Feb
19
2019
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Slack off — send videos instead with $11M-funded Loom

If a picture is worth a thousand words, how many emails can you replace with a video? As offices fragment into remote teams, work becomes more visual and social media makes us more comfortable on camera, it’s time for collaboration to go beyond text. That’s the idea behind Loom, a fast-rising startup that equips enterprises with instant video messaging tools. In a click, you can film yourself or narrate a screenshare to get an idea across in a more vivid, personal way. Instead of scheduling a video call, employees can asynchronously discuss projects or give “stand-up” updates without massive disruptions to their workflow.

In the 2.5 years since launch, Loom has signed up 1.1 million users from 18,000 companies. And that was just as a Chrome extension. Today Loom launches its PC and Mac apps that give it a dedicated presence in your digital work space. Whether you’re communicating across the room or across the globe, “Loom is the next best thing to being there,” co-founder Shahed Khan tells me.

Now Loom is ready to spin up bigger sales and product teams thanks to an $11 million Series A led by Kleiner Perkins . The firm’s partner Ilya Fushman, formally Dropbox’s head of product and corporate development, will join Loom’s board. He’ll shepherd Loom through today’s launch of its $10 per month per user Pro version that offers HD recording, calls-to-action at the end of videos, clip editing, live annotation drawings and analytics to see who actually watched like they’re supposed to.

“We’re ditching the suits and ties and bringing our whole selves to work. We’re emailing and messaging like never before, but though we may be more connected, we’re further apart,” Khan tells me. “We want to make it very easy to bring the humanity back in.”

Loom co-founder Shahed Khan

But back in 2016, Loom was just trying to survive. Khan had worked at Upfront Ventures after a stint as a product designer at website builder Weebly. He and two close friends, Joe Thomas and Vinay Hiremath, started Opentest to let app makers get usability feedback from experts via video. But after six months and going through the NFX accelerator, they were running out of bootstrapped money. That’s when they realized it was the video messaging that could be a business as teams sought to keep in touch with members working from home or remotely.

Together they launched Loom in mid-2016, raising a pre-seed and seed round amounting to $4 million. Part of its secret sauce is that Loom immediately starts uploading bytes of your video while you’re still recording so it’s ready to send the moment you’re finished. That makes sharing your face, voice and screen feel as seamless as firing off a Slack message, but with more emotion and nuance.

“Sales teams use it to close more deals by sending personalized messages to leads. Marketing teams use Loom to walk through internal presentations and social posts. Product teams use Loom to capture bugs, stand ups, etc.,” Khan explains.

Loom has grown to a 16-person team that will expand thanks to the new $11 million Series A from Kleiner, Slack, Cue founder Daniel Gross and actor Jared Leto that brings it to $15 million in funding. They predict the new desktop apps that open Loom to a larger market will see it spread from team to team for both internal collaboration and external discussions from focus groups to customer service.

Loom will have to hope that after becoming popular at a company, managers will pay for the Pro version that shows exactly how long each viewer watched. That could clue them in that they need to be more concise, or that someone is cutting corners on training and cooperation. It’s also a great way to onboard new employees. “Just watch this collection of videos and let us know what you don’t understand.” At $10 per month though, the same cost as Google’s entire GSuite, Loom could be priced too high.

Next Loom will have to figure out a mobile strategy — something that’s surprisingly absent. Khan imagines users being able to record quick clips from their phones to relay updates from travel and client meetings. Loom also plans to build out voice transcription to add automatic subtitles to videos and even divide clips into thematic sections you can fast-forward between. Loom will have to stay ahead of competitors like Vidyard’s GoVideo and Wistia’s Soapbox that have cropped up since its launch. But Khan says Loom looms largest in the space thanks to customers at Uber, Dropbox, Airbnb, Red Bull and 1,100 employees at HubSpot.

“The overall space of collaboration tools is becoming deeper than just email + docs,” says Fushman, citing Slack, Zoom, Dropbox Paper, Coda, Notion, Intercom, Productboard and Figma. To get things done the fastest, businesses are cobbling together B2B software so they can skip building it in-house and focus on their own product.

