What every startup founder should know about exits

Benjamin Joffe Contributor

Benjamin Joffe is a partner at HAX.

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• 70 years of VC innovation
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The dream of a startup founder can often be summarized by the following well-intentioned, and mostly delusional, quote: “We’ll raise a few rounds and in a few years we’ll IPO on Nasdaq.”

But a more likely scenario looks something like this:

You invest a few years of hard work to build something of value. One day you receive an acquisition offer out of the blue. You’re elated. And you’re not prepared. You drop everything to focus on this opportunity. Exclusive due diligence starts. Your company is a mess (IP, contracts, burn). Days become weeks; weeks become months. You’ve neglected business and fundraising. You’re running out of money. M&A is now your one and only option. The buyer says they found a bunch of cockroaches in the walls and drops the price. Now what?

Sounds unlikely?

This is still a favorable situation: you had an offer! Think about how much time you invested in your various funding rounds. The hundreds of names and Google spreadsheet or Streak-powered quasi-CRM process.

Have you spent even a fraction of that on understanding exit paths? If you’d rather not live the situation described above, read along.

The E-word: A strange taboo

Investors live by exits, but many founders keep dreaming of unicornization and avoid the “E-word” until it’s too late. Yet, in 2016, 97% of exits were M&As. And most happened before series B.

Exits matter because that’s when you, your team and your investors get paid. Oddly enough, and to use a chess metaphor, we hear a lot about the “opening game” (lean startup), the “mid-game” (growth) but very little about this “end game”.

As a result, founders miss opportunities or leave money on the table. This is a shame. Our fund, SOSV, has over 700 companies in portfolio. We want the best possible exit for each of them. And fortune favors the prepared! Now, how to get 700 exits (and counting)?

To explore the topic, organized a series of Masterclasses tapping corporate buyers, bankers, investors, lawyers, and startup CEOs with M&A or IPO experience in San Francisco. It was a group that included the founders of Guitar Hero — bought by Activision; JUMP Bikes — a SOSV portfolio company bought by Uber, Ubiquisys  — bought by Cisco, and Withings — bought by Nokia. Each one for hundreds of millions).

Their observations can be summarized below.

Maximize optionality

“Founders must be aware of what contributes to an exit. This means understanding partnerships and how they are formed in the business space the entrepreneur is working in,” said one MasterClass participant.  

As founders, you build your product, your company and… optionality. You need to understand the options open to your company, and take steps to enable them.

The most likely one is an acquisition but there are others like IPO (including small cap), RTO, SBO, LBO, Equity Crowdfunding and even ICO.

“Exit is not a goal ​per se, but as a CEO it is something you should think about as early in your cycle as possible, while being business-focused,” said the London-based investor Frederic Rombaut, of Seraphim Capital.

Indeed, most participants said that exits should always be on the chief executive’s agenda, no matter how early in the process. “Exits should be on the CEO agenda. Not front and center, but on the agenda. M&A is a by-product of a great business and targeted BD. IPOs are always an option once you’ve built significant cashflow forecasting.”

It’s important to ask questions like: How many “strategic engagements” with potential buyers have you had this month? Is your message and value clear in their eyes? Have you considered an acquisition track in parallel to a fundraise?

It doesn’t stop there:

• Equity crowdfunding might help close some gaps at seed stage.
• Early IPOs on smaller exchanges can be an option to raise over $10M — the robotics startup Balyo went public and raised 40MEUR on Euronext to get rid of a critical ‘right of first refusal’ option held by one of its corporate investors.
• Reverse mergers can work too: the medical exoskeleton company EKSO Bionics went public this way.

One thing is sure: the time to exit is not when you’re running out of money.

Companies are bought, not sold

Unicorn or not, the most likely exit is an acquisition.

As George Patterson, Managing Director at HSBC in New York said, “Good tech companies are bought, not sold. The question is thus: how to get bought?”

Patterson says it’s important to understand how mergers and acquisitions actually work; how to prepare a startup for an exit; and how to develop a “feel” for the market you’re exiting through and into. ;

How M&A works

Hearing from corp dev veterans from Cisco, Logitech, Dassault and IBM, a few key ideas emerged:

Motivations vary

It could be (from least to most expensive, or as a mix), as listed by Mark Suster, Managing Partner at Upfront Ventures:

1. Talent hire ($1M/dev as a rule of thumb — location matters)
2. Product gap
3. Revenue driver
4. Strategic threat (avoid or delay disruption)
5. Defensive move (can’t afford a competitor to own it)

How corporates find you

Corporates find deals via the development of partnerships, investment (CVC), their business units, corp dev research, media, and investor connections.

Asked about the best approach, Todd Neville, Manager of Corporate Business Development and Strategy at IBM (who gave the most detailed description of the corp dev process), said, “Do something cool to one of the IBM customers. If they rave about even a POC, we’re interested.”

In other words, business development is corporate development. 

Get the house in order

Buyers typically want to know three things:

1. Is your IP really yours?
2. Is your team capable?
3. Will your customers stick around?

For IP, they will check your contracts (staff and contractors), run some automated code analysis for proprietary code and open source use. They will evaluate potential IP infringement. No point buying you if you end up costing more in lawsuits!

For your team skills: sitting down with your engineers will tell them plenty enough without understanding the details of this or that algorithm. Be sure the last thing a corporate wants is to be accused of stealing!

Lawyers engaged early can help. The later the clean-up, the more costly and painful.

Develop a feel for your “market”

Develop relationships and create champions within corporates. It will help promote your deal when the time comes, and will let you keep your finger on the pulse of corporate strategy to time your moves.

Do you read the earning calls of Cisco or IBM (or others relevant to you)? This is where strategies are presented. Are your keywords coming up there or in their press releases?

Chris Gilbert, former CEO of Ubiquisys (sold to Cisco for over $300M) was very deliberate in planning his exit.

“Selling start on day one and is a leadership-only function — work out who will be your buyer. Only the CEO can do this. Constantly articulate why a company should buy you,” Gilbert said. Bring clear messages into the acquiring company so it can be presented upwards: give them the presentation you would like them to show their boss! When the time is right, force decisions through competition. If you know they have to buy you, your starting position is strong.”

The dark art of price discovery

There are dozens of formulas (from DCF to comparables) to evaluate a deal  —  which also means none is ‘correct’. What matters is: how much would you sell for, and how much is the buyer ready to pay?

Gilbert, at Ubiquisys, described how close interactions with his banker helped drive the price up among the bidders assembled.

Just like buyers, we meet bankers and lawyers too rarely at startup events, but there is much to learn with them. They make deals happen, avoid value erosion and optimize price. They often also make introductions before you engage them, to build goodwill and earn your business.

And if you worry about fees, the right banker handsomely pays for itself by finding more bidders, and playing “bad cop” for you, avoiding direct confrontation with your future employer. Do you want a slice of the watermelon or the whole grape?

