Amazon’s next conquest will be apparel

Late last year, after Amazon announced it had acquired the rights to J.R.R. Tolkien’s epic “Lord of the Rings” saga for $250 million, I wrote how the move underscored Amazon’s relentless pursuit to build one platform to “rule them all.” Now that Amazon is investing half a billion dollars into developing a Middle Earth show – making it the most expensive TV series ever made – it won’t be a surprise to see Jeff Bezos front and center at the Emmys soon.

But Hollywood isn’t the only industry Amazon wants to upend. Based on the company’s great ambitions in apparel, it may not be long before we also see Bezos at New York Fashion Week next to Anna Wintour.

The 800-Pound Gorilla in the Fashion World


As traditional retail continues to recede, direct to commerce fashion brands continue to emerge. I’ve previously shared how Stitch Fix, Warby Parker, Everlane and Allbirds are just a few innovative companies proving the success of this model. As the master of D2C commerce, Amazon has been fine-tuning its fashion operation for over 15 years.

Amazon originally got into apparel all the way back in 2002 and acquired online shoe retailer Zappos for $1.2 billion in 2009, marking the largest purchase in its history at the time. But the company’s quest to dominate fashion has faced several historical obstacles, chief among them that people have not trusted buying apparel online out of a desire to try on the items first and that Amazon was not perceived as a “cool” brand.

Headwinds are now tailwinds. Online shopping for apparel took off and is now the highest online-penetration CPG sector; the majority of women have shopped for clothing online. E-commerce accounts for nearly twice as big a proportion of total clothing sales as it does for retail more broadly (17 percent vs. 10 percent). Amazon, meanwhile, has honed its apparel strategy, providing free returns, better photography and greater selection. Today, the company is the largest apparel retailer by gross merchandise volume. Mission accomplished? Not quite.

Building A Private-Label ‘Fashion House’

An actual Amazon fashion shoot

Bonobos CEO Andy Dunn once said, “Selling a bunch of other people’s stuff is a low margin game that requires a lot of capital and, ultimately, it’s hard to beat Jeff Bezos at that.” This is true, but when it comes to apparel, Bezos has greater ambitions than selling other people’s stuff. Currently, though, that’s mostly what Amazon does.

According to analysis from Coresight Research, nearly 14 percent of listings on the U.S. Amazon Fashion site are from Amazon itself, while third-party sellers account for the remaining 86 percent. Amazon is highly incentivized to increase its share of that pie. Apparel is a highly profitable category for the company, with 40 percent peak gross margins in the last 10 years. Additionally, Prime members heavily overindex for buying apparel on Amazon – nearly two-thirds have done so in the past year.

As it ramps up its private-label offerings, Amazon is clearly keen to move beyond selling the apparel equivalent of batteries and diapers through its Amazon Essentials brand. It started selling thigh-high velvet boots in September, and Coresight’s analysis indicates that the company is focusing on higher-value categories.

If its recent Lord of the Rings rights acquisition was an attempt to further capture young affluent consumers’ eyeballs, and Whole Foods an attempt to lock down their stomachs, it follows that Amazon would want to ensnare their wardrobes as well. Acquiring a hot digitally native vertical brand – or brands – would be a speedy way to accomplish that. Walmart has already pursued this strategy by buying Bonobos, Modcloth and others; Amazon could take a similar path and seek to bring buzzy brands like Everlane into the everything store. This could also go a long way in helping Amazon shed its “uncool” label.

Becoming A Fashion (Power)House

The Echo Look is just one sign Amazon is serious about dominating fashion

Last year, Amazon introduced a number of innovations designed to turbocharge its apparel business and make the online shopping experience as frictionless as possible. It launched Prime Wardrobe, a Stitch Fix-style service that allows you to try three or more items on at home before sending back the items you don’t want for free in a resealable box with a prepaid label.

 It also debuted Echo Look, a new Alexa-powered device that the company dubs a “hands-free camera and style assistant.” The addition of a camera enables the device to record and comment on its owner’s clothing choices, using a combination of machine learning and human stylist feedback. This advice also takes the form of recommendations, which can drive revenue to Amazon Fashion, and specifically its private-label brands.

Amazon is iterating on and rolling out more features for the Echo Look, including curated content and even crowdsourced (human!) style feedback. It also created an AI algorithm for designing clothes and patented an AR mirror that lets you virtually try on clothes. The value of such a mirror was validated recently by L’Oreal’s acquisition of ModiFace, a company that produces technology that powers similar applications in beauty AR.

Analyzing all these moves together, Amazon’s apparel strategy begins to crystallize. First it sells tons of clothes to learn how clothes are sold. Then it starts selling its own clothes to generate higher gross margin. And now has it has Prime Wardrobe to increase lock-in and reduce points at which customers can choose not to buy Amazon’s own clothing (all while gathering more data about individual preferences); and Echo Look to be its data collection and voice-commerce portal (and as an added bonus, it can route ambiguous purchase requests to its growing inventory of private-label items). If this strategy is successful, it will give Amazon an enormous data moat to drive high-margin sales – a competitive advantage that will be extremely difficult for fashion retailers and brands to replicate.

Bezos doesn’t need to even ask.