No piece of enterprise software has to solve everything. But Loom is dependent on apps like Slack, Google Docs, Convo and Asana. Because it lacks a social or identity layer, you’ll need to send the links to your videos through another service. Loom should really build its own video messaging system into its desktop app. But at least Slack is an investor, and Khan says “they’re trying to be the hub of text-based communication,” and the soon-to-be-public unicorn tells him anything it does in video will focus on real-time interaction.

Still, the biggest threat to Loom is apathy. People already feel overwhelmed with Slack and email, and if recording videos comes off as more of a chore than an efficiency, workers will stick to text. And without the skimability of an email, you can imagine a big queue of videos piling up that staffers don’t want to watch. But Khan thinks the ubiquity of Instagram Stories is making it seem natural to jump on camera briefly. And the advantage is that you don’t need a bunch of time-wasting pleasantries to ensure no one misinterprets your message as sarcastic or pissed off.

Khan concludes, “We believe instantly sharable video can foster more authentic communication between people at work, and convey complex scenarios and ideas with empathy.”

Feb
19
2019
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Redis Labs raises a $60M Series E round

Redis Labs, a startup that offers commercial services around the Redis in-memory data store (and which counts Redis creator and lead developer Salvatore Sanfilippo among its employees), today announced that it has raised a $60 million Series E funding round led by private equity firm Francisco Partners.

The firm didn’t participate in any of Redis Labs’ previous rounds, but existing investors Goldman Sachs Private Capital Investing, Bain Capital Ventures, Viola Ventures and Dell Technologies Capital all participated in this round.

In total, Redis Labs has now raised $146 million and the company plans to use the new funding to accelerate its go-to-market strategy and continue to invest in the Redis community and product development.

Current Redis Labs users include the likes of American Express, Staples, Microsoft, Mastercard and Atlassian . In total, the company now has more than 8,500 customers. Because it’s pretty flexible, these customers use the service as a database, cache and message broker, depending on their needs. The company’s flagship product is Redis Enterprise, which extends the open-source Redis platform with additional tools and services for enterprises. The company offers managed cloud services, which give businesses the choice between hosting on public clouds like AWS, GCP and Azure, as well as their private clouds, in addition to traditional software downloads and licenses for self-managed installs.

Redis Labs CEO Ofer Bengal told me the company’s isn’t cash positive yet. He also noted that the company didn’t need to raise this round but that he decided to do so in order to accelerate growth. “In this competitive environment, you have to spend a lot and push hard on product development,” he said.

It’s worth noting that he stressed that Francisco Partners has a reputation for taking companies forward and the logical next step for Redis Labs would be an IPO. “We think that we have a very unique opportunity to build a very large company that deserves an IPO,” he said.

Part of this new competitive environment also involves competitors that use other companies’ open-source projects to build their own products without contributing back. Redis Labs was one of the first of a number of open-source companies that decided to offer its newest releases under a new license that still allows developers to modify the code but that forces competitors that want to essentially resell it to buy a commercial license. Ofer specifically notes AWS in this context. It’s worth noting that this isn’t about the Redis database itself but about the additional modules that Redis Labs built. Redis Enterprise itself is closed-source.

“When we came out with this new license, there were many different views,” he acknowledged. “Some people condemned that. But after the initial noise calmed down — and especially after some other companies came out with a similar concept — the community now understands that the original concept of open source has to be fixed because it isn’t suitable anymore to the modern era where cloud companies use their monopoly power to adopt any successful open source project without contributing anything to it.”

Feb
19
2019
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Senseon raises $6.4M to tackle cybersecurity threats with an AI ‘triangulation’ approach

Darktrace helped pave the way for using artificial intelligence to combat malicious hacking and enterprise security breaches. Now a new U.K. startup founded by an ex-Darktrace executive has raised some funding to take the use of AI in cybersecurity to the next level.

Senseon, which has pioneered a new model that it calls “AI triangulation” — simultaneously applying artificial intelligence algorithms to oversee, monitor and defend an organization’s network appliances, endpoints and “investigator bots” covering multiple microservices — has raised $6.4 million in seed funding.

David Atkinson — the startup’s CEO and founder who had previously been the commercial director for Darktrace and before that helped pioneer new cybersecurity techniques as an operative at the U.K.’s Ministry of Defense — said that Senseon will use the funding to continue to expand its business both in Europe and the U.S. 