Final twist: Exits are not exits

When asked about what happens after an M&A or IPO, buyers said that they generally hoped the founders would stay with them for many years. Often using re-vesting, earn-outs or shares of the acquiring company to incentivize them. Neville, from IBM, mentioned a security company they acquired whose founder is now the head of one of the largest IBM divisions.

In the case of IPOs, supposedly the ultimate “exit”, any block of shares sold by founders would face extreme scrutiny and might cause a price drop.

So who’s exiting during those deals? Investors (and not always).

Eventually, if the average age of a startup at exit is 8–10 years, the active duty period of founders (if not replaced in the meantime) extends even more. Better love the problem you’re solving, and your customers!

Thanks to speakers, participants and supporters of this Masterclass series:

London: Frederic Rombaut (Seraphim Capital), Joe Tabberer (FirstBank), Chris Gilbert (Ubiquisys), Jonathan Keeling (Crowdcube), Fred Destin, Tony Fish (AMF Ventures, James Clark (London Stock Exchange), Denise Law (SGCIB).

Paris: Frederic Rombaut (Seraphim Capital), Manuel Gruson (Dassault Systemes), Pierre-Henri Chappaz (Rothschild Global Advisory), Christine Lambert-Goue (All Invest), Olivier Younes (EXPEN), Eric Carreel (Withings), Fabien Bardinet (Balyo), Xavier Lazarus (Elaia Partners), Pierre-Eric Leibovici(Daphni). Jean de La Rochebrochard (Kima Ventures), Jeremy Sartre (SmartAngels), Gwen Regina Tan (Entrepreneur First).

San Francisco: Natasha Ligai (Logitech), Matt Cutler (Cisco),Will Hawthorne, (CODE Advisors), Ryan Rzepecki (JUMP Bikes), Charles Huang (Guitar Hero), Jeff Thomas (Nasdaq), Shahin Farshchi (Lux Capital), Ammar Hanafi (Moment Ventures), Adam J. Epstein (Third Creek Advisors), Nathan Harding (EKSO Bionics), Kate Whitcomb, Anthony Marino and Ethan Haigh (SOSV).

New York: Todd Neville (IBM), George Patterson (HSBC), Ryan Rzepecki (JUMP Bikes), Aaron Kellner (SeedInvest), Jeremy Levine (Bessemer Venture Partners), Taylor Greene (Collaborative Fund), Adam Rothenberg (BoxGroup), Eli Curi (Fenwick & West), Ian Engstrand and Salil Gandhi (Goodwin), Warren Spar(Sparring Partners Capital), Duncan Turner, Vivian Law and Sheng Ge (SOSV).

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Autonomous-aviation startup Xwing takes flight with $4 million in funding

Marc Piette had a revelation as he buzzed in and out of the Palo Alto Airport in pursuit of his pilot’s license. Instead of freedom, he saw restraint. He also saw potential.

“It became pretty apparent that there were major issues with the general aviation industry with smaller aircraft,” Piette said in a recent interview with TechCrunch. “And yet it had enormous potential to change the way people moved around.”

Now, Piette’s two-year-old autonomous-aviation startup Xwing is ramping up to unlock that potential. The company isn’t building autonomous helicopters and planes. Instead, it’s focused on the software stack that will enable pilotless flight of small passenger aircraft.

The company announced Tuesday that it has raised $4 million in a seed round led by Eniac Ventures. Array Ventures, along with Stripe founders John and Patrick Collison and Nat Friedman of Xamarin, Microsoft and GitHub, also participated in the round.

The funding will be used by the San Francisco-based company to scale operations and continue to hire aerospace and software talent.

The startup has about a dozen employees, including some uniquely talented folks who have experience with optionally piloted vehicles, unmanned systems and certified avionics. For example, the company’s CTO, Maxime Gariel, worked on autonomous-aviation projects such as DARPA Gremlins and the AgustaWestland SW4 Solo autonomous helicopter. Other members of the small team previously worked at Rockwill Collins, with the Naval Research Lab, Google, and McKinsey.

Piette, whose last company Locu was acquired by GoDaddy, sees several restraints to small passenger aircraft: the skill level required to fly a plane and the cost of earning a pilot’s license and accessing a plane. The relatively puny sales volume of small aircraft — just 3,293 general aviation aircraft, including helicopters, were delivered last year worldwide, in contrast to more than 80 million cars — has depressed innovation and kept prices high.

And even when people have both a license and an aircraft, they still must travel from a small airport to their final destination.

The company is focusing on the key functions of autonomous flight, such as sensing, reasoning and control.

Xwing isn’t pinned to one kind of aircraft. Piette said the system is designed to work across different kinds of aircraft. For instance, the company spent 18 months testing on a subscale fixed-wing aircraft. It tested on a helicopter more recently.

Xwing is developing and integrating those technologies for rotorcraft, general aviation fixed-wing and the emerging electric vertical takeoff and landing (known as eVTOL) aircraft.

The company’s sensor integration software enables aircraft to perceive the world around it and reliably detect ground-based and airborne hazards and precisely determine the vehicle’s position.

This perception technology is the building block for autonomous aircraft, and also can be used to increase the operational envelope of current-day piloted aircraft, according to Xwing.

From here, the company’s Autonomy Flight Management System (AFMS) allows the aircraft to act upon the information from its surroundings. The system will integrate with air traffic control, generate flight paths to navigate the airspace, monitor system health and address all contingencies to ensure passenger safety, the company says.

Now, Xwing is in discussion with various, and still unnamed, large companies about integrating the system into their aircraft.

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CallPage lets you call your website visitors

Poland-based CallPage offers something other customer interaction apps don’t: the ability to call your website visitors as soon as they click on your page. In a world where the difference between a sale and a click past your site onto Facebook, this is a pretty cool little feature.

CallPage began in 2015 when the founders, Ross Knap, Sergey Butko, and Andrew Tkachiv, tried to figure out why website visitors would leave their sites. They started out as a consultancy and the product was born out of some after-hours tinkering by the team. Instead of messaging users, they thought, why not let managers talk to them on the phone?

“Our widget analyzes user behavior on your website,” said CEO Knap. “Then when it sees an interested visitor, it offers him a free callback in 28 seconds. The interested visitor leaves a phone number on your site, our widget calls to the first available manager’s mobile phone and then the next one if no one picks up. After the conversation client will receive an SMS of thanks. It doesn’t require any extra work.”

The team raised a $4.5 million Series A from TDJ Pitango Ventures, Innovation Nest, and Market One Capital. They have 3,000 customers and it makes 280,000 calls monthly. The team started with a $50,000 seed check from an early investor.

Knap and the team have big plans.

“CallPage will continue the realization of our development plan,” said Knap. “The company is going to change into a product more from the perspective of ‘All your company calls in one place.’ The R&D department have already started working on using machine learning and AI which allows analyzing of hundreds of thousands of calls through the CallPage system. Thanks to this, companies will be able to run their communications more effectively.”