Amazon has become increasingly dominant in several increasingly important arenas: cloud services, voice assistants, self-serving brick-and-mortar stores with Amazon Go, and of course its now-traditional role as the online everything store. The company is poised to add apparel to this growing list as it changes the way people shop for clothing (again) and entices more of its customers to buy Amazon’s own threads. And it bears mentioning that Amazon Fashion will get a helpful hand from Amazon Studios as well. Bezos once shared that, “When we win a Golden Globe, it helps us sell more shoes.” If he has his way, Amazon will be doing a lot more of both in the coming years.

Source: Tech Crunch

Connecting our homeless neighbors with their loved ones

San Francisco’s housing crisis is painfully obvious with a homeless population of 7,499 people, according to a 2017 homeless census and survey. People lose their homes for a variety of reasons — job losses, wrongful evictions, excessive rent hikes and so forth. What sometimes prevents people from finding a new home is a lack of available resources, pricey rent costs and lost connections with friends, family and loved ones.

The latter part is where Miracle Messages, founded by Kevin Adler, aims to come in. Miracle Messages, a non-profit organization, enables homeless people to deliver short messages to their loved ones.

There are number of factors that play into people losing touch with their loved ones, Adler told me on the latest episode of CTRL+T.

For one, there are bureaucratic barriers, he said. For example, shelters can’t confirm or deny whether someone is or is not at a facility, due to the Health Insurance Portability and Accountability Act. Another part of it, Adler says, is digital literacy.

“A lot of people lose their phones, they lose numbers and they don’t know how to reach out,” Adler said. “But the biggest one,” Adler said, is “shame, embarrassment, fear, feeling worthless.”

Since its inception, Miracle Messages has delivered 220 messages and reunited 118 loved ones. Of those reconnections, 80 percent of them have resulted in a positive outcome and 25 percent have led to stable housing.

Through Miracle Messages, Adler hopes housed people will start to see those without homes as more than just homeless people, but as someone’s son, daughter, sister or brother.

In some cases, unfortunately, some people have lost touch with their families — and that’s partly why they landed on the streets in the first place, Adler said. That’s where the organization’s monthly neighborhood dinners can come in.

It’s about “creating avenues where we can engage our neighbors experiencing homelessness on those fronts,” Adler said.

“It’s not ignoring the pressing issue at hand,” he said. “It’s actually reemphasizing the humanity that we all have to offer and that we need as people.”

Source: Tech Crunch

Gillmor Gang: Carrier Pigeon

The Gillmor Gang — John Taschek, Denis Pombriant, Keith Teare, Esteban Kolsky, and Steve Gillmor. Recorded live Friday, April 20, 2018.

G3: Privacy Fence — Mary Hodder, Maria Ogneva, Francine Hardaway, Kristie Wells, and Tina Chase Gillmor. Recorded live Friday, April 20, 2018.

@stevegillmor, @jtaschek, @kteare, @DenisPombriant, @ekolsky

Produced and directed by Tina Chase Gillmor @tinagillmor

Liner Notes

Live chat stream

The Gillmor Gang on Facebook

G3: Privacy Fence

G3 chat stream

G3 on Facebook

Source: Tech Crunch

Original Content podcast: Netflix successfully reinvents ‘Lost in Space’

Lost in Space started out as a ’60s TV series, got rebooted in the 1990s as a feature film and has now been brought up-to-date by Netflix .

On the latest episode of the Original Content podcast, we review the first season of the new show, which finds the Robinson family once again sent into space, facing constant peril on an alien planet while also getting help from a robot that’s fond of shouting, “Danger, Will Robinson!”

Many of the classic elements have been updated in some way — perhaps the most effective change was casting Parker Posey as the villainous Dr. Smith. The new Lost in Space seems more serious and character-driven than its predecessors, but at the same time, it remains aimed at a family audience.

We also discuss our thoughts on the film version of Ready Player One, AT&T’s plans for a $15-per-month streaming service, ESPN’s new move into streaming and Amazon’s in-development series based on The Peripheral by William Gibson. (At one point in the episode, Jordan says Battlestar Galactica isn’t available on Prime Video, but for the record: It is.)

You can listen in the player below, subscribe using Apple Podcasts or find us in your podcast player of choice. If you like the show, please let us know by leaving a review on Apple. You also can send us feedback directly.

Source: Tech Crunch

Where have all the pilots gone?

You’d think everybody would want to fly. It’s been a universal human dream since the first cave person saw the first pterodactyl¹. You’d think better technology, greater demand, economic growth, and population growth would mean more and more pilots. But the surprising, counterintuitive fact is that fewer and fewer people are flying, and now Earth needs pilots, badly.

Airline industry facing a massive shortfall of pilots.” “Yes, there is a definite pilot shortage. It is true in all parts of aviation.” “The US Air Force is short more than one-quarter of the fighter pilots it needs.” “Asian airlines are running out of trained pilots.” “‘Extraordinary’ Pilot Shortage Threatens Flights; 637,000 Needed.”

Meanwhile, the number of active pilots in the US has declined from over 800,000 in 1980 to barely 600,000 in 2017, a quarter of whom are student pilots, a certificate for which you need no experience at all. Of course there are pilots and there are pilots. A private pilot in a little Cessna is very different from an airline transport pilot guiding a 777. And one reason there’s a shortage is that, while that 777 pilot pulls in six figures, an overworked copilot at a remote feeder airline gets paid peanuts.

