SaaS
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Zuora partners with Amazon Pay to expand subscription billing options
Zuora, the SaaS company helping organizations manage payments for subscription businesses, announced today that it had been selected as a Premier Partner in the Amazon Pay Global Partner Program.
The “Premier Partner” distinction means businesses using Zuora’s billing platform can now easily integrate Amazon’s digital payment system as an option during checkout or recurring payment processes.
The strategic rationale for Zuora is clear, as the partnership expands the company’s product offering to prospective and existing customers. The ability to support a wide array of payment methodologies is a key value proposition for subscription businesses that enables them to service a larger customer base and provide a more seamless customer experience.
It also doesn’t hurt to have a deep-pocketed ally like Amazon in a fairly early-stage industry. With omnipotent tech titans waging war over digital payment dominance, Amazon has reportedly doubled down on efforts to spread Amazon Pay usage, cutting into its own margins and offering incentives to retailers.
As adoption of Amazon Pay spreads, subscription businesses will be compelled to offer the service as an available payment option and Zuora should benefit from supporting early billing integration.
For Amazon Pay, teaming up with Zuora provides direct access to Zuora’s customer base, which caters to tens of millions of subscribers.
With Zuora minimizing the complexity of adding additional payment options, which can often disrupt an otherwise unobtrusive subscription purchase experience, the partnership with Zuora should help spur Amazon Pay adoption and reduce potential friction.
“By extending the trust and convenience of the Amazon experience to Zuora, merchants around the world can now streamline the subscription checkout experience for their customers,” said Vice President of Amazon Pay, Patrick Gauthier. “We are excited to be working with Zuora to accelerate the Amazon Pay integration process for their merchants and provide a fast, simple and secure payment solution that helps grow their business.”
The world subscribed
The collaboration with Amazon Pay represents another milestone for Zuora, which completed its IPO in April of this year and is now looking to further differentiate its offering from competing in-house systems or large incumbents in the Enterprise Resource Planning (ERP) space, such as Oracle or SAP.
Going forward, Zuora hopes to play a central role in ushering a broader shift towards a subscription-based economy.
Tien Tzuo, founder and CEO of Zuora, told TechCrunch he wants the company to help businesses first realize they should be in the subscription economy and then provide them with the resources necessary to flourish within it.
“Our vision is the world subscribed.” said Tzuo. “We want to be the leading company that has the right technology platform to get companies to be successful in the subscription economy.”
The partnership will launch with publishers “The Seattle Times” and “The Telegraph”, with both now offering Amazon Pay as a payment method while running on the Zuora platform.
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Shared inbox startup Front launches a complete redesign
Front is launching a major revamp today. And it starts with a brand new design. Front is now powered by React for the web and desktop app, which should make it easier to add new features down the road.
Front hasn’t pivoted to become something else. At heart, it remains a multiplayer email client. You can share generic email addresses with your coworkers, such as sales@yourcompany or jobs@yourcompany. You can then assign emails, comment before replying and integrate your CRM with your email threads.
But the company is also adding a bunch of new features. The most interesting one is the ability to start a thread with your team without having to send an email first. If a client sends you an email, you can comment on the thread and mention your coworkers just like on a Facebook post.
Many companies already use emails for internal communications. So they started using Front to talk to their coworkers. Before today, you had to send an original email and then people could comment on it. Now, you can just create a post by giving it a title and jumping to the comment section. It’s much more straightforward.
“We aren’t planning for all internal conversations to move to Front, but a lot of them very well could. A tool like Slack is often used for questions that don’t require the immediate response that Slack demands,” co-founder and CEO Mathilde Collin told me. “By bringing these messages into Front, we aim to reduce disruptions and help people stay focused.”
In other words, a Slack message feels like a virtual tap on the shoulder. You have to interrupt what you’re doing to take a minute and answer. Front can be used for asynchronous conversations and things that don’t need an immediate response. That’s why you can now also send Slack messages to Front so that you can deal with them in Front.
With this update, Front is making sharing more granular. Front isn’t just about shared addresses. You can assign your personal emails to a coworker — this is much more efficient than forwarding an email. Now, you can easily see who can read and interact with an email thread at the top of the email view.
