohort represents one of our most diverse yet, in terms of ideas and industries that they are working within, and their collective backgrounds. There are over 20 nationalities represented in this cohort, eight of the founders are PhDs and across the group of 35 individuals, there have been over 60 academic publications and over 750 citations in papers. The ideas that the teams are working on, continue to set their sights on high ambitions.”
Scalia is building what it describes as a “unified product data platform” for the e-commerce industry. The — potentially, huge — problem it is setting out to solve is that 71 percent of product listings are inaccurate, incomplete or just plain wrong.
That’s because there is no standardization in data, in terms of product schema and definitions, and data format.
This, says the startup, is the root cause of brand damage on the supplier side, and retailer side, and leads to high product returns (because customers end up with incorrect orders being fulfilled).
To solve this, Scalia’s data exchange platform uses machine learning to make product mapping simple, in addition to enriching existing data using computer vision for up to 17 data points.
The result is that the company aims to be the single source for product data. Or, more ambitiously, a “universal data layer for the e-commerce industry.”
“Product standardization doesn’t sound sexy, even if you put it in a French accent. But it’s unavoidable,” said the Scalia founder ending his pitch.
Transformative is working on what it calls “predictive healthcare through deep learning.” They have created a patent-pending algorithm, dubbed cardioAI, that is able to predict the onset of sudden cardiac arrest, allowing for advance warning and preparation for intervention.
Based on the premise that predictive analytics is the key to improving healthcare, Tranformative’s AI-powered algorithm detects small changes in physiology, allowing for prior warning and advanced intervention for patients at risk.
The startup’s prototype claims a 91 percent success rate at predicting cardiac arrest four minutes in advance of an incident. The aim is to extend it to an hour.
“By 2025, you’ll be able to hail a flying car,” opened the Marble founder, which, incidentally, marked the 100th pitch in EF’s history.
After providing the caveat that “moonshot” projects from the likes of Google are also working on flying cars and that they will need to cross major technical and legal hurdles, he described how the company is getting a head start by building autonomous electric aircraft for maritime surveillance.
Specifically, these are designed as low-cost, modular, aerospace-grade unmanned flying vehicles.
Admittedly, it was impossible to choose just three top picks from EF7, so I’m sneaking in a bonus fourth pick: Observe is described as the world’s first AI automation platform for fish farms.
The idea is to replace a very manually intense process that comprises using video footage and other sensors to maintain optimum feeding in terms of getting the fish as big as possible as fast as possible and as cheap as possible.
Overfeeding wastes food and lowers margins, while underfeeding means the fish don’t grow fast enough to be profitable.
To solve this, Observe uses computer vision and machine learning to simplify the feeding process on large-scale fish farms: how much to feed and when.
It has partnered with the leading grower of salmon, meaning the startup has “5 million fish to train our data sets on.” The ultimate aim is to make fish the most sustainable food source in the world. Or, in the founder’s own words, they’re going to “capture the market hook, line and sinker.”
The full list of presenting teams (in their own words)
Eyn combines advanced face recognition techniques with novel facial anti-spoofing to transform the smartphone into a real-time biometric ID verification device.
Sentient Machines uses deep learning to bring customer understanding to the call center industry.
OilFront transforms the way shipping companies buy fuel in a market worth more than $200 billion per year.
Scalia is the unified product data platform that powers the e-commerce industry.
Observe Technologies is using artificial intelligence to automate fish farms.
Transformative enables predictive healthcare through deep learning.
Proportunity explains and forecasts the real estate market using machine learning.
Multiply is using AI to bring holistic financial advice to millions.
Optimal Labs is building artificial intelligence for highly controllable farming environments Their state-of-the-art deep reinforcement learning algorithms turn intuition into science, multiplying the profitability of greenhouses.
Scape is a 3D-mapping company focused on augmented reality.
Lendr is a reverse-auction platform for mortgages.
Plotist is the first story-centric production management platform that brings together the whole production team around the story they are telling.
Marble is building the future of autonomous electric aircraft. We have already begun with a breakthrough maritime surveillance aircraft.
Creative AI gives every business the power of a dedicated marketing team.
ThinkSono empowers any healthcare professional to diagnose deep vein thrombosis (DVT) at the point of care.
Predina Technologies is the AI platform for predicting and mitigating risk in autonomous vehicles.
Selerio unlocks untapped ad revenue in videos with real-time, targeted, product placement.
Phoelex is revolutionizing data centers with transceivers that are 5x cheaper, 10x smaller and 3x more energy-efficient.