But this overall broad decline in piloting is still truly remarkable. Why are we flying so much less in person, at the same time that we are flying so much more remotely? (The demand for commercial drone pilots, who in the USA must qualify for a “remote pilot certificate” by passing an aeronautical knowledge exam and a TSA security check, is also growing.) Why are fewer and fewer people taking to the skies, when they have never been more accessible, and flying car startups, some of them self-flying, are erupting like mushrooms after rain? Might self-flying airplanes ultimately solve the pilot shortage?

To try to answer these questions and more, I have recently taken up flying lessons myself, as a sterling example of investigative journalism on behalf of TechCrunch’s readers.

I jest. Really this was my friend Nat’s fault. “The thing about flying,” he said to me over dinner once, “is it combines romance, adventure, science, and exploration.” A heartbeat of stunned silence later I managed to retort, “Well, that sounds terrible,” but the damage was done.

Taking off seems easy enough, at first, on a demo flight. Just thrust the throttle forward, and feel the whole airplane thrill with the engine’s unleashed power as you accelerate down the enormous runway. The flight instructor next to you tells you when to pull up, gently — you’re not even moving that fast, maybe 70 miles an hour, normal highway speed — but when you do, just like that, you’re flying. You are so accustomed to vehicles on wheels that the freedom from the tyranny of the earth, the absence of the sensation of ground against tires, feels almost vertiginous, like weightlessness.

Around you the earth falls away: runway, airport, golf course, the San Francisco Bay glittering in the sun. From a cockpit 2500 feet up the Bay Area looks almost too gorgeous to be real, like a special-effect matte painting of sea, rippling hills, great pale swathes of buildings, cargo ships arrayed in their unloading queue, the forest of skyscrapers that is downtown San Francisco, the pale arc of the Bay Bridge, the clenched fist of Alcatraz, the famed distant silhouette of the Golden Gate.

I’m a terrible cliché now, of course. A Bay Area tech CTO who takes up flying is about as remarkable as a coastal Australian who takes up surfing. I blame Nat.

Does self-deprecatingly admitting that you’re a terrible cliché make it better or worse?

“Science,” he said, and there’s some of that, but really it’s mostly engineering, a kind very different from the engineering I know professionally. This is physical, visceral, greasy. Not a Matryushka doll of nested software abstractions, running on some faraway server whose physical details you don’t know or care about; not digital chipsets and circuit boards, taking advantage of Moore’s Law and the peace dividend of the smartphone wars, to drive LEDs or solenoids or little electric motors. This is airfoils, spars, composite materials, airflow vortices, a shifting center of gravity as fuel burns, physical forces fighting to keep you aloft against the relentless pull of the Earth. This is pistons, spark plugs, carburetors, magnetos, fuel pumps, propellers.

You need to understand how all this engineering works because it is there to keep you aloft and alive. Light aircraft are not dangerous — the one I’m learning in, the Diamond DA-40, a 21st-century airplane with an excellent safety record, is statistically safer per hour than a motorcycle — but that’s because of pilot training, not their inherent security. Whether you like it or not, part of the adventure of flying is that it’s replete with risks. Weather risks, largely: thunderstorms, icing, wind shear, and especially clouds.

(Yes, clouds. Basic pilot training is for “VFR” (visual flight rules) and if you’re not trained to fly “IFR” (instrument flight rules) then clouds can and will kill you, because without a visual horizon to track, your instincts and senses will promptly start telling you lies about your airplane’s attitude and behavior, and if you’re not trained to override those gut feelings, and follow what the instruments say, then you are asking for a controlled flight into terrain. Fun fact: night flights over water can still be “VFR” in the USA! See also the sad fate of JFK Jr.)

But technical risks are very real too. Did water get into your fuel tanks? Were they accidentally filled with jet fuel instead of avgas? How do you know? Is your engine running rough today? Maybe you just need to lean the mixture for a few minutes during the run-up; and maybe you need to turn around and call a mechanic. What speed will this airplane stall at? Trick question! Stalls aren’t dictated by speed. You better know what they are dictated by, if you want to fly.

And you do. Or at least I do. It’s glorious. It’s adrenalinizing, it’s breathtaking; it’s freedom, it’s beauty; it’s like dreaming while awake.

That said, learning to fly is frequently more Type II fun than Type I. I always actively enjoy it while I’m doing it, but at the same time, it is often tense, draining, and stressful. You need to always be on when you are in the cockpit. It takes time to get accustomed, at a gut level, to hurtling through the sky at high speeds in a little shell of fibreglass and carbon fibre with wings and a tail. And at least at first, you are drowning in information and obligations.

Student piloting is brief periods of pleasant inactivity interspersed with frequent periods of frantic multitasking. Aviate, Navigate, Communicate, they say — but at first aviation alone seems to take more attention and brainpower than you can allocate. You have rudders, ailerons, elevators, trim, and throttle to control. Sometimes you need to tweak the propellor, the mixture, and the active fuel tank. All this while constantly watching your airspeed, altitude, heading, and vertical speed; maintaining awareness of your engine indicators; and keeping an eye out for other airborne traffic.