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Discord’s Jason Citron to chat it up at Disrupt SF

In September of 2013, Jason Citron hopped on to the Disrupt Startup Battlefield stage to pitch Fates Forever, a multiplayer online battle arena game for the iPad. Now, five years later, Citron is gearing up to join us once again on the Disrupt stage to discuss the stellar growth of Discord.

Though Fates Forever had all the components to be a great mobile game, users simply never took much interest. The company struggled to monetize, and like any good startup, the team began to reassess its own situation.

The conversation turned to communication, where the space contained a few players with lack-luster products.

“Can we make a 10X project?,” said CMO Eros Resmini, relaying the tale of the company’s pivot to TechCrunch. “Low-friction usage, no renting servers, beautiful design we took from mobile.”

That’s how Discord was born. The platform launched in 2016, and has since grown to 90 million registered users, and has raised nearly $80 million in funding.

Coming from the publishing side, the Discord team had a keen awareness of what gamers want and need: a clean, secure communications platform. Since launch, the team has launched features that let game developers integrate Discord chat into their own games, as well as video-chat and screen-sharing.

But the progress has not been without discord. The company shut down several servers associated with the alt-right for violating the terms of service, bringing Discord to the center of the on-going conversation around censorship and political bias.

That said, Discord has seemed to find its stride, forming partnerships with various esports organizations for verified servers.

There is plenty to discuss with Jason Citron at Disrupt SF, and we hope you’ll join us to check out the conversation live.

The full agenda is here. Passes for the show are available at the early-bird rate until August 1 here.

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Skyline AI raises $18M Series A for its machine learning-based real estate investment tech

Skyline AI founders Iri Amirav, Or Hiltch, Guy Zipori and Amir Leitersdorf

A mere four months after coming out of stealth mode with $3 million in seed funding, real estate investment startup Skyline AI announced that it has raised an $18 million Series A. The round was led by Sequoia Capital, a returning investor, and TLV Partners, with participation from JLL Spark, a division of real estate investment management firm JLL. The strategic funding will allow Skyline AI to add more asset classes to its platform, which uses data science and machine learning algorithms to help institutional investors make better decisions about properties.

Skyline AI says its technology is trained on what it claims is the most comprehensive data set in the industry, drawing from more than 100 sources, with market information covering the last 50 years. Its technology is meant to provide faster and more accurate analysis than traditional methods, so investors can react more quickly to changes in the real estate market.

Co-founder and CEO Guy Zipori told TechCrunch in an email that the startup decided to raise its Series A so soon after coming out of sleath because of positive response from investors, adding that the round was oversubscribed. “The timing of the round also worked out perfectly with our current deal flow and expansion plans. The round was significant, putting us in a great position to move forward,” he said.

Skyline AI has had a busy few months since emerging from stealth. In June, it teamed up with an unnamed partner in the U.S. to acquire two residential complexes in Philadelphia for $26 million. Zipori said they decided to make an unsolicited offer after Skyline AI’s platforms determined the properties were being mismanaged. Then in July, Skyline AI announced a partnership with Greystone, a real estate lending, investment and advisory firm, to collaborate on improving the dealmaking and loan underwriting processes.

JLL and other strategic investors in Skyline AI’s Series A will allow the startup to add analysis and underwriting for new asset classes, including industrial, retail and office properties, to its platform. “This in turn will enable us to deepen and strengthen cooperation with the leading commercial real estate investment firms across the U.S.,” said Zipori. Some of the capital will also be spent on growing its research and development, data science and AI teams in Tel Aviv, and its recently opened sales and real estate office in New York.

In a press statement, Sequoia Capital partner Haim Sadger said “Over the last few years, we’ve seen AI disrupt a number of traditional industries and the real estate market should be no different. The power of Skyline AI technology to understand vast amounts of data that affect real estate transactions, will unlock billions of dollars in untapped value.”

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Athena Club offers a cheaper way to prepare for your next period

For those of us unlucky enough to be forced to accommodate mother nature’s whims on a monthly basis, you know that — in addition to cramps, headaches and mood swings — it can be a challenge to find time in your schedule to buy the period products you need.

Desperate trips to the pharmacy when disaster hits can suffice, but the co-founders of the tampon subscription service Athena Club, Maria Markina and Allie Griswold, thought there had to be a better way to provide women the products they need in a cheap and empowering way.

“We’ve both had our fair share of tampon war stories,” Griswold told TechCrunch. “It’s something that every woman goes through at some point in her life and it’s a universal problem that we wanted to make easier. There are so many other amazing things that women can and should be doing than worrying about [where to get tampons] every month.”

Athena Club launches today after receiving $3.8 million in seed funding led by Henry Kravis of KKR. The company currently offers two tampon types (Premium and Organic) and a variety of absorbances (ranging from light to super+ for its Premium product and regular to super for its Organic one). The company also has plans to expand its products into pads and liners as the brand progresses.

In each order, customers can decide how many bags they need (each reusable bag includes 18 tampons), what type of tampon and what mix of absorbances they want, and how frequently they need them delivered. A selection of its Premium tampons cost $6.50/bag and its Organic selections are $7.50/bag.

For the founders, this level of customization was an important part of giving women autonomy over their periods.

“[We chose] the name Athena Club because we believe Athena is a really strong, fearless, independent woman and we’re very excited to bring that essence to our brand.” said Griswold. “Like Athena, women today have many passions and talents. They can’t all fit into one box and we want to provide [the option] to find the right customized package that works for their body.”

Athena Club also recognizes that for some women, access to tampons and period products is more than just a nuisance but a critical health issue. To help provide security and education surrounding periods and women’s health to women in need, Athena Club is committed to supporting groups like Period.org and Support the Girls. To date, Athena Club has already donated 10,000 tampons to women in need through Period.org and has plans to continue that support on a yearly basis.

Athena Club is joining a fairly crowded feminine care subscription space, but the founders say that its price point will help it stand apart from the crowd. Tampon subscription companies like LOLA offer a subscription plan priced at $10/box for 18 plastic applicator tampons (the same type and count as Athena Club) and Cora offers 18 tampons for $13/box. Other more extravagant boxes, like Hello Flo incorporate add-ons like chocolate or underwear in their boxes and can be priced upwards of $40.

And, all of these models are up against long-term, reusable period solutions like Thinx period underwear (which can cost up to $39 for two tampons worth of absorption per use) and plastic menstrual cups like the Diva Cup (which retails for $40.99.)

With so many options, Athena Club presents itself as the cheap, no-fuss solution for women who are through letting periods disrupt their lives.

 

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Tractable is applying AI to accident and disaster appraisal

“Happy to spend 10 minutes on our vision and the journey we’re on, but then, really, 15 minutes on what we’ve got today, what it is we’ve achieved, what it is our AI does,” says Tractable co-founder and CEO Alexandre Dalyac when I video called him a couple of weeks ago. “You can probably speed up all of that,” I quip back.

The resulting conversation, lasting well over an hour, spanned all of the above and more, including what is required to build a successful AI business and why he and his team think they can help prevent another “AI winter.”

