The team behind Rlay believes that blockchain technology can play a crucial role in helping businesses crowdsource their data-gathering tasks.

Founder Michael Hirn said this is a problem he encountered while working with Sunstone Capital to develop a more quantitative approach to venture capital, which meant pulling startup data from a wide variety of online sources. It ended up being an incredibly time-consuming process, and he said, “90 percent of the time was spent cleaning the data and acquiring the data.”

CTO Max Goisser argued that this is a broad problem. There are already successful examples of crowdsourced data, most notably Wikipedia, but in his view, they succeeded because “these things were of value for the entire world — everyone’s interested in that.”

“But what if you wanted to crowdsource something that is [only] interesting to you as a company?” Goisser said. Then you’d need the right incentive system to convince people to contribute. And that’s where Rlay (pronounced “relay”) comes in — the startup is launching onstage today as part of our Startup Battlefield at Disrupt Berlin.

There are other startups, like Dirt Protocol, offering blockchain-powered tools for data collection and verification. But it sounds like one of Rlay’s big selling points is its ability to integrate with existing enterprise database technology.

In other words, Rlay leverages the blockchain side of things to provide a mechanism for people to contribute data and be rewarded for their contributions (each customer decides how they want to structure the incentives), but the goal is to collect the data in a format that’s useful for the company, and where, if the company desires, it can be kept private.

“We abstract over the backend database that you as a company would use, we abstract over the blockchain or ledger technology — it’s currently Ethereum, but technically, it doesn’t matter,” Hirn said. “So you don’t have to figure out how to work between Postgres and Ethereum, you don’t have to figure out ‘How do we represent the data?’, all of that is taken care of by Rlay.”

As for the incentives, he said:

There are almost as many ways [of] incentivizing as there are different types of financial products. Obviously some ways are more robust than others and we outlined a very general and universal incentive mechanism in our whitepaper, but for most of the applications that is a little bit to complex. So with Rlay, we will provide some templates in the future and certainly advice for certain ways when we work with a client, but Rlay just gives a good interface to define these things very easily.

Ultimately, this should allow companies to acquire the data they need at a lower cost than going out and buying data sets or hiring their own data collection team. For example, Hirn said Rlay is working with “a big name in the blockchain space” to gather environmental, social and governance (ESG) data required by hedge funds and other investors.

For now, Hirn said Rlay is focused on working with developers to collect data that’s online but not aggregated or structured in a way that makes it easily accessible. In the ESG case, that means writing scripts to pull the data from the reports that many companies are already publishing. Ultimately, Rlay could move into collecting data from the physical world, as well.

Goisser said the company is also developing various ways to recognize and resolve conflicting data, so its customers can be sure that the information they’re collecting is accurate.

Source: Tech Crunch Startups | Rlay offers a blockchain-powered platform to help companies build better crowdsourced data sets

Presenting onstage today in the 2018 TC Disrupt Berlin Battlefield is Indian agtech startup Imago AI, which is applying AI to help feed the world’s growing population by increasing crop yields and reducing food waste. As startup missions go, it’s an impressively ambitious one.

The team, which is based out of Gurgaon near New Delhi, is using computer vision and machine learning technology to fully automate the laborious task of measuring crop output and quality — speeding up what can be a very manual and time-consuming process to quantify plant traits, often involving tools like calipers and weighing scales, toward the goal of developing higher-yielding, more disease-resistant crop varieties.

Currently they say it can take seed companies between six and eight years to develop a new seed variety. So anything that increases efficiency stands to be a major boon.

And they claim their technology can reduce the time it takes to measure crop traits by up to 75 percent.

In the case of one pilot, they say a client had previously been taking two days to manually measure the grades of their crops using traditional methods like scales. “Now using this image-based AI system they’re able to do it in just 30 to 40 minutes,” says co-founder Abhishek Goyal.

Using AI-based image processing technology, they can also crucially capture more data points than the human eye can (or easily can), because their algorithms can measure and asses finer-grained phenotypic differences than a person might pick up on or be easily able to quantify just judging by eye alone.

“Some of the phenotypic traits they are not possible to identify manually,” says co-founder Shweta Gupta. “Maybe very tedious or for whatever all these laborious reasons. So now with this AI-enabled [process] we are now able to capture more phenotypic traits.

“So more coverage of phenotypic traits… and with this more coverage we are having more scope to select the next cycle of this seed. So this further improves the seed quality in the longer run.”