It’s easier than that sounds, but it’s not as easy as it looks. Even takeoffs are harder than they first seem. (When you push the throttle forward, four separate physical forces skew the nose of the airplane sharply to the left, so you need to step on the rudder, without stepping on the brake, to keep the nose straight-ish.) Landings are hard full stop. Well, sometimes they feel easy, but consistency is hard.

Are self-flying planes on the horizon? I am skeptical, barring a new breakthrough in machine learning, which admittedly I don’t rule out. But there are two barriers. First, when will safe self-flying be possible? Self-driving cars are hard enough, and they only have one axis of control, and don’t get blown around by winds, and if something goes wrong you hit the brakes. Airplanes have pitch and roll as well as yaw, and move within a highly dynamic medium, and if something goes wrong — like an engine failure, or a bird strike — a quick halt is generally the exact opposite of a desirable outcome. I can easily envision self-flying AI which handles 99.99% of flights, but that 0.01% of exceptional situations will be awfully hard to train for.

Second, even if we get there, when will it be practical? While individuals might volunteer to be bleeding-edge adopters, how can you prove its validity to the FAA and other regulatory authorities? We’d need to add many more nines before self-flying software start competing with professional human pilots, who, unlike human drivers, have a remarkable safety record; commercial aviation had zero fatalities in 2017. Better autopilots for ordinary conditions are one thing, but removing pilots from flying entirely is quite another. Maybe after we build up a long, deep history of perfect safety with comparable drones or military flights; but not any time soon.

Better technology will however help with navigation. I don’t mean point-to-point, I mean in familiar places. Navigation may seem relatively easy above the San Francisco Bay, a well-known territory full of landmarks. Guess again. That sky may be empty but it is not unoccupied. Instead it is segmented into dozens of complex three-dimensional zones, and woe betide you if you stray into the wrong one.

Bay Area VFR airspaces

Picture a tiered wedding cake, upside-down, with radiuses measured in miles. That’s the airspace of San Francisco International. But right across the bay you have Oakland International, which has its own smaller but still sizable wedding cake, and a little south San Jose International has its own, and both of those intersect with SFO’s. Then you have the half-dozen smaller regional airports, each jealously guarding their own disc of space, except where squashed by one of those cakes. Each of those kinds of airspace has its own rules and regulations. (SFO’s have the virtue of being exceedingly simple, for student pilots: keep out.)

You may not enter any of those airspaces without first communicating with their controllers, and to communicate you first must master aviation’s clipped, dense, custom language. “Hayward Tower, Seven Papa Victor holding short at runway Two Eight Left Alpha, request right crosswind departure.” “Norcal Approach, DA-40 Seven Eight Seven Papa Victor, three thousand over Lake Chabot, inbound to Oakland for touch-and-gos with information Foxtrot.” “Seven Papa Victor, squawk oh three five seven and contact Oakland Tower.” It would be unremarkable to change frequencies several times, and talk to a few different controllers, during a half-hour Bay flight.

Knowing what frequency to use, what to say, who to say it to, and when, while picking your own call sign out of the frequent chatter, most of which is irrelevant to you, and parsing / copying down the important information you need — that would be nontrivial all by itself, at first. But it’s not by itself. It’s something you do simultaneously with everything else you’re doing while flying the airplane.

Does the heavy use of voice communications over frequently (and manually) shifted shared channels seem a little … well … twentieth century? A little technologically backward? Well, yes, and no. Voice over radio is simple, powerful, flexible, and time-tested. There are a lot of old airplanes and old pilots out there. Aviation as an industry is understandably loath to make rapid changes — many of its rules are, as they say, written in the blood of people who learned the need for them the hard way.

That said, modern aircraft like the DA-40s I’m learning on tend to have “glass cockpits,” with one LED screen displaying an artificial horizon and all the important instrument data so you don’t have to look at the actual dials (which are still there as backup), and the other displaying a zoomable map with terrain, your heading, airspace boundaries, nearby traffic, etc., and containing databases of information such as airport locations, runways, and frequencies — all at your fingertips if you can master their baffling and perverse knob-and-button user interfaces. (“Turn the big knob left. Now turn the little knob right. Now push ENT. Now turn the little knob left…”)

Apps like ForeFlight make it easier yet. And we happen to be 20 months away from a massive technological phase shift in general aviation, after which much American airspace will require “ADS-B” technology that will essentially let every aircraft be tracked in 3-D in real time; this should make communications and aircraft spacing much easier.

It feels a little bureaucratic, it’s true. The romance of the glory days of flight, Antoine de Saint-Exupéry and company wrestling their planes over the Andes and the Sahara, with the freedom of the whole sky thanks to their skill and their machinery, feels distant from today’s strictly ruled, tightly regimented airspaces, and constant surveillance anywhere near a major airport. But then the skies were empty back then, and the machinery all too often so lethal that skill meant nothing, in the end.