The deal was co-led by MMC Ventures and Mark Weatherford, who is chief cybersecurity strategist at vArmour (which itself raised money in recent weeks) and previously Deputy Under Secretary for Cybersecurity, U.S. Department of Homeland Security. Others in the round included Amadeus Capital Partners, Crane Venture Partners and CyLon, a security startup incubator in London.

As Atkinson describes it, triangulation was an analytics concept first introduced by the CIA in the U.S., a method of bringing together multiple vectors of information to unearth inconsistencies in a data set (you can read more on triangulation in this CIA publication). He saw an opportunity to build a platform that took the same kind of approach to enterprise security.

There are a number of companies that are using AI-based techniques to help defend against breaches — in addition to Darktrace, there is Hexadite (a remediation specialist acquired by Microsoft), Amazon is working in the field and many others. In fact I think you’d be hard-pressed to find any IT security company today that doesn’t claim to or actually use AI in its approach.

Atkinson claims, however, that many AI-based solutions — and many other IT security products — take siloed, single-point approaches to defending a network. That is to say, you have network appliance security products, endpoint security, perhaps security for individual microservices and so on.

But while many of these work well, you don’t always get those different services speaking to each other. And that doesn’t reflect the shape that the most sophisticated security breaches are taking today.

As cybersecurity breaches and identified vulnerabilities continue to grow in frequency and scope — with hundreds of millions of individuals’ and organizations’ data potentially exposed in the process, systems disabled, and more — we’re seeing an increasing amount of sophistication on the part of the attackers.

Yes, those malicious actors employ artificial intelligence. But — as described in this 2019 paper on the state of cybersecurity from Symantec — they are also taking advantage of bigger “surface areas” with growing networks of connected objects all up for grabs; and they are tackling new frontiers like infiltrating data in transport and cloud-based systems. (In terms of examples of new frontiers, mobile networks, biometric data, gaming networks, public clouds and new card-skimming techniques are some of the specific areas that Experian calls out.)

Senseon’s antidote has been to build a new platform that “emulates how analysts think,” said Atkinson. Looking at an enterprise’s network appliance, an endpoint and microservices in the cloud, the Senseon platform “has an autonomous conversation” using the source data, before it presents a conclusion, threat, warning or even breach alert to the organization’s security team.

“We have an ability to take observations and compare that to hypothetical scenarios. When we tell you something, it has a rich context,” he said. Single-point alternatives essentially can create “blind spots that hackers manoeuvre around. Relying on single-source intelligence is like tying one hand behind your back.”

After Senseon compiles its data, it sends out alerts to security teams in a remediation service. Interestingly, while the platform’s aim is to identify malicious activity in a network, another consequence of what it’s doing is to help organizations identify “false positives” that are not actually threats, to cut down on time and money that get wasted on investigating those.

“Organisations of all sizes need to get better at keeping pace with emerging threats, but more importantly, identifying the attacks that require intervention,” said Mina Samaan of MMC Ventures in a statement. “Senseon’s technology directly addresses this challenge by using reinforcement learning AI techniques to help over-burdened security teams better understand anomalous behaviour through a single holistic platform.”

Although Senseon is only announcing seed funding today, the company has actually been around since 2017 and already has customers, primarily in the finance and legal industries (it would only give out one customer reference, the law firm of Harbottle & Lewis).

Feb
14
2019
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Peltarion raises $20M for its AI platform

Peltarion, a Swedish startup founded by former execs from companies like Spotify, Skype, King, TrueCaller and Google, today announced that it has raised a $20 million Series A funding round led by Euclidean Capital, the family office for hedge fund billionaire James Simons. Previous investors FAM and EQT Ventures also participated, and this round brings the company’s total funding to $35 million.

There is obviously no dearth of AI platforms these days. Peltarion focus on what it calls “operational AI.” The service offers an end-to-end platform that lets you do everything from pre-processing your data to building models and putting them into production. All of this runs in the cloud and developers get access to a graphical user interface for building and testing their models. All of this, the company stresses, ensures that Peltarion’s users don’t have to deal with any of the low-level hardware or software and can instead focus on building their models.