The wordy phrase they use to describe what their technology delivers is: “High throughput precision phenotyping.”

Or, put another way, they’re using AI to data-mine the quality parameters of crops.

“These quality parameters are very critical to these seed companies,” says Gupta. “Plant breeding is a very costly and very complex process… in terms of human resource and time these seed companies need to deploy.

“The research [on the kind of rice you are eating now] has been done in the previous seven to eight years. It’s a complete cycle… chain of continuous development to finally come up with a variety which is appropriate to launch in the market.”

But there’s more. The overarching vision is not only that AI will help seed companies make key decisions to select for higher-quality seed that can deliver higher-yielding crops, while also speeding up that (slow) process. Ultimately their hope is that the data generated by applying AI to automate phenotypic measurements of crops will also be able to yield highly valuable predictive insights.

Here, if they can establish a correlation between geotagged phenotypic measurements and the plants’ genotypic data (data which the seed giants they’re targeting would already hold), the AI-enabled data-capture method could also steer farmers toward the best crop variety to use in a particular location and climate condition — purely based on insights triangulated and unlocked from the data they’re capturing.

One current approach in agriculture to selecting the best crop for a particular location/environment can involve using genetic engineering. Though the technology has attracted major controversy when applied to foodstuffs.

Imago AI hopes to arrive at a similar outcome via an entirely different technology route, based on data and seed selection. And, well, AI’s uniform eye informing key agriculture decisions.

“Once we are able to establish this sort of relation this is very helpful for these companies and this can further reduce their total seed production time from six to eight years to very less number of years,” says Goyal. “So this sort of correlation we are trying to establish. But for that initially we need to complete very accurate phenotypic data.”

“Once we have enough data we will establish the correlation between phenotypic data and genotypic data and what will happen after establishing this correlation we’ll be able to predict for these companies that, with your genomics data, and with the environmental conditions, and we’ll predict phenotypic data for you,” adds Gupta.

“That will be highly, highly valuable to them because this will help them in reducing their time resources in terms of this breeding and phenotyping process.”

“Maybe then they won’t really have to actually do a field trial,” suggests Goyal. “For some of the traits they don’t really need to do a field trial and then check what is going to be that particular trait if we are able to predict with a very high accuracy if this is the genomics and this is the environment, then this is going to be the phenotype.”

So — in plainer language — the technology could suggest the best seed variety for a particular place and climate, based on a finer-grained understanding of the underlying traits.

In the case of disease-resistant plant strains it could potentially even help reduce the amount of pesticides farmers use, say, if the the selected crops are naturally more resilient to disease.

While, on the seed generation front, Gupta suggests their approach could shrink the production time frame — from up to eight years to “maybe three or four.”

“That’s the amount of time-saving we are talking about,” she adds, emphasizing the really big promise of AI-enabled phenotyping is a higher amount of food production in significantly less time.

As well as measuring crop traits, they’re also using computer vision and machine learning algorithms to identify crop diseases and measure with greater precision how extensively a particular plant has been affected.

This is another key data point if your goal is to help select for phenotypic traits associated with better natural resistance to disease, with the founders noting that around 40 percent of the world’s crop load is lost (and so wasted) as a result of disease.

And, again, measuring how diseased a plant is can be a judgement call for the human eye — resulting in data of varying accuracy. So by automating disease capture using AI-based image analysis the recorded data becomes more uniformly consistent, thereby allowing for better quality benchmarking to feed into seed selection decisions, boosting the entire hybrid production cycle.

Sample image processed by Imago AI showing the proportion of a crop affected by disease

In terms of where they are now, the bootstrapping, nearly year-old startup is working off data from a number of trials with seed companies — including a recurring paying client they can name (DuPont Pioneer); and several paid trials with other seed firms they can’t (because they remain under NDA).

Trials have taken place in India and the U.S. so far, they tell TechCrunch.

“We don’t really need to pilot our tech everywhere. And these are global [seed] companies, present in 30, 40 countries,” adds Goyal, arguing their approach naturally scales. “They test our technology at a single country and then it’s very easy to implement it at other locations.”

Their imaging software does not depend on any proprietary camera hardware. Data can be captured with tablets or smartphones, or even from a camera on a drone or using satellite imagery, depending on the sought for application.

Although for measuring crop traits like length they do need some reference point to be associated with the image.

“That can be achieved by either fixing the distance of object from the camera or by placing a reference object in the image. We use both the methods, as per convenience of the user,” they note on that.