Founded in 2014 by Dalyac, Adrien Cohen and Razvan Ranca after going through company builder Entrepreneur First, London-based Tractable is applying artificial intelligence to accident and disaster recovery. Specifically, through the use of deep learning to automate visual damage appraisal, and therefore help speed up insurance payouts and access to other types of financial aid.

Our AI has already been trained on tens of millions of these cases, so that’s a perfect case of us already having distilled thousands of people’s work experience Alexandre Dalyac

Dalyac launches into what is clearly a well-rehearsed and evidently polished pitch. “We are on a journey to help the world recover faster from accidents and disasters. Our belief is that when accidents and disasters hit, the response could be 10 times faster thanks to AI. So what we mean there is, everything from road accidents, burst piping to large-scale floods and hurricane. Whenever any of these things happen, things get damaged.”

Those things, he says, broadly break down into cars, homes and crops, roughly equating to $1 trillion in damage each year. But, perhaps more importantly, livelihoods get impacted.

“If a car gets damaged, mobility is reduced. If a home gets damaged, shelter is reduced. And if crops get damaged, food is reduced. Across all of those accidents and disasters, we’re talking hundreds of millions of lives affected.”

It is here where a little lateral (and non-artificial) thinking is required. Accident and disaster recovery starts with visual damage appraisal: look at the damage, say how much it’s going to cost, unlock the funds and rebuild. The problem (and Tractable’s opportunity) is that having an appraiser look at a car, house or field can take days to weeks depending on availability — and therefore so can accessing funds to start rebuilding — whereas the claim is that computer vision and AI technology can potentially do the same job in minutes.

“When you assess, that is basically a very powerful but very narrow visual task, which is, look at the damage, how much is it gonna cost? Today, as you can imagine, these kind of assessments are manual. And they take days to weeks. And so you instantly know that with AI that can be 10 times faster,” says Dalyac.

“In some sense this is a perfect class of AI tasks, because it’s very heavy on image classification. And image classification is a task where AI can surpass human performance as of this decade. If you have instant appraisal, that means faster recovery. Hence the mission.”

Dalyac says that part of Tractable’s secret sauce is in the many millions of proprietary labels the company has produced. This has been aided by its patented “interactive machine learning technology,” which allows it to label images faster and cheaper than typical labeling services.

The team’s focus to date has been to train its AI to understand car damage, technology it has already deployed in six countries, seeing the startup work primarily with insurers.

Related to this I’m shown a simple demo of Tractable’s car damage appraisal tool. Dalyac opens a folder of car images on his laptop and uploads them to the software. Within seconds, the AI has seemingly identified the different parts of the car and determined which parts can be repaired and which parts need to be entirely written-off and therefore replaced fully. Each has an AI-generated estimated cost.

It all happens within a matter of minutes, although I have no way of knowing how difficult the pre-determined and fully controlled task is. It’s also unclear how an AI can possibly do the full job of a human assessor based on a limited set of 2D images alone, and without the ability to peek under the hood or undertake further investigations.

“We’re trying to figure out how much damage there is to a vehicle based on photos,” explains Dalyac. “There’s some really tough correlations to pick out, which are: based on the photos of the outside, what’s the internal damage? When you’re a human you are going to have seen and torn down maybe about a thousand to two thousand cars in your whole life of 20 or 30 years of doing that. Our AI has already been trained on tens of millions of these cases, so that’s a perfect case of us already having distilled thousands of people’s work experience. That allows us to get hold of some very challenging correlations that humans just can’t do.”

You need to find real-world use cases that will make a difference, where you can surpass human performance Alexandre Dalyac

With that said, he does concede that a photo doesn’t always contain all of the necessary information, and that it might only have a certain level of accuracy. “You might need to then get a tear-down of the car and get photos of the internal damage. You might even want to get some data from the dashboard. And you can think that as cars get more sensors… the appraisal will be not just visual but also based on IoT data. But that doesn’t detract from the fact that we are convinced that it will be AI that will be doing this entirely.”

What is abundantly clear is Dalyac’s commitment to developing AI technology with real-world use that is commercially viable. If that doesn’t happen, he believes it won’t just be Tractable that will suffer, but the continued belief and investment in AI as a whole. Here, of course, he’s talking about the prospect of another so-called “AI winter,” citing a recent Crunchbase report that says funding for artificial intelligence companies in the U.S. has levelled off and even started to decline at seed stage.

“If you’re trying to make the $15 billion that has been invested into AI not fuck up and lead to something successful that will prevent an AI winter that will lead to continuous improvement, you need a really good return on that asset class. And for that you need those businesses to be successful.

“To make an AI company successful, really successful — not just an acqui-hire, not just an IP exit but a real commercial success that’s going to prevent an AI winter — you need to find real-world use cases that will make a difference, where you can surpass human performance, where you can change the way things work,” he says.

The reference to acqui-hire or IP exit takes on more meaning when you consider that Tractable was in the same cohort at Entrepreneur First as Magic Pony Technology, the AI startup acquired by Twitter for up to $150 million for its image enhancing technology. And most recently, the team behind Bloomsbury AI, another EF company, was acqui-hired by Facebook for $20-30 million.

To ensure that Tractable can continue its mission of applying AI to accident and disaster recovery — and presumably not sell too early — the startup has closed $20 million in Series B investment in a round led by U.S. venture capital firm Insight Venture Partners. Existing investors, including Ignition Partners, Zetta Venture Partners, Acequia Capital and Plug and Play Ventures, also participated. The new capital is to be spent on accelerating growth, expanding its research and development and entering new markets.

(The Series B also included an additional $5 million in secondary funding, seeing some investors at least partially exit. I understand Tractable’s founders sold a relatively small number of shares as they were permitted to take money off the table. Dalyac declined to comment.)

As we wrap up our call, I note that all of Tractable’s main investors, not including EF, are from the U.S. — something Dalyac says was a deliberate decision after he discovered the gulf between European and U.S. valuations.

“That’s a shame, isn’t it?” I say with my European tech ecosystem hat on.

“It isn’t; it’s enormous exports for the U.K.,” says the Tractable CEO who is French-born but raised in the U.K. “We have, as of today, the vast majority of our headcount in London. The entire product team is in London. The entire R&D team is in London. But most of the revenue comes from the United States. We are making AI an export industry of the U.K.”

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Optoro raises $75 million more to make it easier for brands to manage and resell returned and excess inventory

As the economy has chugged along, so have retail sales, which last year capped their strongest year since 2014. Online sales have been especially brisk, growing 16 percent between 2016 and 2017 alone, according to the U.S. Commerce Department, which estimates that consumers spent $453.5 billion online last year.

Of course, with every booming market comes supporting cast members that benefit. Such is the case with eight-year-old, Washington, D.C.-based Optoro, which itself just rang up $75 million in new funding. A logistics company, Optoro’s software helps retailers — both online and off — more easily re-sell inventory that has been returned by customers.

That’s a big number. The overall amount of merchandise returned as a percent of total sales last year was 10 percent in 2017, according to the National Retail Federation. In dollars, that’s $351 billion.