“The speed at which AI systems can be built and deployed on the operational platform is orders of magnitude faster compared to the industry standard tools such as TensorFlow and require far fewer people and decreases the level of technical expertise needed,” Luka Crnkovic-Friis, of Peltarion’s CEO and co-founder, tells me. “All this results in more organizations being able to operationalize AI and focusing on solving problems and creating change.”

In a world where businesses have a plethora of choices, though, why use Peltarion over more established players? “Almost all of our clients are worried about lock-in to any single cloud provider,” Crnkovic-Friis said. “They tend to be fine using storage and compute as they are relatively similar across all the providers and moving to another cloud provider is possible. Equally, they are very wary of the higher-level services that AWS, GCP, Azure, and others provide as it means a complete lock-in.”

Peltarion, of course, argues that its platform doesn’t lock in its users and that other platforms take far more AI expertise to produce commercially viable AI services. The company rightly notes that, outside of the tech giants, most companies still struggle with how to use AI at scale. “They are stuck on the starting blocks, held back by two primary barriers to progress: immature patchwork technology and skills shortage,” said Crnkovic-Friis.

The company will use the new funding to expand its development team and its teams working with its community and partners. It’ll also use the new funding for growth initiatives in the U.S. and other markets.

Feb
12
2019
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Donde Search picks up $6 million to help fashion retailers with visual search

Donde Search has just closed a $6 million Series A investment led by Matrix Partners, with participation from previous investors such as senior leaders from AliExpress, Google and Waze.

Donde first launched in 2014 as a consumer-facing app that helped users search and discover apparel items based on visual characteristics rather than text-based searches. In early 2018, the company pivoted to the enterprise space, helping retailers power suggestions and related items on their websites.

Here’s how it works:

Retailers partnered with Donde hand over their product catalog and run it through the Donde algorithm, which identifies all the visual features associated with each product. Retailers can then add a widget to their site to let users search based on those features (like sleeve length or type, color or material).

As users interact with the products, the website adapts to that behavior to offer personalized product recommendations and related items.

Moreover, Donde offers an analytics dashboard that not only provides insights on the customer’s own website, but a look into trends being featured on competing e-commerce websites to understand the industry in general.

Donde was founded by Liat Zakay, who previously served as a software engineer and R&D team manager in the Israeli intelligence unit 8200. Using her technical expertise, she built Donde to solve her own problem of not having the time or energy to go through the tedious process of online shopping.

Zakay told TechCrunch that Donde is focused on apparel for now, but that the technology can be applied to almost any vertical.

“One of the interesting pieces about Donde is that it’s language agnostic,” said Zakay. “You don’t need to know what it’s called and it doesn’t matter what language you speak, you can still find what you want based on visual features. Which makes us extremely relevant to global retailers.”

The new funding, which will be used to expand the product and the team, came shortly after the announcement of Donde’s partnership with Forever 21. The fast-fashion retailer tested out the Donde platform on its mobile app and, after a month, saw a 20 percent increase in average purchase value and higher conversions. Forever 21 has now expanded the program, putting Donde on the web, as well.

Donde said it is working on pilot programs with several other retailers across the U.S. and Europe.

Fast fashion, in particular, represents a big opportunity for Donde. Because product turnover is so fast, retailers rarely have reliable data around a certain SKU, with the website being run on outdated data from last “season.”

This latest round brings Donde’s total funding to $9.5 million, with backing from UpWest, Afterdox and Golden Seeds.

Feb
06
2019
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vArmour, a security startup focused on multi-cloud deployments, raises $44M

As more organizations move to cloud-based IT architectures, a startup that’s helping them secure that data in an efficient way has raised some capital. vArmour, which provides a platform to help manage security policies across disparate public and private cloud environments in one place, is announcing today that it has raised a growth round of $44 million.

The funding is being led by two VCs that specialise in investments into security startups, AllegisCyber and NightDragon.

CEO Tim Eades said that also participating are “two large software companies” as strategic investors that vArmour works with on a regular basis but asked not to be named. (You might consider that candidates might include some of the big security vendors in the market, as well as the big cloud services providers.) This Series E brings the total raised by vArmour to $127 million.

When asked, Eades said the company would not be disclosing its valuation. That lack of transparency is not uncommon among startups, but perhaps especially should be expected at a business that operated in stealth for the first several years of its life.