While some current phenotyping methods are very manual, there are also other image-processing applications in the market targeting the agriculture sector.

But Imago AI’s founders argue these rival software products are only partially automated — “so a lot of manual input is required,” whereas they couch their approach as fully automated, with just one initial manual step of selecting the crop to be quantified by their AI’s eye.

Another advantage they flag up versus other players is that their approach is entirely non-destructive. This means crop samples do not need to be plucked and taken away to be photographed in a lab, for example. Rather, pictures of crops can be snapped in situ in the field, with measurements and assessments still — they claim — accurately extracted by algorithms which intelligently filter out background noise.

“In the pilots that we have done with companies, they compared our results with the manual measuring results and we have achieved more than 99 percent accuracy,” is Goyal’s claim.

While, for quantifying disease spread, he points out it’s just not manually possible to make exact measurements. “In manual measurement, an expert is only able to provide a certain percentage range of disease severity for an image example; (25-40 percent) but using our software they can accurately pin point the exact percentage (e.g. 32.23 percent),” he adds.

They are also providing additional support for seed researchers — by offering a range of mathematical tools with their software to support analysis of the phenotypic data, with results that can be easily exported as an Excel file.

“Initially we also didn’t have this much knowledge about phenotyping, so we interviewed around 50 researchers from technical universities, from these seed input companies and interacted with farmers — then we understood what exactly is the pain-point and from there these use cases came up,” they add, noting that they used WhatsApp groups to gather intel from local farmers.

While seed companies are the initial target customers, they see applications for their visual approach for optimizing quality assessment in the food industry too — saying they are looking into using computer vision and hyper-spectral imaging data to do things like identify foreign material or adulteration in production line foodstuffs.

“Because in food companies a lot of food is wasted on their production lines,” explains Gupta. “So that is where we see our technology really helps — reducing that sort of wastage.”

“Basically any visual parameter which needs to be measured that can be done through our technology,” adds Goyal.

They plan to explore potential applications in the food industry over the next 12 months, while focusing on building out their trials and implementations with seed giants. Their target is to have between 40 to 50 companies using their AI system globally within a year’s time, they add.

While the business is revenue-generating now — and “fully self-enabled” as they put it — they are also looking to take in some strategic investment.

“Right now we are in touch with a few investors,” confirms Goyal. “We are looking for strategic investors who have access to agriculture industry or maybe food industry… but at present haven’t raised any amount.”

Source: Tech Crunch Startups | Agtech startup Imago AI is using computer vision to boost crop yields

It can be tough for diabetes patients to keep a constant eye on their glucose levels. Spike Diabetes lets family and doctors lend a hand by sending them real-time alerts about the patient’s stats. And the app’s artificial intelligence features can even send helpful reminders or suggest the most diabetes-friendly meals when you walk into a restaurant.

Today onstage at TechCrunch Disrupt Berlin Startup Battlefield, Spike Diabetes is launching its Guardian Portal so loved ones with permission can get a closer look at a patients’ data and coach them about staying healthy.

“Diabetes is an incurable chronic disease that forces diabetics to live a life of carb-counting and insulin injections,” says Spike co-founder Ziad Alame. “Since diabetics are forced to do those mundane tasks for the rest of their lives, they tend to fall off the tracks sometimes simply because of how demanding those tasks can be. As for guardians and parents, they are left in the dark about their loved ones.”

With doctors often only getting data during quarterly or semi-annual checkups, patients are often left on their own. “A lifetime of management is very stressful, especially if your life depends on it.”

The startup faces stiff competition from literally hundreds of apps claiming to help patients monitor their vitals. MySugr, Diabetes Connect and Health2Sync are among the most popular. But Alame says many require users to track their levels through complex spreadsheets.

Spike offers customizable mobile charts, and will even read users their stats out loud to make staying safe an easier part of daily life. Spike is invite-only and just on iOS, but it also touts an Apple Watch app plus optimized engineering to minimize battery usage.

“Spike started off as a personal project to help myself adhere better to my medication after reaching critical times in my diabetic life,” Alame tells me. Now he’s bringing to the problem his experience as CTO of the GivingLoop charity platform, TeensWhoCode summer camp and Zoomal crowdfunding site for the Arab world.

Alame has assembled a team of diabetics, engineers and PhDs, plus $200,000 in seed funding from MEVP, Cedar Mundi and Phoenician Funds. They hope to see the premium paid version of Spike’s freemium app overtake longstanding competition through word-of-mouth triggered by bringing loved ones and doctors into the loop.