If somebody sends an email to Sarah and Sam, they’ll both have a copy of this email in their personal inboxes. If Sarah and Sam start commenting and @-mentioning people, Front will now merge the threads.
As a user, you get a unified inbox with all your personal emails, emails that were assigned to you and messages assigned to your team inbox.
Finally, Front has improved its smart filtering system. You can now create more flexible rules. For instance, if an email matches some or all criteria, Front can assign an email to a team or a person, send an automated reply, trigger another rule and more.
The new version of Front will be available later this month. Once again, Front remains focused on its core mission — making work conversations more efficient and more flexible. The company doesn’t try to reinvent the wheel and still relies heavily on emails.
Many people (myself included) say that email is too often a waste of time. Dealing with emails doesn’t necessarily mean getting work done. Front wants to remove all the pains of this messaging protocol so that you can focus on the content of the messages.
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Zenefits’ Parker Conrad returns with Rippling to kill HR & IT busywork
Parker Conrad likes to save time, even though it’s gotten him in trouble. The former CEO of Zenefits was pushed out of the $4.5 billion human resources startup because he built a hack that let him and employees get faster insurance certifications. But 2.5 years later, he’s back to take the busy work out of staff onboarding as well as clumsy IT services like single sign-on to enterprise apps. Today his startup Rippling launches its combined employee management system, which Conrad calls a much larger endeavor than the minimum viable product it announced while in Y Combinator’s accelerator 18 months ago.
“It’s not an HR system. It’s a level below that,” Conrad tells me. “It’s this unholy, crazy mashup of three different things.” First, it handles payroll, benefits, taxes and PTO across all 50 states. “Except Syria and North Korea, you can pay anyone in the world with Rippling,” Conrad claims. That makes it a competitor with Gusto… and Zenefits.
Second, it’s a replacement for Okta, Duo and other enterprise single-sign on security apps that authenticate staffers across partnered apps. Rippling bookmarklets make it easy to auth into over 250 workplace apps, like Gmail, Slack, Dropbox, Asana, Trello, AWS, Salesforce, GitHub and more. When an employee is hired or changes teams, a single modification to their role in Rippling automatically changes all the permissions of what they can access.
And third, it handles computer endpoint security like Jamf. When an employee is hired, Rippling can instantly ship them a computer with all the right software installed and the hard drive encrypted, or have staffers add the Rippling agent that enforces the company’s security standards. The system is designed so there’s no need for an expert IT department to manage it.
“Distributed, fragmented systems of record for employee data are secretly the cause of almost all the annoying administrative work of running a company,” Conrad explains. “If you could build this system that ties all of it together, you could eliminate all this crap work.” That’s Rippling. It’s opening up to all potential clients today, charging them a combined subscription or à la carte fees for any of the three wings of the product.
Conrad refused to say how much Rippling has raised total, citing the enhanced scrutiny Zenefits’ raises drew. But he says a Wall Street Journal report that Rippling had raised $7 million was inaccurate. “We haven’t raised any priced VC rounds. Just a bunch of seed money. We raised from Initialized Capital, almost all the early seed investors at Zenefits and a lot of individuals.” He cited Y Combinator, YC Growth Fund, YC’s founder Jessica Livingston and president Sam Altman, other YC partners, as well as DFJ and SV Angel.
“Because we were able to raise a bunch of money and court great engineers . . . we were able to spend a lot of time building this fundamental technology,” Conrad tells me. Rippling has about 50 team members now, with about 40 of them being engineers, highlighting just how thoroughly Conrad wants to eradicate manual work about work, starting with his own startup.
The CEO refused to discuss details of exactly what went down at Zenefits and whether he thought his ejection was fair. He was accused of allowing Zenefits’ insurance brokers to sell in states where they weren’t licensed, and giving some employees a macro that let them more quickly pass the online insurance certification exam. Conrad ended up paying about $534,000 in SEC fines. Zenefits laid off 430 employees, or 45 percent of its staff, and moved to selling software to small-to-medium sized businesses through a network of insurance brokers.