According to PitchBook, vArmour was valued at $420 million when it last raised money, a $41 million round in 2016. That would put the startup’s valuation at $464 million with this round, if everything is growing at a steady pace, or possibly more if investors are keen to tap into what appears to be a growing need.

That growing need might be summarised like this: We’re seeing a huge migration of IT to cloud-based services, with public cloud services set to grow 17.3 percent in 2019. A large part of those deployments — for companies typically larger than 1,000 people — are spread across multiple private and public clouds.

This, in turn, has opened a new front in the battle to secure data amid the rising threat of cybercrime. “We believe that hybrid cloud security is a market valued somewhere between $6 billion and $8 billion at the moment,” said Eades. Cybercrime has been estimated by McAfee to cost businesses $600 billion annually worldwide. Accenture is even more bullish on the impact; it puts the impact on companies at $5.2 trillion over the next five years.

The challenge for many organizations is that they store information and apps across multiple locations — between seven and eight data centers on average for, say, a typical bank, Eades said. And while that may help them hedge bets, save money and reach some efficiencies, that lack of cohesion also opens the door to security loopholes.

“Organizations are deploying multiple clouds for business agility and reduced cost, but the rapid adoption is making it a nightmare for security and IT pros to provide consistent security controls across cloud platforms,” said Bob Ackerman, founder and managing director at AllegisCyber, in a statement. “vArmour is already servicing this need with hundreds of customers, and we’re excited to help vArmour grow to the next stage of development.”

vArmour hasn’t developed a security service per se, but it is among the companies — Cisco and others are also competing with it — that are providing a platform to help manage security policies across these disparate locations. That could either mean working on knitting together different security services as delivered in distinct clouds, or taking a single security service and making sure it works the same policies across disparate locations, or a combination of both of those.

In other words, vArmour takes something that is somewhat messy — disparate security policies covering disparate containers and apps — and helps to hand it in a more cohesive and neat way by providing a single way to manage and provision compliance and policies across all of them.

This not only helps to manage the data but potentially can help halt a breach by letting an organization put a stop in place across multiple environments.

“From my experience, this is an important solution for the cloud security space,” said Dave DeWalt, founder of NightDragon, in a statement. “With security teams now having to manage a multitude of cloud estates and inundated with regulatory mandates, they need a simple solution that’s capable of continuous compliance. We haven’t seen anyone else do this as well as vArmour.”

Eades said that one big change for his company in the last couple of years has been that, as cloud services have grown in popularity, vArmour has been putting in place a self-service version of the main product, the vArmour Application Controller, to better target smaller organizations. It’s also been leaning heavily on channel partners (Telstra, which led its previous round, is one strategic of this kind) to help with the heavy lifting of sales.

vArmour isn’t disclosing revenues or how many customers it has at the moment, but Eades said that it’s been growing at 100 percent each year for the last two and has “way more than 100 customers,” ranging from hospitals and churches through to “8-10 of the largest service providers and over 25 financial institutions.”

At this rate, he said the plan will be to take the company public in the next couple of years.

Feb
05
2019
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Backed by Benchmark, Blue Hexagon just raised $31 million for its deep learning cybersecurity software

Nayeem Islam spent nearly 11 years with chipmaker Qualcomm, where he founded its Silicon Valley-based R&D facility, recruited its entire team and oversaw research on all aspects of security, including applying machine learning on mobile devices and in the network to detect threats early.

Islam was nothing if not prolific, developing a system for on-device machine learning for malware detection, libraries for optimizing deep learning algorithms on mobile devices and systems for parallel compute on mobile devices, among other things.

In fact, because of his work, he also saw a big opportunity in better protecting enterprises from cyberthreats through deep neural networks that are capable of processing every raw byte within a file and that can uncover complex relations within data sets. So two years ago, Islam and Saumitra Das, a former Qualcomm engineer with 330 patents to his name and another 450 pending, struck out on their own to create Blue Hexagon, a now 30-person Sunnyvale, Calif.-based company that is today disclosing it has raised $31 million in funding from Benchmark and Altimeter.

The funding comes roughly one year after Benchmark quietly led a $6 million Series A round for the firm.