One of the app’s most interesting features is the proactive info it delivers. “For example, you walk into McDonald’s around 2 PM. Spike would automatically know it’s lunch time for you and suggest the top three options you can have with approximate carb counts,” Alame tells me.

“After some time (~25 minutes) Spike automatically reminds you of your insulin and syncs with your diabetic devices to log all the details. With time, as the app gets to know the diabetic’s taste more, Spike would be able to suggest small behavioral tweaks to enhance lifestyle such as walking routes suggestions or new places similar to the diabetic’s taste but with a lower insulin consumption rate.”

Alame jokes that “The biggest risk [to Spike] is the best thing that can happen — which is finding a cure for diabetes.” But even if that happens, he believes Spike’s app for tracking and actively coaching users could be relevant to other diseases, as well. For now, though, it will have to convince users that an app could make managing diabetes simpler rather than more complex.

Source: Tech Crunch Startups | Spike Diabetes applies social pressure to keep patients safe

Lemonade this morning revealed plans to expand into the European market. The news marks the first international expansion for the AI-powered insurance app, which launched in New York City in 2016.

The official announcement issued by the company is extremely light on details, with the promise to reveal more pertinent information — namely, which country will be the first on its list — “shortly.” Instead, the news is a bit of flag planting from the company, as it navigates the tricky international insurance waters.

It also notably comes a few months after the startup dropped a short-lived lawsuit alleging that German company Wefox had essentially reverse engineered the Lemonade model for ONE Insurance. “We intend to defend ourselves vigorously,” Wefox’s founder told TechCrunch at the time. “This lawsuit appears to be an attempt to bait the media into covering a non-issue.” Court filings showed that the suit was unceremoniously dropped.

For its part, Lemonade is positioning its global expansion among the list of some of tech’s most successful names in recent years.

“Whether in Chicago, Paris, or Singapore, today’s consumers listen to music on Spotify, ride with Uber, and stay with Airbnb. Great digital brands don’t stop at the water’s edge,” Lemonade CEO Daniel Schreiber said in a press release. “That’s why going global feels so natural for us: consumers are increasingly cosmopolitan, socially aware, and tech-native – everything Lemonade was built to be.”

The age of the digital startup has certainly afforded companies a more rapid path to international success, though the list of companies cited does, perhaps unintentionally point to some of the difficulties dealing with local regulations. And healthcare has enough complex nuances to put even song publishing to shame.

Source: Tech Crunch Startups | Insurance app Lemonade prepares for European expansion

Readdle launched its first app on the App Store ten years ago and recently celebrated 100 million downloads. Readdle’s Denys Zhadanov came to TechCrunch Disrupt to look back at the past ten years.

“I think it's about timing. Back in 2007 when the iPhone was launched for the first time, there was no app or no App Store,” Zhadanov said. “And then we got a call from Apple that said: ‘Hey guys, we're launching the App Store.’”

One of the reasons why Readdle ended up on Apple’s radar is that they started working on a solution to read books and documents even before the App Store. It was a web app and it was already listed on Apple’s website.

This web app alone attracted 60,000 users — again, that was before the App Store and with a small iPhone install base.

Today, Readdle has eight productivity apps. If you have an iPhone, chances are you’re using some of them, such as Scanner Pro, Documents, PDF Expert and Spark.

And it says a lot about Readdle’s skills. When you’re building productivity apps, you’re competing with built-in apps. There’s already a calendar app and an email app on your iPhone when you first set it up.

“The way we look at this, if our work can inspire one of the biggest companies to move into this area, we're doing something right,” Zhadanov said. “But we have to be very fast and move and run faster because there is no way you can compete with giants like Apple, Google and Microsoft.”

What’s next for Readdle now? The company has received acquisition offers in the past. “We've had offers from different partners but we never discuss and disclose publicly either these talks or our revenues because we're still private,” Zhadanov said.

But it doesn’t mean that Readdle is standing still. When Readdle released Spark four years ago, it was a free app from day one. Spark now has 500,000 daily active users.

“Now we're at this stage where we are trying to accomplish a much bigger challenge than ever before, which is reinventing email,” Zhadanov said.

You can now use Spark to share inboxes with your team. It lets you comment on an email thread, assign emails to team members and more. If you want to unlock all the collaborative features, you need to pay a premium subscription.

It’s still the very beginning of the team product. “I think we have thousands of teams but only tens or hundreds are paying,” Zhadanov said.