Right now, that includes sales from big box retailers and many other “legacy” companies that allow shoppers to buy items — and return them — in their stores. But as online sales rise, so do online returns. Indeed, Optoro co-founder and CEO Tobin Moore tells the WSJ that the “return rate from e-commerce sales is two to three times the return rate of brick-and-mortar” and “sometimes higher in fashion and apparel.” And with most retailers also paying for shipping on returns — after all, a happy customer is a repeat customer — it’s a major logistics cost for these online brands.

Little wonder that Optoro, which uses data analytics and multi-channel online marketing to determine the best path for each item (ostensibly maximizing recovery and reducing environmental waste in the process) is a hit with a growing base of customers.

A growing number of investors is getting behind the company, too. Optoro’s newest round was led by Franklin Templeton Investments, but the company has now raised at least $200 million altogether, including from Revolution Growth, Generation Investment Management, Grotech Ventures and even the UPS Strategic Enterprise Fund.

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A pickaxe for the AI gold rush, Labelbox sells training data software

Every artificial intelligence startup or corporate R&D lab has to reinvent the wheel when it comes to how humans annotate training data to teach algorithms what to look for. Whether its doctors assessing the size of cancer from a scan or drivers circling street signs in self-driving car footage, all this labeling has to happen somewhere. Often that means wasting six months and as much as a million dollars just developing a training data system. With nearly every type of business racing to adopt AI, that spend in cash and time adds up.

LabelBox builds artificial intelligence training data labeling software so nobody else has to. What Salesforce is to a sales team, LabelBox is to an AI engineering team. The software-as-a-service acts as the interface for human experts or crowdsourced labor to instruct computers how to spot relevant signals in data by themselves and continuously improve their algorithms’ accuracy.

Today, LabelBox is emerging from six months in stealth with a $3.9 million seed round led by Kleiner Perkins and joined by First Round and Google’s Gradient Ventures.

“There haven’t been seamless tools to allow AI teams to transfer institutional knowledge from their brains to software” says co-founder Manu Sharma. “Now we have over 5000 customers, and many big companies have replaced their own internal tools with Labelbox.”

Kleiner’s Ilya Fushman explains that “If you have these tools, you can ramp up to the AI curve much faster, allowing companies to realize the dream of AI.”

Inventing The Best Wheel

Sharma knew how annoying it was to try to forge training data systems from scratch because he’d see it done it before at Planet Labs, a satellite imaging startup. “One of the thing that I observed was that Planet Labs has a superb AI team, but that team had been for over 6 months building labeling and training tools. Is this really how teams around the world are approaching building AI?” he wondered.

Before that, he’d worked at DroneDeploy alongside Labelbox co-founder and CTO Daniel Rasmuson who was leading the aerial data startup’s developer platform. “Many drone analytics companies that were also building AI were going through the same pain point” Sharma tells me. In September, the two began to explore the idea and found that 20 other companies big and small were also burning talent and capital on the problem. “We thought we could make that much smarter so AI teams can focus on algorithms” Sharma decided.

Labelbox’s team Co-founders: Ysiad Ferreiras (third from left), Manu Sharma (fourth from left), Brian Rieger (sixth from left), Daniel Rasmuson (seventh from left)

Labelbox launched its early alpha in January and saw swift pickup from the AI community that immediately asked for additional features. With time, the tool expanded with more and more ways to manually annotate data, from gradation levels like how sick a cow is for judging its milk production to matching systems like whether a dress fits a fashion brand’s aesthetic. Rigorous data science is applied to weed out discrepancies between reviewers’ decisions and identify edge cases that don’t fit the models.

“There are all these research studies about how to make training data” that Labelbox analyzes and applies, says co-founder and COO Ysiad Ferreiras, who’d led all of sales and revenue at fast-rising grassroots campaign texting startup Hustle. “We can let people tweak different settings so they can run their own machine learning program the way they want to, instead of being limited by what they can build really quickly.” When Norway mandated all citizens get colon cancer screenings, it had to build AI for recognizing polyps. Instead of spending half a year creating the training tool, they just signed up all the doctors on Labelbox.

Any organization can try Labelbox for free, and Ferreiras claims hundreds of thousands have. Once they hit a usage threshold, the startup works with them on appropriate SAAS pricing related to the revenue the client’s AI will generate. One called Lytx makes DriveCam, a system installed on half a million trucks with cameras that use AI to detect unsafe driver behavior so they can be coached to improve. Conde Nast is using Labelbox to match runway fashion to related items in their archive of content.

The big challenge is convincing companies that they’re better off leaving the training software to the experts instead of building it in-house where they’re intimately, though perhaps inefficiently, involved in every step of development. Some turn to crowdsourcing agencies like CrowdFlower, which have their own training data interface, but they only work with generalist labor, not the experts required for many fields. Labelbox wants to cooperate rather than compete here, serving as the management software that treats outsourcers as just another data input.

Long-term, the risk for Labelbox is that it’s arrived too early for the AI revolution. Most potential corporate customers are still in the R&D phase around AI, not at scaled deployment into real-world products. The big business isn’t selling the labeling software. That’s just the start. Labelbox wants to continuously managage the fine-tuning data to help optimize an algorithm through its entire lifecycle. That requires AI being part of the actual engineering process. Right now it’s often stuck as an experiment in the lab. “We’re not concerned about our ability to build the tool to do that. Our concern is ‘will the industry get there fast enough?'” Ferreiras declares.

Their investor agrees. Last year’s big joke in venture capital was that suddenly you couldn’t hear a startup pitch without ‘AI’ being referenced.. “There was a big wave where everything was AI. I think at this point it’s almost a bit implied” says Fushman. But it’s corporations that already have plenty of data, and plenty of human jobs to obfuscate, that are Labelbox’s opportunity. “The bigger question is ‘when does that [AI] reality reach consumers, not just from the Googles and Amazons of the world, but the mainstream corporations?”

Labelbox is willing to wait it out, or better yet, accelerate that arrival — even if it means eliminating jobs. That’s because the team believes the benefits to humanity will outweigh the transition troubles.

“For a colonoscopy or mammogram, you only have a certain number of people in the world who can do that. That limits how many of those can be performed. In the future, that could only be limited by the computational power provided so it could be exponentially cheaper” says co-founder Brian Rieger. With Labelbox, tens of thousands of radiology exams can be quickly ingested to produce cancer-spotting algorithms he says studies show can become more accurate than humans. Employment might get tougher to find, but hopefully life will get easier and cheaper too. Meanwhile, improving underwater pipeline inspections could protect the environment from its biggest threat: us.

“AI can solve such important problems in our society” Sharma concludes. “We want to accelerate that by helping companies tell AI what to learn.”

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Body scanning app 3DLOOK raises $1 million to measure your corpus

3D body scanning systems have hit the big time after years of stops and starts. Hot on the heels of Original Stitch’s Bodygram, another 3D scanner, 3DLOOK, has entered into the fray with a $1 million investment to measure bodies around the world.