And, I mean, these too are the glory days. You can fly. All by yourself. It isn’t an easy thing to learn, or to do. (OK, some people are naturals. I myself am not.) Multitasking is hard. Kinesthetic learning is hard. Establishing new muscle memories is hard. Developing good judgement is hard. Flying an airplane smoothly, with coordinated turns (using the ailerons and rudder together) while maintaining precise control of altitude and airspeed and bank angle, is … actually that’s not so difficult; but doing all this while at the controls of an aircraft that’s, say, being buffeted by crosswind gusts as you turn towards a runway, in a busy traffic pattern, with the stall warning beginning to whine because you banked too late and too hard, but it’s too late to fix that judgement error now, and the radio crackling in your ears as the tower says something which might or might not be germane to you —

— well, the instructor who made that first takeoff seem easy told me, later that same day, that most people who begin pilot training never finish it. There are plenty of good reasons for that. It is, as my friend Dillo put it, more expensive than a crack habit. People hit plateaus and get frustrated and give up. But I think the main reason is because it’s complicated, and difficult, and stressful, and when the lessons stop being novel, people stop forcing themselves to do the hard thing, despite the ultimate rewards.

Is that why there are far fewer pilots in America than there were in 1980, even though there are 100 million more people? Would better, modernized navigation and communications technology go a long way towards making flying a little less draining, and a little more appealing? Maybe. There are cultural reasons, too, though, and I think they’re more significant. I think we now lean more towards the abstract than the physical, and towards comfort rather than adventure.

I remember, years ago, seeing online reactions to a study reporting that teenagers in gifted programs were likely to quickly drop things they weren’t immediately good at, the theory being that they feared losing their gifted designation, and that this instinct persisted into adulthood. An astonishing number of my friends, especially my friends who worked in tech, said they strongly identified with this. I wonder if that’s a factor.

Most of all, though, I think flying seems like a very 20th-century activity in the popular imagination. But I suspect that won’t last. Something, whether hardware or software, will catapult it into the 21st century mindset soon enough.


¹Yes, I know. It’s a joke.

Source: Tech Crunch

Pivotal CEO talks IPO and balancing life in Dell family of companies

Pivotal has kind of a strange role for a company. On one hand its part of the EMC federation companies that Dell acquired in 2016 for a cool $67 billion, but it’s also an independently operated entity within that broader Dell family of companies — and that has to be a fine line to walk.

Whatever the challenges, the company went public yesterday and joined VMware as a  separately traded company within Dell. CEO Rob Mee says the company took the step of IPOing because it wanted additional capital.

“I think we can definitely use the capital to invest in marketing and R&D. The wider technology ecosystem is moving quickly. It does take additional investment to keep up,” Mee told TechCrunch just a few hours after his company rang the bell at the New York Stock Exchange.

As for that relationship of being a Dell company, he said that Michael Dell let him know early on after the EMC acquisition that he understood the company’s position. “From the time Dell acquired EMC, Michael was clear with me: You run the company. I’m just here to help. Dell is our largest shareholder, but we run independently. There have been opportunities to test that [since the acquisition] and it has held true,” Mee said.

Mee says that independence is essential because Pivotal has to remain technology-agnostic and it can’t favor Dell products and services over that mission. “It’s necessary because our core product is a cloud-agnostic platform. Our core value proposition is independence from any provider — and Dell and VMware are infrastructure providers,” he said.

That said, Mee also can play both sides because he can build products and services that do align with Dell and VMware offerings. “Certainly the companies inside the Dell family are customers of ours. Michael Dell has encouraged the IT group to adopt our methods and they are doing so,” he said. They have also started working more closely with VMware, announcing a container partnership last year.

Photo: Ron Miller

Overall though he sees his company’s mission in much broader terms, doing nothing less than helping the world’s largest companies transform their organizations. “Our mission is to transform how the world builds software. We are focused on the largest organizations in the world. What is a tailwind for us is that the reality is these large companies are at a tipping point of adopting how they digitize and develop software for strategic advantage,” Mee said.

The stock closed up 5 percent last night, but Mee says this isn’t about a single day. “We do very much focus on the long term. We have been executing to a quarterly cadence and have behaved like a public company inside Pivotal [even before the IPO]. We know how to do that while keeping an eye on the long term,” he said.

Source: Tech Crunch

In the NYC enterprise startup scene, security is job one

While most people probably would not think of New York as a hotbed for enterprise startups of any kind, it is actually quite active. When you stop to consider that the world’s biggest banks and financial services companies are located there, it would certainly make sense for security startups to concentrate on such a huge potential market — and it turns out, that’s the case.

According to Crunchbase, there are dozens of security startups based in the city with everything from biometrics and messaging security to identity, security scoring and graph-based analysis tools. Some established companies like Symphony, which was originally launched in the city (although it is now on the west coast), has raised almost $300 million. It was actually formed by a consortium of the world’s biggest financial services companies back in 2014 to create a secure unified messaging platform.

There is a reason such a broad-based ecosystem is based in a single place. The companies who want to discuss these kinds of solutions aren’t based in Silicon Valley. This isn’t typically a case of startups selling to other startups. It’s startups who have been established in New York because that’s where their primary customers are most likely to be.

In this article, we are looking at a few promising early-stage security startups based in Manhattan

Hypr: Decentralizing identity

Hypr is looking at decentralizing identity with the goal of making it much more difficult to steal credentials. As company co-founder and CEO George Avetisov puts it, the idea is to get rid of that credentials honeypot sitting on the servers at most large organizations, and moving the identity processing to the device.