Eventually, Readdle could end up raising money to iterate faster — maybe, maybe not. “I'm not saying we need [to raise money ]. I'm saying we might raise money next year to scale faster,” Zhadanov said.

Being a bootstrapped company has some great advantages for now. Readdle doesn’t feel any pressure from investors saying that they need to launch something now. The company can spend more time refining products.

Finally, TechCrunch’s Ingrid Lunden asked about the political climate in Ukraine. A few days ago, a presidential decree introduced martial law in some parts of Ukraine due to tensions with Russia.

“We're trying not to comment on political issues as well. But, right now, we're not affected as a company, as a business,” Zhadanov said. "I think the perception from outside might be affected.”

According to him, Readdle has already thought about “plan B and plan C” in case it gets worse.

Source: Tech Crunch Startups | Looking back at Readdle’s journey from zero to hero

Bay Area-based robotic exoskeleton company Roam announced this morning that it has secured a $12 million series A. The round, led by Yamaha Motors, with investments from Boost VC, Heuristics Capital Partners, Menlo Ventures, R7 Partners, Spero Ventures, Valor Equity Partners and Venture Investment Associates, brings the company’s total funding up to around $15 million.

Investors are understandably bullish on the space, which has far-reaching implications for industrial workers and mobility. Of course, Roam’s got a fair bit of competition in the robotic exoskeleton category, including prominent names like Ekso and SuitX. So far, however, the company has looked to carve out a niche with a product focused on skiers.

The Elevate, first announced in March, will finally be available for demo rental over the Christmas holiday in select Lake Tahoe locations, followed by Park City, Utah over the Presidents’ Day holiday. This new round will go a ways toward boosting sales and marketing for the first product.

In addition to the funding, Yamaha partner Amish Parashar and Spero general partner Shripriya Mahesh will be joining Roam’s board of directors. Here’s the former on the deal, “By making these robotic exoskeletons affordable, scalable, and powerful Roam has removed the biggest barriers to widespread adoption. We envision these products will one day be commonly used to create new thrilling experiences and support human mobility.”

Source: Tech Crunch Startups | Robotic Exoskeleton company Roam raises a million Series A

Atomico, the London-based venture capital firm co-founded by Skype founder Niklas Zennström, has launched a new program to find, mentor and back the next generation of angel investors across various hubs in the European tech startup ecosystem.

Dubbed the Atomico Angel Programme, and unveiled on stage at TechCrunch Disrupt Berlin, the new initiative is headed up by newly promoted Atomico Partner Sophia Bendz, with support from Associate Will Dufton. Prior to joining Atomico she was an exec and early employee at Spotify, and has been a very active angel investor based in the Nordics over the last few years.

In a call last Friday, Bendz explained that the idea behind the program is to help “activate” a new generation of angel investors who Atomico believes are well-placed to discover “the most innovative and ambitious” founders just starting out, and to attract new people to angel investing sooner than might otherwise happen. More broadly, Atomico is always looking for new ways to help grow the ecosystem in Europe. A rising tide lifts all boats, after all.

“We are passionate about helping all of the ecosystems to flourish and this is one way of boosting them, and we’re also passionate about helping to activate the next generation of angels,” said Bendz. “And for me it has been such a rewarding journey doing angel investments, and there are more people out there with knowledge and capabilities, so this is a way for us to sort of help seed them in a way”.

The Atomico Angel Programme will run on a 12-month rolling basis, with 12 angels backed in the first cohort (full list published below). Each angel is given $100,000 to write multiple early-stage cheques. They remain entirely autonomous and who they choose to invest in is up to them, as long as it does not violate Atomico’s ethical investment principles and commitments to its LPs (i.e nothing “unethical” including drugs, alcohol, tobacco, firearms, and porn startups etc).

And of course angels get a share of the upside if or when the founders they back succeed, in the same way that Atomico does. To promote collaboration by angels in the program, Atomico is also allocating “pooled carry,” meaning that one company’s success benefits all the Atomico angels in the same cohort.

“It’s more relationships than transactions that matters for us, so this is a long-term play where we care about relationships with founders and talented and interesting people in our ecosystem,” said Bendz. “It’s a way for us to come closer to the grassroots community and we are always passionate about, you know, connecting and making sure people meet, so we can help being that connector and put the graduate community even closer to the old established institutions and the people that they want to meet”.

Interestingly, Atomico itself doesn’t do seed investments but backs companies one or two stages later at Series A and beyond, so the Angel Programme is very different from the angel scout networks typically operated by large VC firms in Silicon Valley that want to build a bridge to seed stage deal-flow.