The founders, Vadim Rogovskiy, Ivan Makeev, and Alex Arapovd, created 3DLOOK when they found that they could measure a human body using just a smartphone. The team found that other solutions couldn’t let them measure fits with any precision and depended on expensive hardware.

“After more than six years of building companies in the ad tech industry I wanted to build something new which was not a commodity,” said Rogovskiy. “I wanted to overcome growth obstacles and I learned that the apparel industry had mounting return problems in e-commerce. 3DLOOK’s co-founders spent over a year on pure R&D and testing new approaches and combinations of different technologies before creating SAIA (Scanning Artificial Intelligence for Apparel) in 2016.”

The team raised $400,000 to date and most recently raised a $1 million seed round to grow the company.

The team also collects “fit profiles” and is able to supply these profiles based on “geographic location, age, and gender groups.” This means that 3DLOOK can give you exact sizes based on your scanned measurements and tell you how clothes will fit on your body. They have 20,000 profiles already and are working with eight paying customers and five large enterprise systems. Lemonade Fashion and Koviem are both using the platform.

“3DLOOK is the first company that managed to build a technology that allows capturing human body measurements with just two casual photos, and plans to disrupt the market of online apparel sales, offering brands and small stores an API for desktop and SDK for mobile to gather clients measurements and build custom clothing proposals,” said Rogovskiy. “Additionally, the company collects the database of human body measurements so that brands could build better clothing for all types of body and solve fit and return problems. It will not only allow stores to sell more apparel, it will allow people get the quality apparel.”

3D scanners have gotten better and better over the years and it’s interesting to see companies being able to scan bodies just from a few photos. While these things can’t account for opinions of taste they can definitely make sure that your clothes fit before you order them.

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Interior Define, the custom furniture startup, opens new location in SF

The direct-to-consumer space has some stand-out players, both in newcomers like Brooklinen and old-timers like Warby Parker. But one company, Interior Define, has maintained a low profile over the four years of its existence.

The company offers fully customizable furniture, including couches, dining sets and bed frames, to customers through an online showroom. But ID also has guide shops in Chicago (its home market), LA, New York, and Austin.

Interior Define has also just opened up its biggest retail location yet, right in the middle of Hayes Valley in San Francisco. And this time, the store has a twist.

In the back of the showroom, Interior Define has built out a fully furnished two-story home called Studio ID. Alongside its own pieces, Studio ID includes pieces and products from other digitally native partners including Wright Bedding, Gantri, Snowe Home, Barn & Willow, 57st Design, Revival Rugs, Minted, Fireclay Tile, and Sonos.

The idea here is to show off ID’s pieces in their most natural setting, alongside offering partner companies better exposure via offline retail.

[gallery ids="1682684,1682685,1682686,1682687,1682688"]

According to Interior Define cofounder and CEO Rob Royer, there is no exchange of cash for these partnerships.

Royer also told TechCrunch that San Francisco has been a priority market for the company for a while, but that the startup insisted on finding a great place within Hayes Valley, and waited until they found this newest location to move into the market.

When Interior Define first launched, the company simply sold customizable sofas. Users could choose the upholstery, the measurements, and the accents like sofa legs. The company has since expanded into dining sets and bed frames, but has also enhanced the overall experience with an Interior Define app.

The app lets users scan the floor of their home and place the item they’re customizing into the home via augmented reality. Interior Define also took a page out of the Warby Parker playbook, offering a free swatch program for users interested in purchasing online.

Interior Define has raised a total of $27.2 million from investors such as Fifth Wall, Pritzker Group, Breakout Capital, and Greak Oaks.

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Fabric offers an alternative to Facebook sharing with a private timeline of personal moments

Fabric, a personal journaling app that emerged from Y Combinator’s 2016 batch of startups, is relaunching itself as a Facebook alternative. The app is giving itself a makeover in the wake of Facebook’s closure of the Moves location tracker, by offering its own tool to record your activities, photos, memories and other moments shared with friends and family. But unlike on Facebook, everything in Fabric is private by default and data isn’t shared with marketers.

Instead, the startup hopes to build something users will eventually pay for, via premium features or subscriptions.

The idea for the startup came from two people who helped create Facebook’s core features.

Co-founders Arun Vijayvergiya and Nikolay Valtchanov worked for several years at the social network, where Vijayvergiya built the product that would later become Facebook Timeline at an internal hackathon. He also worked on products like Friendship Pages, Year in Review and On This Day, while Valtchanov developed integrations between Facebook and fitness applications.

After leaving Facebook, both were inspired to work on Fabric because of their interest in personal journaling – and that became the key focus for the original version of the Fabric app. But while other journaling apps may offer a blank space for recording thoughts, Fabric automates the process by pulling in photos, posts from elsewhere on social media, places you visited, and more, and put those on its map interface.

The longer-term goal is that Fabric users will be able to look back across their personal history to answer any kind of question about where they had been, what they did, and who they were with – but in a more private environment than what’s available on Facebook.

Facebook could have built something similar, but its focus has been more on how personal profile data could be useful to advertisers.

Despite numerous check-ins, posts where you tagged friends, shared photos and more, there’s still not an easy way to ask Facebook about that great Indian restaurant you tried last March, or who was on that group beach trip with you a few years ago, for example. At best, Facebook offers memory flashbacks through its On This Day feature (now available at any time via the Memories tab), or round-ups and collages that appear at various times throughout the year.

As a search engine for your own memories, it’s not that great.

What’s New 

This is where Fabric comes in. It will automatically record your activities, checking you in to places you visit, which you can then choose to add friends to.

While the idea of automatic location gathering may turn a good number of users off, the difference is that Fabric’s data collection is meant for your eyes only, unless you explicitly choose to share something with friends.

Fabric doesn’t use third-party software for its location system – it’s written in-house, so the data is never touched by a third-party. It also uses industry standard encryption for data transfer and storage, and login information is stored in a separate system from the rest of your data as an added precaution.

Notably, Fabric doesn’t plan to generate revenue by selling data or offering it to advertisers for targeting purposes. Instead, the company hopes users will eventually pay for its product – perhaps as a subscription or through premium upgrades. (It’s not doing this yet, however.)

“The whole motivation behind Fabric is that many meaningful parts of your life do not belong in the public sphere,” explains Vijayvergiya. “In order to be able to capture these moments, user trust is essential and is something we have baked into our company culture. Internally, we refer to ourselves as a ‘private-first’ company. Everything on Fabric is private by default. You have to choose to include friends in your moments. We don’t share any data with marketers, and we don’t intend to share personally identifiable information with advertisers,” he says.

Since its 2016 release, Fabric has been downloaded 70,000 times by users across 117 countries, and has seen 112 million automatic check-ins.

The new version of the app has been redesigned to be something users engage with more often, as opposed to the more passive journaling app it was before.

The app now offers an outline of your activities, which it also calls Timeline. Here, you can add people, photos and memorable anecdotes to those automated entries. You can jump back to any day to see your history with any person or place that appears on the Timeline.