Hypr lets organizations remove stored credentials from the logon process. Photo: Hypr

“The goal of these companies in moving to decentralized authentication is to isolate account breaches to one person,” Avetisov explained. When you get rid of that centralized store, and move identity to the devices, you no longer have to worry about an Equifax scenario because the only thing hackers can get is the credentials on a single device — and that’s not typically worth the time and effort.

At its core, Hypr is an SDK. Developers can tap into the technology in their mobile app or website to force the authorization to the device. This could be using the fingerprint sensor on a phone or a security key like a Yubikey. Secondary authentication could include taking a picture. Over time, customers can delete the centralized storage as they shift to the Hypr method.

The company has raised $15 million and has 35 employees based in New York City.

Uplevel Security: Making connections with graph data

Uplevel’s founder Liz Maida began her career at Akamai where she learned about the value of large data sets and correlating that data to events to help customers understand what was going on behind the scenes. She took those lessons with her when she launched Uplevel Security in 2014. She had a vision of using a graph database to help analysts with differing skill sets understand the underlying connections between events.

“Let’s build a system that allows for correlation between machine intelligence and human intelligence,” she said. If the analyst agrees or disagrees, that information gets fed back into the graph, and the system learns over time the security events that most concern a given organization.

“What is exciting about [our approach] is you get a new alert and build a mini graph, then merge that into the historical data, and based on the network topology, you can start to decide if it’s malicious or not,” she said.

Photo: Uplevel

The company hopes that by providing a graphical view of the security data, it can help all levels of security analysts figure out the nature of the problem, select a proper course of action, and further build the understanding and connections for future similar events.

Maida said they took their time creating all aspects of the product, making the front end attractive, the underlying graph database and machine learning algorithms as useful as possible and allowing companies to get up and running quickly. Making it “self serve” was a priority, partly because they wanted customers digging in quickly and partly with only 10 people, they didn’t have the staff to do a lot of hand holding.

Security Scorecard: Offering a way to measure security

The founders of Security Scorecard met while working at the NYC ecommerce site, Gilt. For a time ecommerce and adtech ruled the startup scene in New York, but in recent times enterprise startups have really started to come on. Part of the reason for that is many people started at these foundational startups and when they started their own companies, they were looking to solve the kinds of enterprise problems they had encountered along the way. In the case of Security Scorecard, it was how could a CISO reasonably measure how secure a company they were buying services from was.

Photo: Security Scorecard

“Companies were doing business with third-party partners. If one of those companies gets hacked, you lose. How do you vett the security of companies you do business with” company co-founder and CEO Aleksandr Yampolskiy asked when they were forming the company.

They created a scoring system based on publicly available information, which wouldn’t require the companies being evaluated to participate. Armed with this data, they could apply a letter grade from A-F. As a former CISO at Gilt, it was certainly a paint point he felt personally. They knew some companies did undertake serious vetting, but it was usually via a questionnaire.

Security Scorecard was offering a way to capture security signals in an automated way and see at a glance just how well their vendors were doing. It doesn’t stop with the simple letter grade though, allowing you to dig into the company’s strengths and weaknesses and see how they compare to other companies in their peer groups and how they have performed over time.

It also gives customers the ability to see how they compare to peers in their own industry and use the number to brag about their security position or conversely, they could use it to ask for more budget to improve it.

The company launched in 2013 and has raised over $62 million, according to Crunchbase. Today, they have 130 employees and 400 enterprise customers.

If you’re an enterprise security startup, you need to be where the biggest companies in the world do business. That’s in New York City, and that’s precisely why these three companies, and dozens of others have chosen to call it home.

Source: Tech Crunch

Through luck and grit, Datadog is fusing the culture of developers and operations

There used to be two cultures in the enterprise around technology. On one side were software engineers, who built out the applications needed by employees to conduct the business of their companies. On the other side were sysadmins, who were territorially protective of their hardware domain — the servers, switches, and storage boxes needed to power all of that software. Many a great comedy routine has been made at the interface of those two cultures, but they remained divergent.

That is, until the cloud changed everything. Suddenly, there was increasing overlap in the skills required for software engineering and operations, as well as a greater need for collaboration between the two sides to effectively deploy applications. Yet, while these two halves eventually became one whole, the software monitoring tools used by them were often entirely separate.

New York City-based Datadog was designed to bring these two cultures together to create a more nimble and collaborative software and operations culture. Founded in 2010 by Olivier Pomel and Alexis Lê-Quôc, the product offers monitoring and analytics for cloud-based workflows, allowing ops team to track and analyze deployments and developers to instrument their applications. Pomel said that “the root of all of this collaboration is to make sure that everyone has the same understanding of the problem.”

The company has had dizzying success. Pomel declined to disclose precise numbers, but says the company had “north of $100 million” of recurring revenue in the past twelve months, and “we have been doubling that every year so far.” The company, headquartered in the New York Times Building in Times Square, employs more than 600 people across its various worldwide offices. The company has raised nearly $150 million of venture capital according to Crunchbase, and is perennially on banker’s short lists for strong IPO prospects.

The real story though is just how much luck and happenstance can help put wind in the sails of a company.