It is also notable that, unlike some U.S. VCs, Atomico is making the initiative public from the get-go, offering a greater level of transparency. After all, there’s something rather odd about angel investors investing in young companies but unable to disclose where the money is actually coming from. That said, Atomico isn’t disclosing the exact split between Atomico, the angels in the program, and the pooled carry.

Another thing worth pointing out and the part that is arguably disruptive, albeit on quite a small-scale, is that the program has a chance to create angel investors that might never have the personal wealth to start investing, and therefore to diversify the angel ecosystem with fresh ideas and new, otherwise untapped investor talent. That’s because the program is targeting people who are not expected to have had a huge exit or even any exit at all. Right off the bat, the gender balance of the first cohort is better than any group of angels I’ve come across.

“What I’m excited about with this program is we are doing things a bit differently, we’re transparent about it and reaching a slightly different group of angels than the ones that are approached by the big firms in the Valley,” said Bendz. “These are more people that are operators, founders, co-founders. c-suite people, and some are great connectors with their feet down in the depths of the ecosystem, so we want to help them to do angel investments, maybe even sooner than what normally happens: People with great deal-flow that maybe haven’t had their own liquidity event”.

That’s not to say that there isn’t direct upside for Atomico. The firm makes no secret that it wants to find well-placed future angels in hard to reach “pockets” right across the often fragmented European ecosystem.

The first cohort is quite shrewdly filled with a number of known uber-connectors, such as former U.K. government advisor Rohan Silva and Station F’s Roxanne Varza. And whilst there is absolutely no guarantee that Atomico will go on to back any of the companies its newly activated angels choose to invest in, VC relationships often work best when they start early. Bendz also told me Atomico worked hard to find angels outside of its existing network.

To that end, the full list is as follows:

• Doreen Huber, Founder, LemonCat
• Suvi Haimi, Co-Founder, Sulapac
• Stefano Bernardi, Co-Founder, Token Economy
• Rohan Silva, Co-Founder, Second Home
• Clare Johnston, Founder, The Up Group
• Emily Brooke, Founder, Beryl
• Gregory Gazagne, Executive Vice President, Criteo
• Roxanne Varza, Director, Station F
• Josefin Landgård, Co-Founder, Kry
• Tuva Palm, Founder, Executive Tech Advisor
• Ritu Jain, Co-Founder, LifeX
• Johan Brand, Founding Partner, We Are Human

Source: Tech Crunch Startups | Atomico unveils Angel Programme to ‘activate’ the next generation of European investors

While Brexit’s effects are dominating headlines in the UK and around the globe, the nation’s startup industry should emerge from the chaos relatively unscathed, according to longtime European venture investor Saul Klein .

A former partner at Index Ventures (and an employee at Skype back in the day), Klein is on to his next act as an early-stage investor alongside his father, Robin (who is, himself, a famous early-stage investor in technology) at LocalGlobe. 

Onstage at TechCrunch Disrupt Berlin, Klein brushed off any potential impact that the exit of the UK from the European Union might have on startups and entrepreneurship for the country. Indeed, according to Klein, Britain’s startup kids are all right.

Given that roughly 85% of Klein’s portfolio at LocalGlobe is based in the UK, his take on Brexit’s potential impact better be right (for the sake of his fund).

But there’s data to back up Klein’s assertion of the ramifications of Brexit for the UK startup community. “We did a survey with a lot of other people in the ecosystem,” says Klein. “Only 9 percent of companies were thinking of moving. It hasn’t really changed behavior.”

From Klein’s perspective, industry observers need only look at the increasing capital commitments being made to UK startups. “[The] UK in 2016 had about $3.5 billion and the year after it had $7 billion or $8 billion. Venture is a 10- to 12-year bet. Anyone investing in the UK in 2017 and 2018 had heard of Brexit and priced that in.”

Beyond the current investments, the past indicators of Britain’s success loom large over the entire European startup industry. Roughly 40 percent of Europe and Israel’s unicorns hail from the UK and seven out of Europe’s top ten investment funds hail from the UK (based on the number of unicorns they’ve invested in), according to Klein.

Even immigration issues shouldn’t present a problem for Britain. “The UK is thinking about how do we get more highly skilled talent to the UK. Not less,” Klein says.

Source: Tech Crunch Startups | LocalGlobe co-founder Saul Klein says despite Brexit fears, the UK’s startup kids should be all right