But when asked what he’d learned from Zenefits, Conrad looked past those troubles and instead recalled that “one of the mistakes that we made was that we did a lot stuff manually behind the scenes. When you scale up, there are these manual processes, and it’s really hard to come back later when it’s a big hard complicated thing and replace it with technology. You get upside down on margins. If you start at the beginning and never let the manual processes creep in . . . it sort of works.”
Perhaps it was trying to cut corners that got Conrad into the Zenefits mess, but now that same intention has inspired Rippling’s goal of eliminating HR and IT drudgery with an all-in-one tool.
“I think I’m someone who feels the pain of that kind of stuff particularly strongly. So that’s always been a real irritant to me, and I saw this problem. The conventional wisdom is ‘don’t build something like this, start with something much smaller,’ ” Conrad concludes. “But I knew if I didn’t do this, that no one else was gong to do it and I really wanted this system to exist. This is a company that’s all about annoying stuff and making that fucking annoying stuff go away.”
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RankScience closes $1.8M seed — and now only wants to replace human SEO staff if you don’t have any
A couple of years ago YC-backed RankScience, which offers AI-enhanced SEO split-testing, put a few SEO experts’ noses out of joint when the fledgling startup brashly talked about replacing human expertise with automation.
Two years on its pitch has mellowed, with the team saying their self-service platform is “augmenting human SEO ability rather than replacing them”.
The startup has also — finally — closed a seed round, announcing $1.8M led by Initialized Capital, along with Adam D’Angelo, Michael Seibel, BoxGroup, Liquid2 Ventures, FundersClub, and Jenny 8 Lee participating.
The new roster of investors join a list of prior backers that includes Y Combinator, 500 Startups, Christina Cacioppo, and Jack Groetzinger.
So what took them so long? Founder Ryan Bednar tells TechCrunch they wanted to take their time with the seed, rather than raise more money than they needed — a position that was possible thanks to already being profitable at YC Demo Day.
“I admit that this is unusual,” he says of the slow seed, though he also says they did raise a “small amount” after demo day, before filling out the rest this month.
“I saw many YC batchmates raising massive rounds pre product-market-fit, which can end up being a mistake,” he adds. “We probably could have raised a few million at Demo Day but ultimately didn’t feel we were ready for it. I didn’t know what I would spend the money on, and we were growing without it, so we chose not to. I wanted to raise capital when I felt we were ready to use it for growth, and now’s that time.”
Bednar also says he is “selective” when it comes to investors — and “specifically” wanted to work with Initialized, saying he’s “known Garry and Alexis personally for years, and trust that they would support us in building a long-term scalable business”.
Commenting on the funding to TechCrunch, Initialized Capital’s Alexis Ohanian tells us: “Even though so many businesses depend on traffic from search, it’s a challenge for them to be data-driven about SEO. RankScience makes it easy to test changes to your website that can lift search traffic. They also automate a growing number of technical SEO tasks, which otherwise would take engineers away from building product and infrastructure, which is really exciting.”
RankScience plans to use the fresh funding to hire more AI and machine learning engineers, with headcount growth targeted at its SF office.
While the founders have stepped back from pronouncing ‘the death of the SEO expert’, they are still touting the power of automation AI for SEO — noting how, after crawling a customer’s site/s, the software automatically proposes “SEO enhancements and experiments” to customers — for “one-click [human] approval”.
It also includes what Bednar bills as a “self-driving car mode” — where the tech will deploy the touted “enhancements and experiments” without customer approval. But he concedes it’s not for all RankScience users.
“For about half of our customers, we’re their only SEO vendor so we automate SEO services 100% for them, and for the other half, our software augments human SEO ability, either from in-house marketers or agencies,” he says, explaining how the team has evolved their thinking on automation vs human agency and expertise.
“When we launched we didn’t think hard enough about what sorts of controls SEO managers at larger websites would want, and we tried to automate everything without giving marketers enough control. This was a mistake and we’ve worked hard on correcting it.