So what has investors so bullish on the company’s prospects, aside from its credentialed founders? In a word, speed, seemingly. According to Islam, Blue Hexagon has created a real-time, cybersecurity platform that he says can detect known and unknown threats at first encounter, then block them in “sub seconds” so the malware doesn’t have time to spread.

The industry has to move to real-time detection, he says, explaining that four new and unique malware samples are released every second, and arguing that traditional security methods can’t keep pace. He says that sandboxes, for example, meaning restricted environments that quarantine cyberthreats and keep them from breaching sensitive files, are no longer state of the art. The same is true of signatures, which are mathematical techniques used to validate the authenticity and integrity of a message, software or digital document but are being bypassed by rapidly evolving new malware.

Only time will tell if Blue Hexagon is far more capable of identifying and stopping attackers, as Islam insists is the case. It is not the only startup to apply deep learning to cybersecurity, though it’s certainly one of the first. Critics, some who are protecting their own corporate interests, also worry that hackers can foil security algorithms by targeting the warning flags they look for.

Still, with its technology, its team and its pitch, Blue Hexagon is starting to persuade not only top investors of its merits, but a growing — and broad — base of customers, says Islam. “Everyone has this issue, from large banks, insurance companies, state and local governments. Nowhere do you find someone who doesn’t need to be protected.”

Blue Hexagon can even help customers that are already under attack, Islam says, even if it isn’t ideal. “Our goal is to catch an attack as early in the kill chain as possible. But if someone is already being attacked, we’ll see that activity and pinpoint it and be able to turn it off.”

Some damage may already be done, of course. It’s another reason to plan ahead, he says. “With automated attacks, you need automated techniques.” Deep learning, he insists, “is one way of leveling the playing field against attackers.”

Feb
05
2019
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Databricks raises $250M at a $2.75B valuation for its analytics platform

Databricks, the company founded by the original team behind the Apache Spark big data analytics engine, today announced that it has raised a $250 million Series E round led by Andreessen Horowitz. Coatue Management, Green Bay Ventures, Microsoft and NEA, also participated in this round, which brings the company’s total funding to $498.5 million. Microsoft’s involvement here is probably a bit of a surprise, but it’s worth noting that it also worked with Databricks on the launch of Azure Databricks as a first-party service on the platform, something that’s still a rarity in the Azure cloud.

As Databricks also today announced, its annual recurring revenue now exceeds $100 million. The company didn’t share whether it’s cash flow-positive at this point, but Databricks CEO and co-founder Ali Ghodsi shared that the company’s valuation is now $2.75 billion.

Current customers, which the company says number around 2,000, include the likes of Nielsen, Hotels.com, Overstock, Bechtel, Shell and HP.

“What Ali and the Databricks team have built is truly phenomenal,” Green Bay Ventures co-founder Anthony Schiller told me. “Their success is a testament to product innovation at the highest level. Databricks is without question best-in-class and their impact on the industry proves it. We were thrilled to participate in this round.”

While Databricks is obviously known for its contributions to Apache Spark, the company itself monetizes that work by offering its Unified Analytics platform on top of it. This platform allows enterprises to build their data pipelines across data storage systems and prepare data sets for data scientists and engineers. To do this, Databricks offers shared notebooks and tools for building, managing and monitoring data pipelines, and then uses that data to build machine learning models, for example. Indeed, training and deploying these models is one of the company’s focus areas these days, which makes sense, given that this is one of the main use cases for big data, after all.

On top of that, Databricks also offers a fully managed service for hosting all of these tools.

“Databricks is the clear winner in the big data platform race,” said Ben Horowitz, co-founder and general partner at Andreessen Horowitz, in today’s announcement. “In addition, they have created a new category atop their world-beating Apache Spark platform called Unified Analytics that is growing even faster. As a result, we are thrilled to invest in this round.”

Ghodsi told me that Horowitz was also instrumental in getting the company to re-focus on growth. The company was already growing fast, of course, but Horowitz asked him why Databricks wasn’t growing faster. Unsurprisingly, given that it’s an enterprise company, that means aggressively hiring a larger sales force — and that’s costly. Hence the company’s need to raise at this point.

As Ghodsi told me, one of the areas the company wants to focus on is the Asia Pacific region, where overall cloud usage is growing fast. The other area the company is focusing on is support for more verticals like mass media and entertainment, federal agencies and fintech firms, which also comes with its own cost, given that the experts there don’t come cheap.