You can also turn any moment into one you collaborate on with friends, by allowing others to add photos and comments. That is, instead of broad post to a group of so-called “friends” on Facebook, you share the moment with those who really matter. This isn’t all that different from how people use private messaging apps and group chats today – in order to share things with people that aren’t necessarily meant for everyone to see.

In addition, Fabric allows you to add your friends to the app, so you can be automatically tagged when you both spend time together in the real world. This also simplifies sharing because you won’t have to think about which posts should be shared with which audience.

For instance, Vijayvergiya says, “this means you can add your mom as a friend, and only share with her the moments you spend together in the same place.”

The most compelling feature in the updated app may not be check-ins or sharing, but search.

In Fabric, you can now search for past events in your life similar to how you search the web. That is, you could type in “restaurant rome 2017” or “camila los angeles birthday” and find the matching posts, Vijayvergiya suggests. And because you can import your Facebook, Instagram, and Camera Roll to Fabric, it’s now offering the search engine that Facebook itself forgot to build. (You can import your Facebook Moves history, too, ahead of its shutdown.)

Fabric’s search will also be available on the desktop web, where it’s currently in beta.

Fabric’s real challenger, as it turns out, may not be Facebook, though. It’s Google Photos.

Because of advances in image recognition technology, Google Photos (and some other photo apps) have built advanced search capabilities that let you pull up not places, things, people, and more, using data recognized in the image itself. Users can also share those photos with others, collaborate on albums, and leave notes as comments.

The difference is that Fabric offers import from a variety of sources and encourages journaling. But that may not be enough to attract a large user base, especially when automatic check-ins rely on the app’s use of background location which has some impact on battery life.

Fabric is a free download on iOS.

 

 

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Serverless, Inc. lands $10 M Series A to build serverless developers platform

Serverless, Inc came to the serverless game early, creating an open source framework for developers back in 2015. Today, they want to build on that earlier product to give developers more control over deployment and delivery of serverless applications. To that end, they announced a $10 million Series A round led by Lightspeed Ventures. They have now raised a total of $13 million, according to the company.

The company also announced the release of the Serverless Platform, which include the Serverless Framework, Serverless Dashboard and Serverless Gateway. The Framework lets developers set up their serverless code across different cloud platforms and set conditions on the deployment such as function rules and infrastructure dependencies. The dashboard gives visibility and information about the deployment, so that you can track and trace serverless functions over time, regardless of the cloud platform you’re using.

Diagram: Serverless, Inc.

The gateway provides a way to pull in legacy tools into a serverless approach. As the company describes it, “The Serverless Gateway allows businesses to easily integrate serverless into their existing mesh of services, including containers, SaaS or other legacy systems. The Event Gateway, along with serverless compute, gives organizations a powerful way to react to all of their business events with code.”

Company founder and CEO Austen Collins says that as companies shift to a serverless-first mindset, we’re going to see a lower cost to build and deploy applications, but that is going to take some tooling to really work across a team or large organization, tooling his company wants to provide.

“I think now we are seeing widespread demand for tools to operationalize serverless development, tools to make developers across an entire team, or even across entire organization all practice serverless development in a safe and standard way,” Collins explained.

The framework and communications gateway are open source and always will be, Collins, explained. They will make money by charging companies to use the dashboard to get insights into their serverless code or to access a hosted version of the gateway. People can host their own version of the gateway through using the open source version of the product.

With serverless, developers no longer have to worry about the infrastructure required to run their applications. Instead, they create functions that trigger events and the cloud vendor takes care of deploying the necessary compute, memory and storage to run that event.

It offers a number of advantages including eliminating the need to worry about deploying the appropriate infrastructure and only paying for the infrastructure you use each time your function triggers a given event. This is in stark contrast to the traditional approach to development where you deploy a server for your application and pay for it 24/7 whether it happens to be in use or not.

While this approach undoubtedly has the potential to remove some of the complexity associated with developing and deploying applications, it doesn’t remove all of the requirements developers have to deploy and manage their code according to a set of defined policies. The kind of tool set Serverless Inc is offering provides some additional control and insight developers could be lacking with such a new approach.

The company launched in 2015 and currently has 22 employees in a distributed office approach. Their main office is in San Francisco. Customers include EA Sports, Nordstrom, Reuters and Coca-Cola. The new money should allow them to expand and build out the platform further.

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Feature.fm offers free “pre-save” tool for upcoming releases on Spotify, Apple Music and Deezer

In an age where people stream music instead of buying it, how do you build something equivalent to a pre-order campaign for upcoming releases? The answer is to create a “pre-save” campaign, akin to a landing page where fans can authorise you to automatically add a new song, EP or album to their steaming library or playlist of their choice as soon as it becomes available.

However, pre-save tools for Spotify — if you even knew they existed — are often perceived as expensive and solely for use at major labels or established music marketing companies. Now music marketing and technology startup Feature.fm wants to change that with its “Ultimate Pre-Save,’ a free tool for artists or labels of any size.

Better yet, the Ultimate Pre-Save tool also supports Apple’s newly launched “Pre-Add” feature, which works in a similar way to a Spotify pre-save. Deezer’s version of pre-save is supported too.

The set up process is simple. You register with Feature.fm as either an individual artist or label, select the Ultimate Pre-Save tool and click on create new pre-save. Next you are required to give the work a launch date and tell it which of the three services you plan to launch on. You then need to add a title, an image, preview link, and make any changes to the standard text. Later on, once you know the final URL for your new release on each respective service, you add that too.

And that’s pretty much it. Your fully functioning pre-save page is built, ready for you to start sharing/promoting and hopefully have a successful Day One launch.

Meanwhile, any fan who lands on your pre-save page can click “Pre-Save” or “Pre-Add” to get your music into their libraries on release day. They’ll also automatically follow your artist page if they don’t already. You also have the option to re-direct them to a different URL afterwards so you can reward fans with things like exclusive content or contests.

One other useful feature is that the Feature.fm pre-save link automatically converts to a “smart link” once the song/album is released. So up until release the message will be “pre-save on Spotify, Apple Music or Deezer” etc. and then after release day the link automatically switches to a “buy or stream on your preferred service” and pulls in other digital music services too e.g. Amazon and Tidal etc. The idea is that you only need one smart link for the entire life of a campaign.

Other than that, you can capture/collect up to 50 fan emails for free, and get access to click and pre-save counts. There is also the option to pay for some advanced features, such as custom domains, either monthly or as a one-off campaign. And of course Feature.fm wants to up-sell you to a host of other marketing tech features, such as its incredibly easy to use music ad tools, deeper analytics, and the ability to send remarketing data to your Facebook Ads, Google AdWords, and other ad programs.

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Twitter turns to academics to improve conversational health on the platform

Twitter is partnering with two groups of academic researchers to figure out how to measure the health of conversations happening on the platform.