“This should have been obvious but it turns out that SEO managers are highly selective about what sorts of HTML changes our software might make to their webpages. So we’ve spent the past year building tools to give SEO marketers complete control over everything our software does, and also advanced editors and tools so they can create their own SEO enhancements and run SEO split tests through the platform.”
For those who make use of RankScience’s ‘Self-Driving Car Mode’ the software is replacing SEO staff “completely”, but he adds: “This works especially well for startups and medium size businesses. But SEO is such a multifaceted problem, we want to give larger companies with marketing teams complete control over our platform, and so we work with both types of customers.”
As well as (finally) closing out its seed round now, RankScience is also launching a new self-service platform for startups and SMEs — touting greater controls.
On the customer front, Bednar says they have “hundreds” of sites on the platform now — and are serving “hundreds of millions of page views per month”. Cumulatively he says they’ve deployed “millions” of SEO split tests at this point.
“Our customers run the gamut from startups just getting started with SEO to publicly-traded companies,” he continues. “Our best industries are SaaS, ecommerce, marketplaces, healthcare, publishing, and location-based sites.
“We’ve recently been working with more consumer goods brands, and we’ve also launched a partnership program so that we can work with SEO and Digital Marketing Agencies and independent consultants.”
He says the vast majority of RankScience users are based in the US at this stage but adds that Europe is a “growing market”.
In terms of competition, Bednar name-checks the likes of Moz, Conductor (acquired this year by WeWork), BloomReach and BrightEdge — so it is swimming in a pool with some very big fish.
“Most of these products are more akin to advanced SEO analytics suites, and we differ in that RankScience is 100% focused on data-driven SEO automation,” he says, fleshing out the differences and RankScience’s edge, as he sees it. “Our software doesn’t just tell you what changes to make to your site to increase search traffic, it actually makes the changes for you. (Now with more controls!)”
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Why Blissfully decided to go all in on serverless
Serverless has become a big buzzword of late, and with good reason. It has the potential to completely alter how developers write code. They can simply write a series of event triggers, while letting the cloud vendor worry about providing whatever amount of compute resources are required to complete the job. It represents a huge shift in how programs are developed, but it’s been difficult to find companies who were built from the ground up using this methodology because it’s fairly new.
Blissfully, a startup that helps customers manage their Software-as-a-Service usage inside their companies, is one company that decided to do just that. Aaron White, co-founder and CTO, says that when he was building early versions of Blissfully, he found he needed quick bursts of compute power to deliver a list of all the SaaS products an organization is using.
He figured he could set aside a bunch of servers to provide that burst of power as needed, but that would have required a ton of overhead on his part to manage. At this point, he was a lone programmer trying to prove his SaaS management idea was even possible. As he looked at the pros and cons of serverless versus traditional virtual machines, he began to see serverless as a viable approach.
What he learned along the way was that serverless offers many advantages to a company with a bursty approach like Blissfully, scaling up and down as needed. But it isn’t perfect and there are issues around management and tooling and handling the pros and cons of that scaling ability that he had to learn about on the fly, especially coming in as early as he did with this approach.
Serverless makes sense
Blissfully is a service where serverless made a lot of sense. It wouldn’t have to manage or pay for servers it wasn’t using. Nor would it have to worry about the underlying infrastructure at all. That would be up to the cloud provider, and it would only pay for the bursts as they happened.
Serverless is actually a misnomer, in that it doesn’t mean there are no servers. It actually means you don’t have to set up servers in order to run your program, which is a pretty mind-blowing transformation. In traditional programming you have to write your code and set up all the underlying hardware ahead of time, whether it’s in your data center or in the cloud. With serverless, you just write the code and the cloud provider handles all of that for you.
The way it works in practice is that programmers set up a series of event triggers, so when a certain thing happens, the cloud provider sees this and provides the necessary resources on demand. Most of the cloud vendors are offering this type of service, whether AWS Lambda, Azure Functions or Google Functions.
At this point, White began to think about serverless as a way of freeing him from thinking about managing and maintaining infrastructure and all that entailed. “I started thinking, let’s see how far we can take this. Can we really do absolutely everything serverless, and if so that reduces a ton of traditional DevOps-style work you have to do in practice. There’s still plenty, but that was the thinking at the beginning,” he said.