Ghodsi likes to call this “boring AI,” since it’s not as exciting as self-driving cars. In his view, though, the enterprise companies that don’t start using machine learning now will inevitably be left behind in the long run. “If you don’t get there, there’ll be no place for you in the next 20 years,” he said.

Engineering, of course, will also get a chunk of this new funding, with an emphasis on relatively new products like MLFlow and Delta, two tools Databricks recently developed and that make it easier to manage the life cycle of machine learning models and build the necessary data pipelines to feed them.

Jan
24
2019
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Humio raises $9M Series A for its real-time log analysis platform

Humio, a startup that provides a real-time log analysis platform for on-premises and cloud infrastructures, today announced that it has raised a $9 million Series A round led by Accel. It previously raised its seed round from WestHill and Trifork.

The company, which has offices in San Francisco, the U.K. and Denmark, tells me that it saw a 13x increase in its annual revenue in 2018. Current customers include Bloomberg, Microsoft and Netlify .

“We are experiencing a fundamental shift in how companies build, manage and run their systems,” said Humio CEO Geeta Schmidt. “This shift is driven by the urgency to adopt cloud-based and microservice-driven application architectures for faster development cycles, and dealing with sophisticated security threats. These customer requirements demand a next-generation logging solution that can provide live system observability and efficiently store the massive amounts of log data they are generating.”

To offer them this solution, Humio raised this round with an eye toward fulfilling the demand for its service, expanding its research and development teams and moving into more markets across the globe.

As Schmidt also noted, many organizations are rather frustrated by the log management and analytics solutions they currently have in place. “Common frustrations we hear are that legacy tools are too slow — on ingestion, searches and visualizations — with complex and costly licensing models,” she said. “Ops teams want to focus on operations — not building, running and maintaining their log management platform.”

To build this next-generation analysis tool, Humio built its own time series database engine to ingest the data, with open-source tools like Scala, Elm and Kafka in the backend. As data enters the pipeline, it’s pushed through live searches and then stored for later queries. As Humio VP of Engineering Christian Hvitved tells me, though, running ad-hoc queries is the exception, and most users only do so when they encounter bugs or a DDoS attack.

The query language used for the live filters is also pretty straightforward. That was a conscious decision, Hvitved said. “If it’s too hard, then users don’t ask the question,” he said. “We’re inspired by the Unix philosophy of using pipes, so in Humio, larger searches are built by combining smaller searches with pipes. This is very familiar to developers and operations people since it is how they are used to using their terminal.”

Humio charges its customers based on how much data they want to ingest and for how long they want to store it. Pricing starts at $200 per month for 30 days of data retention and 2 GB of ingested data.

Jan
23
2019
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Anchorage emerges with $17M from a16z for ‘omnimetric’ crypto security

I’m not allowed to tell you exactly how Anchorage keeps rich institutions from being robbed of their cryptocurrency, but the off-the-record demo was damn impressive. Judging by the $17 million Series A this security startup raised last year led by Andreessen Horowitz and joined by Khosla Ventures, #Angels, Max Levchin, Elad Gil, Mark McCombe of Blackrock and AngelList’s Naval Ravikant, I’m not the only one who thinks so. In fact, crypto funds like Andreessen’s a16z crypto, Paradigm and Electric Capital are already using it.

They’re trusting in the guys who engineered Square’s first encrypted card reader and Docker’s security protocols. “It’s less about us choosing this space and more about this space choosing us. If you look at our backgrounds and you look at the problem, it’s like the universe handed us on a silver platter the Venn diagram of our skill set,” co-founder Diogo Monica tells me.

Today, Anchorage is coming out of stealth and launching its cryptocurrency custody service to the public. Anchorage holds and safeguards crypto assets for institutions like hedge funds and venture firms, and only allows transactions verified by an array of biometrics, behavioral analysis and human reviewers. And because it doesn’t use “buried in the backyard” cold storage, asset holders can actually earn rewards and advantages for participating in coin-holder votes without fear of getting their Bitcoin, Ethereum or other coins stolen.