Pomel first met Lê-Quôc while an undergraduate in France. He was working on running the campus network, and helped to discover that Lê-Quôc had hacked the network. Lê-Quôc was eventually disconnected, and Pomel would migrate to IBM’s upstate New York offices after graduation. After IBM, he led technology at Wireless Generation, a K-12 startup, where he ran into Lê-Quôc again, who was heading up ops for the company. The two cultures of develops and ops was glaring at the startup, where “we had developers who hated operations” and there was much “finger-pointing.”

Putting aside any lingering grievances from their undergrad days, the two began to explore how they could ameliorate the cultural differences they witnessed between their respective teams. “Bringing dev and ops together is not a feature, it is core,” Pomel explained. At the same time, they noticed that companies were increasingly talking about building on Amazon Web Services, which in 2009, was still a relatively new concept. They incorporated Datadog in 2010 as a cloud-first monitoring solution, and launched general availability for the product in 2012.

Luck didn’t just bring the founders together twice, it also defined the currents of their market. Datadog was among the first cloud-native monitoring solutions, and the superlative success of cloud infrastructure in penetrating the enterprise the past few years has benefitted the company enormously. We had “exactly the right product at the right time,” Pomel said, and “a lot of it was luck.” He continued, “It’s healthy to recognize that not everything comes from your genius, because what works once doesn’t always work a second time.”

While startups have been a feature in New York for decades, enterprise infrastructure was in many ways in a dark age when the company launched, which made early fundraising difficult. “None of the West Coast investors were listening,” Pomel said, and “East Coast investors didn’t understand the infrastructure space well enough to take risks.” Even when he could get a West Coast VC to chat with him, they “thought it was a form of mental impairment to start an infrastructure startup in New York.”

Those fundraising difficulties ended up proving a boon for Datadog, because it forced the company to connect with customers much earlier and more often than it might have otherwise. Pomel said, “it forced us to spend all of our time with customers and people who were related to the problem” and ultimately, “it grounded us in the customer problem.” Pomel believes that the company’s early DNA of deeply listening to customers has allowed it to continue to outcompete its rivals on the West Coast.

More success is likely to come as companies continue to move their infrastructure onto the cloud. Datadog used to have a roughly even mix of private and public cloud business, and now the balance is moving increasingly toward the public side. Even large financial institutions, which have been reticent in transitioning their infrastructures, have now started to aggressively embrace cloud as the future of computing in the industry, according to Pomel.

Datadog intends to continue to add new modules to its core monitoring toolkit and expand its team. As the company has grown, so has the need to put in place more processes as parts of the company break. Quoting his co-founder, Pomel said the message to employees is “don’t mind the rattling sound — it is a spaceship, not an airliner” and “things are going to break and change, and it is normal.”

Much as Datadog has bridged the gap between developers and ops, Pomel hopes to continue to give back to the New York startup ecosystem by bridging the gap between technical startups and venture capital. He has made a series of angel investments into local emerging enterprise and data startups, including Generable, Seva, and Windmill. Hard work and a lot of luck is propelling Datadog into the top echelon of enterprise startups, pulling New York along with it.

Source: Tech Crunch

NS1 brings domain name services to the enterprise

When you think about critical infrastructure, DNS or domain naming services might not pop into your head, but what is more important than making sure your website opens quickly and efficiently for your users. NS1 is a New York City startup trying to bring software smarts and automation to the DNS space.

“We’re a DNS and [Internet] traffic management technology company. We sit in a critical path. Companies point domains at our platforms,” company CEO and co-founder Kris Beevers told TechCrunch. That means when you type in the domain name like, you go to Google and you go there fast. It’s basic internet plumbing, but it’s essential.

Beevers cut his teeth as head of engineering at Voxel, a cloud infrastructure company that was acquired by Internap in 2012 for $35 million. He and his NS1 co-founders saw an opening in the DNS space and launched the company in 2013 with a set of software-defined DNS services. The startup was able to take advantage of the New York startup ecosystem early on to drive some business, even before they went looking for funding, but one incident really helped put the company on the map and effectively double its business.

That event occurred in almost exactly two years ago in 2016. One of NS1’s primary competitors, Dyn, a New Hampshire-based DNS company was the victim of a massive DDoS attack that took down the service for hours. When critical infrastructure like your domain name server goes away, you see the consequences pretty starkly and suddenly customers realized they didn’t just need this service, they needed redundancy in case the primary service went down — and with that attack, NS1’s business effectively doubled overnight.

Suddenly everyone who owned one, needed another for redundancy. One competitor’s misfortune turned out to be highly beneficial for NS1, who turned out to be in the right place at the right time with the right solution. Dyn was actually acquired by Oracle later that year.

“DNS had been around since 1983. The first 20 years were very boring with no commercial ecosystem,” Beevers said. Even when it went commercial in the early 2000s, nobody was looking at this as a software problem. “We saw everyone in this space was a hardware or networking vendor. Nobody was a software company. Nobody had thought about automation or how automation fit into the stack. And nobody saw the big infrastructure trends,” Beevers explained.

They got their start in the adtech startup space that was booming in NYC when they launched in 2013. These companies were willing to take a chance with an unknown startup, partly because they were looking for any edge they could get, and partly because they knew Beevers from his days at Voxall so he wasn’t a completely unknown quantity.