It’s all part of the company’s continuing long game for social relevance. Despite the fact that it lost 1 million users, the company also posted $100 million in profit during last week’s earnings. But neither of these numbers seem to change the fact that Twitter needs to make some adjustments to the way people use the social network.

In March, Twitter called for proposals from researchers to see how they might approach the issue of analytics around the types and manner of conversations on Twitter. These proposals were thoroughly reviewed by Twitter employees from a variety of departments at the company, including Engineering, Product, Machine Learning, Data Science, Trust and Safety, Legal and Research. Twitter also says that the review committee was organized to include representatives from diverse groups across the company. (Reminder: less than 10 percent of Twitter employees are diverse, so it was likely a busy few months for those people.)

Well, the review process is now over and Twitter has decided on two research teams, who will focus on two different issues.

The first team, led by scholars from Leiden University, will look at how echo chambers form and their effect, as well as the difference between incivility and intolerance within Twitter conversations. The team — including Dr. Rebekah Tromble, Assistant Professor of Political Science at Leiden University, Dr. Michael Meffert at Leiden, Dr. Patricia Rossini and Dr. Jennifer Stromer-Galley at Syracuse University, Dr. Nava Tintarev at Delft University of Technology, and Dr. Dirk Hovy at Bocconi University — has found in past research that echo chambers can cause hostility and promote resentment towards those not having the same conversation.

The first set of metrics this team is focusing on will look at the extent to which people acknowledge and engage with diverse viewpoints on Twitter. The second set of metrics will look at the difference between incivility and intolerance. Past research by this group shows that incivility can serve important functions in political dialogue, though not without spurring its own problems. On the other hand, intolerant speech (hate speech, racism, xenophobia) threatens our democracy. The team plans to develop algorithms that will distinguish between more useful incivility and the very useless intolerance we encounter daily on Twitter.

The second research project will be led by Professor Miles Hewstone and John Gallacher at The University of Oxford, in partnership with Dr. Marc Heerdink at the University of Amsterdam. The work will be an extension of Prof. Hewstone’s long standing work to study intergroup conflict. The current findings from this study show that when conversation contains more positive sentiments, cooperative emotions, and more complex thinking and reasoning from multiple perspectives, prejudice will go down and the quality of the relationships will go up.

“As part of the project, text classifiers for language commonly associated with positive sentiment, cooperative emotionality, and integrative complexity will be adapted to the structure of communication on Twitter,” the Twitter blog says.

Just like any social network, Twitter provides scaffolding. Users, on the other hand, construct buildings made of dialogue. How exactly Twitter will be able to adjust the scaffolding to produce more useful, empathetic conversations is still a mystery. But bringing in the academic community to help is an excellent next step.

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Bus-sharing app Shuttl gets $11M Series B from investors including Amazon India

Shuttl, a service that lets Indian city dwellers find seats on multiple bus routes through one app, announced today that it has raised a $11 million Series B led by Amazon India, Amazon Alexa Fund and Dentsu Ventures. Returning investors Sequoia Capital, Times Internet and Lightspeed Ventures also participated.

The Gurgaon-based startup’s last round of funding was a $20 million Series A announced in December 2015, just eight months after it launched.

The Amazon Alexa Fund was created in 2016 to fund new voice technology. One of Shuttl’s most interesting features is “Chirp,” which verifies passengers by sending a sound from their mobile phones to the driver’s version of its app. The idea is that “chirping” is quicker than using tickets or passes and can therefore decrease delays on bus routes.

Shuttl, which is owned by Super Highway Labs, was created with the goal of reducing pollution and traffic in major cities like Delhi by encouraging people to take public transportation. In order to compete with Uber and Ola, its tech platform optimizes routes and capacity, while its app enables users to track the location of their bus, giving them similar convenience and reliability to on-demand ride services (as long as they remember to book their seat a day in advance).

Shuttl’s platform now includes 800 buses and it claims to have 60,000 monthly active users and provide 45,000 rides per day in five cities. Its new funding will be used to expand into two new cities.

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Grover raises €37M Series A to offer latest tech products as a subscription

Grover, the Berlin-based startup that offers “pay-as-you-go” subscriptions to the latest consumer tech as an alternative to owning products outright, has raised €37 million in funding.

The Series A round is led by Circularity Capital LLP — a VC that specialises in the so-called “circular economy” — with participation from fintech investor Coparion, Samsung NEXT, and Varengold Bank. Existing investors, including Commerzbank’s Main Incubator, also followed on.

Noteworthy, the funding consists of €12 million in equity and a new €25 million debt facility. Building an inventory of new tech products to rent is quite capital insensitive, after all.

Targeting Germany only, for now (after withdrawing from the U.K. and pausing a soft launch in the U.S.), Grover wants to be something akin to Netflix for gadgets. It offers individual tech products by monthly, three-monthly or yearly subscription, or via its newly launched “Grover Mix” subscription, which has a fixed monthly price and lets you switch item at any time.

In addition, you are afforded some upside protection, should you wish to purchase the item after renting it first. You’re given the option to buy products with 30 percent of your subscription payments to date being deducted from the recommended retail price. For longer rental periods, Grover will also warn you if you are close to reaching 130 percent of the full purchase price and prompt you to consider buying it for €1.

The startup has also been trialling a B2B product aimed at burgeoning companies, dubbed “Startups get Grover”. This I’m told came about after demand from startups who, for example, want to subscribe to a bunch of Macbooks to give to new employees, and as an alternative to deploying upfront capital.

In a call with Grover founder and CEO Michael Cassau, he told me the new capital will be used to expand the company’s market leadership in Germany and re-boot international expansion in a bid to continue a current revenue growth rate of 20 percent per month. He said the startup had taken the decision in early 2017 to focus on Germany, temporarily abandoning internationalization, after it had signed a major partnership with German e-retailer MediaMarkt. It has since also partnered with Saturn, Gravis, Conrad, and Tchibo.

This sees Grover become a checkout option, alongside other payment buttons or financing offers. That way a customer can choose to rent a tech product via their favourite online store powered by Grover. Behind the scenes, Grover actually buys the product from the retailer, having put agreements in place with regards to what products fit the Grover model and aren’t already overstocked by Grover.

Alternatively, in some instances, Grover has a “re-circulation” deal in place so that a retailer can continue offering Grover as an option even if Grover has enough inventory already, and instead take a share of future subscription income. This works particularly well for slightly older products or items that are diminishing in popularity.

In addition to growing in Germany and future international ambitions, Cassau says that the startup plans to invest in the user experience of Grover, suggesting that it has room for improvement. This will include developing “new and innovative usage models,” while he also conceded that with further scale the company can get more customer aligned in terms of the products on offer and its subscription pricing.

At some point, if Grover’s subscription model becomes compelling enough, it’s hoped that purchasing many tech products will become so unattractive as to create Netflix-level changes in consumption behaviour. Or, at least, that’s the aim. In my case, that would mean spending far less time recycling things like smartphones and music technology gear on eBay as I tread a well-trodden and perpetual upgrade path.

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