Overcoming obstacles
But there were issues, especially getting into serverless as early as he did. For starters, White needed to find developers who could work in this fashion, and in 2016 when it launched there weren’t a large number of people out there with serverless skills. White said he wasn’t looking for direct experience so much as people who were curious to learn and were flexible enough to deal with new technology, regardless of how Blissfully implemented that.
Once he figured out the basics, he needed to think about how this would work structurally. “Part of the challenge is figuring out where do you draw the boundaries between different serverless functions? How do you think about how much you want to overload the capability of one function versus another? How do you want to split it up? You could go way too specific, and you can of course, go way too broad. So there’s a lot of judgement calls to be made in terms of how you want to split your code base to work in this way,” he said.
The other challenge he faced going with a serverless approach so early was a dearth of tooling around it. White found Serverless, Inc. right way, which helped him with a basic framework for developing, but he lacked good logging tools and says that the company still struggles with this even now. “DevOps doesn’t go away. This is still running on a server somewhere (even if you don’t control that) and you will run into issues.” One such issue he calls a “cold start issue.”
Getting the resources right
Blissfully uses AWS Lambda, and as their customers require resources, it isn’t as though Amazon has a set of dedicated resources set aside waiting for such an event. If it needs to start servers cold, that could result in latency. To compensate for that, Blissfully runs a job that pings Lambda continually, so that it’s always ready to run the actual application, and there isn’t a lag time related to starting from scratch.
The other issue could be the opposite problem. You can scale much faster than you’re ready to deal with and that can be a problem for a small team. He says in that case, you want to put a limiter on the speed of the calls so you don’t end up spending more than you can afford, and it doesn’t scale beyond your team’s ability to manage it, “I think, in some ways, this actually accelerates you running into problems where you would normally be larger scale before you really had to think about them,” White said.
The other piece is that once Lambda gets everything going, it can move data faster than your external APIs can handle, and that could require limiters to actually slow things down. “I never had that problem in the past where I was provisioning so many computational resources that Google was yelling at me for being too fast. Being too fast for Google takes a lot of effort, but it doesn’t take a lot of effort with Lambda. When it does decide to spool up whatever resources, you can do some serious outbound damage to other APIs.” That meant he and his team actually had to think very early on about building sophisticated rate-limiting schemes.
As for costs, White estimates that his costs are much lower now that he has the service built and in place. “Our costs are so low right now, and far lower than if we had server-based infrastructure. Our computational pattern is very bursty.” That’s because it re-parses the SaaS database once a day or when the customer first signs up, and in between, usage is fairly low beyond interacting with the data.
“So for us that was perfect for serverless because I don’t really need to keep capacity around that would be pure waste.”
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IBM launches cloud tool to detect AI bias and explain automated decisions
IBM has launched a software service that scans AI systems as they work in order to detect bias and provide explanations for the automated decisions being made — a degree of transparency that may be necessary for compliance purposes not just a company’s own due diligence.
The new trust and transparency system runs on the IBM cloud and works with models built from what IBM bills as a wide variety of popular machine learning frameworks and AI-build environments — including its own Watson tech, as well as Tensorflow, SparkML, AWS SageMaker, and AzureML.
It says the service can be customized to specific organizational needs via programming to take account of the “unique decision factors of any business workflow”.
The fully automated SaaS explains decision-making and detects bias in AI models at runtime — so as decisions are being made — which means it’s capturing “potentially unfair outcomes as they occur”, as IBM puts it.
It will also automatically recommend data to add to the model to help mitigate any bias that has been detected.
Explanations of AI decisions include showing which factors weighted the decision in one direction vs another; the confidence in the recommendation; and the factors behind that confidence.
IBM also says the software keeps records of the AI model’s accuracy, performance and fairness, along with the lineage of the AI systems — meaning they can be “easily traced and recalled for customer service, regulatory or compliance reasons”.
For one example on the compliance front, the EU’s GDPR privacy framework references automated decision making, and includes a right for people to be given detailed explanations of how algorithms work in certain scenarios — meaning businesses may need to be able to audit their AIs.