“Our ability around dynamic traffic management and performance reliability gave those ad companies [an advantage].They were able to take a chance on us. If we have a bad day, a customer can’t operate. We had limited infrastructure. They placed a bet on us because of the [positive] impact we had on their business.”

Today the company is growing fast, has raised close to $50 million and has close to 100 employees. While the bulk of those folks are in NYC, they have also opened offices in San Francisco, Londonderry, NH, the UK and Singapore.

Beevers says the Dyn incident in many ways brought the industry closer together. While they compete, they still need to cooperate to keep the domain system up and running. “We compete and are comrades in the internet mess. We will all fall apart if we don’t work together,” he said. As it turned out, being part of the whole New York infrastructure community didn’t hurt either.

Source: Tech Crunch

Full-Metal Packet is hosting the future of cloud infrastructure

Cloud computing has been a revolution for the data center. Rather than investing in expensive hardware and managing a data center directly, companies are relying on public cloud providers like AWS, Google Cloud, and Microsoft Azure to provide general-purpose and high-availability compute, storage, and networking resources in a highly flexible way.

Yet as workflows have moved to the cloud, companies are increasingly realizing that those abstracted resources can be enormously expensive compared to the hardware they used to own. Few companies want to go back to managing hardware directly themselves, but they also yearn to have the price-to-performance level they used to enjoy. Plus, they want to take advantage of a whole new ecosystem of customized and specialized hardware to process unique workflows — think Tensor Processing Units for machine learning applications.

That’s where Packet comes in. The New York City-based startup’s platform offers a highly-customizable infrastructure for running bare metal in the cloud. Rather than sharing an instance with other users, Packet’s customers “own” the hardware they select, so they can use all the resources of that hardware.

Even more interesting is that Packet will also deploy custom hardware to its data centers, which currently number eighteen around the world. So, for instance, if you want to deploy a quantum computing box redundantly in half of those centers, Packet will handle the logistics of installing those boxes, setting them up, and managing that infrastructure for you.

The company was founded in 2014 by Zac Smith, Jacob Smith, and Aaron Welch, and it has raised a total of $12 million in venture capital financing according to Crunchbase, with its last round led by Softbank. “I took the usual path, I went to Juilliard,” Zac Smith, who is CEO, said to me at his office, which overlooks the World Trade Center in downtown Manhattan. Double bass was a first love, but he found his way eventually into internet hosting, working as COO of New York-based Voxel.

At Voxel, Smith said that he grew up in hosting just as the cloud started taking off. “We saw this change in the user from essentially a sysadmin who cared about Tom’s Hardware, to a developer who had never opened a computer but who was suddenly orchestrating infrastructure,” he said.

Innovation is the lifeblood of developers, yet, public clouds were increasingly abstracting away any details of the underlying infrastructure from developers. Smith explained that “infrastructure was becoming increasingly proprietary, the land of few companies.” While he once thought about leaving the hosting world post-Voxel, he and his co-founders saw an opportunity to rethink cloud infrastructure from the metal up.

“Our customer is a millennial developer, 32 years old, and they have never opened an ATX case, and how could you possibly give them IT in the same way,” Smith asked. The idea of Packet was to bring back choice in infrastructure to these developers, while abstracting away the actual data center logistics that none of them wanted to work on. “You can choose your own opinion — we are hardware independent,” he said.

Giving developers more bare metal options is an interesting proposition, but it is Packet’s long-term vision that I think is most striking. In short, the company wants to completely change the model of hardware development worldwide.

VCs are increasingly investing in specialized chips and memory to handle unique processing loads, from machine learning to quantum computing applications. In some cases, these chips can process their workloads exponentially faster compared to general purpose chips, which at scale can save companies millions of dollars.

Packet’s mission is to encourage that ecosystem by essentially becoming a marketplace, connecting original equipment manufacturers with end-user developers. “We use the WeWork model a lot,” Smith said. What he means is that Packet allows you to rent space in its global network of data centers and handle all the logistics of installing and monitoring hardware boxes, much as WeWork allows companies to rent real estate while it handles the minutia like resetting the coffee filter.

In this vision, Packet would create more discerning and diverse buyers, allowing manufacturers to start targeting more specialized niches. Gone are the generic x86 processors from Intel driving nearly all cloud purchases, and in their place could be dozens of new hardware vendors who can build up their brands among developers and own segments of the compute and storage workload.

In this way, developers can hack their infrastructure much as an earlier generation may have tricked out their personal computer. They can now test new hardware more easily, and when they find a particular piece of hardware they like, they can get it running in the cloud in short order. Packet becomes not just the infrastructure operator — but the channel connecting buyers and sellers.

That’s Packet’s big vision. Realizing it will require that hardware manufacturers increasingly build differentiated chips. More importantly, companies will have to have unique workflows, be at a scale where optimizing those workflows is imperative, and realize that they can match those workflows to specific hardware to maximize their cost performance.

That may sound like a tall order, but Packet’s dream is to create exactly that kind of marketplace. If successful, it could transform how hardware and cloud vendors work together and ultimately, the innovation of any 32-year-old millennial developer who doesn’t like plugging a box in, but wants to plug in to innovation.

Source: Tech Crunch