The result is a crypto custody service that could finally lure big-time commercial banks, endowments, pensions, mutual funds and hedgies into the blockchain world. Whether they seek short-term gains off of crypto volatility or want to HODL long-term while participating in coin governance, Anchorage promises to protect them.

Evolving past “pirate security”

Anchorage’s story starts eight years ago when Monica and his co-founder Nathan McCauley met after joining Square the same week. Monica had been getting a PhD in distributed systems while McCauley designed anti-reverse engineering tech to keep U.S. military data from being extracted from abandoned tanks or jets. After four years of building systems that would eventually move more than $80 billion per year in credit card transactions, they packaged themselves as a “pre-product acqui-hire” Monica tells me, and they were snapped up by Docker.

As their reputation grew from work and conference keynotes, cryptocurrency funds started reaching out for help with custody of their private keys. One had lost a passphrase and the $1 million in currency it was protecting in a display of jaw-dropping ignorance. The pair realized there were no true standards in crypto custody, so they got to work on Anchorage.

“You look at the status quo and it was and still is cold storage. It’s the same technology used by pirates in the 1700s,” Monica explains. “You bury your crypto in a treasure chest and then you make a treasure map of where those gold coins are,” except with USB keys, security deposit boxes and checklists. “We started calling it Pirate Custody.” Anchorage set out to develop something better — a replacement for usernames and passwords or even phone numbers and two-factor authentication that could be misplaced or hijacked.

This led them to Andreessen Horowitz partner and a16z crypto leader Chris Dixon, who’s now on their board. “We’ve been buying crypto assets running back to Bitcoin for years now here at a16z crypto. [Once you’re holding crypto,] it’s hard to do it in a way that’s secure, regulatory compliant, and lets you access it. We felt this pain point directly.”

Andreessen Horowitz partner and Anchorage board member Chris Dixon

It’s at this point in the conversation when Monica and McCauley give me their off-the-record demo. While there are no screenshots to share, the enterprise security suite they’ve built has the polish of a consumer app like Robinhood. What I can say is that Anchorage works with clients to whitelist employees’ devices. It then uses multiple types of biometric signals and behavioral analytics about the person and device trying to log in to verify their identity.

But even once they have access, Anchorage is built around quorum-based approvals. Withdrawals, other transactions and even changing employee permissions requires approval from multiple users inside the client company. They could set up Anchorage so it requires five of seven executives’ approval to pull out assets. And finally, outlier detection algorithms and a human review the transaction to make sure it looks legit. A hacker or rogue employee can’t steal the funds even if they’re logged in because they need consensus of approval.

That kind of assurance means institutional investors can confidently start to invest in crypto assets. That swell of capital could help replace the retreating consumer investors who’ve fled the market this year, leading to massive price drops. The liquidity provided by these asset managers could keep the whole blockchain industry moving. “Institutional investing has had centuries to build up a set of market infrastructure. Custody was something that for other asset classes was solved hundreds of years ago, so it’s just now catching up [for crypto],” says McCauley. “We’re creating a bigger market in and of itself,” Monica adds.

With Anchorage steadfastly handling custody, the risk these co-founders admit worries them lies in the smart contracts that govern the cryptocurrencies themselves. “We need to be extremely wide in our level of support and extremely deep because each blockchain has details of implementation. This is inherently a very difficult problem,” McCauley explains. It doesn’t matter if the coins are safe in Anchorage’s custody if a janky smart contract can botch their transfer.

There are plenty of startups vying to offer crypto custody, ranging from Bitgo and Ledger to well-known names like Coinbase and Gemini. Yet Anchorage offers a rare combination of institutional-since-day-one security rigor with the ability to participate in votes and governance of crypto assets that’s impossible if they’re in cold storage. Down the line, Anchorage hints that it might serve clients recommendations for how to vote to maximize their yield and preserve the sanctity of their coin.

They’ll have crypto investment legend Chris Dixon on their board to guide them. “What you’ll see is in the same way that institutional investors want to buy stock in Facebook and Google and Netflix, they’ll want to buy the equivalent in the world 10 years from now and do that safely,” Dixon tells me. “Anchorage will be that layer for them.”

But why do the Anchorage founders care so much about the problem? McCauley concludes that, “When we look at what’s potentially possible with crypto, there a fundamentally more accessible economy. We view ourselves as a key component of bringing that future forward.”

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