The IBM AI scanner tool provides a breakdown of automated decisions via visual dashboards — an approach it bills as reducing dependency on “specialized AI skills”.
However it is also intending its own professional services staff to work with businesses to use the new software service. So it will be both selling AI, ‘a fix’ for AI’s imperfections, and experts to help smooth any wrinkles when enterprises are trying to fix their AIs… Which suggests that while AI will indeed remove some jobs, automation will be busy creating other types of work.
Nor is IBM the first professional services firm to spot a business opportunity around AI bias. A few months ago Accenture outed a fairness tool for identifying and fixing unfair AIs.
So with a major push towards automation across multiple industries there also looks to be a pretty sizeable scramble to set up and sell services to patch any problems that arise as a result of increasing use of AI.
And, indeed, to encourage more businesses to feel confident about jumping in and automating more. (On that front IBM cites research it conducted which found that while 82% of enterprises are considering AI deployments, 60% fear liability issues and 63% lack the in-house talent to confidently manage the technology.)
In additional to launching its own (paid for) AI auditing tool, IBM says its research division will be open sourcing an AI bias detection and mitigation toolkit — with the aim of encouraging “global collaboration around addressing bias in AI”.
“IBM led the industry in establishing trust and transparency principles for the development of new AI technologies. It’s time to translate principles into practice,” said David Kenny, SVP of cognitive solutions at IBM, commenting in a statement. “We are giving new transparency and control to the businesses who use AI and face the most potential risk from any flawed decision making.”
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Crypto’s second bubble, Juul has 60 days and three Chinese IPOs
Hello and welcome back to Equity, TechCrunch’s venture capital-focused podcast where we unpack the numbers behind the headlines.
After a long run of having guests climb aboard each week, we took a pause on that front, bringing together three of our regular hosts instead: Connie Loizos, Danny Chrichton, and myself.
Despite the fact that there were just three of us instead of the usual four, we got through a mountain of stuff. Which was good as it was a surprisingly busy week, and we didn’t want to leave too much behind.
Up top we dug into the latest in the land of crypto, which Danny had politely summarized for us in an article. The gist of his argument is that the analogies relating crypto as an industry to the Internet may work, but most people have their timelines wrong: Crypto isn’t like the Internet in the 90s, perhaps. More like the 80s.
On the same topic, crypto companies formed a team lobbying effort, and a high-flying crypto fund is struggling to once again post strong profit figures.
Moving along, Juul is back in the news. Not, however, for raising more money or posting quick growth. Well, sort of the latter, as the government is after it. The Food and Drug Administration has put Juul on a countdown to get its act together regarding teens and smoking. That the financially impressive unicorn is in as much trouble as it is, is nearly surprising.
Finally, we ran through the three most recent Chinese IPOs that hit our radar. Here they are:
- Meituan Dianping: The Tencent-backed group buying, delivery, and everything company raised over $4 billion in its debut, which was impressive, but also short of expectations. The firm won’t begin trading until the 20th, but it’s one more massive deal that got done in 2018.
- 111: We spent a minute on the show discussing what counts as a technology company thanks to 111. We voted that the Chinese online-to-offline pharmacy startup did in fact count. So, it’s in our list. Some notes on its debut can be found here.
- NIO: Finally on our list was NIO, a Chinese electric car company with, as we have discussed on Equity before, a shockingly short history of revenue generation. Whether the company is a gamble or not, it did raise $1 billion in its own offering. And its stock is off like a rocket to boot.
And that was the end of things. Thanks for sticking with us, as always. Speaking of which, our 100th episode is coming up. Who should we bring onto the show to celebrate?
Equity drops every Friday at 6:00 am PT, so subscribe to us on Apple Podcasts, Overcast, Pocket Casts, Downcast and all the casts.
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New Relic shifts with changing monitoring landscape
New Relic CEO Lew Cirne was feeling a bit nostalgic last week when he called to discuss the announcements for the company’s FutureStack conference taking place tomorrow in San Francisco. It had been 10 years since he first spoke to TechCrunch about his monitoring tool. A lot has changed in a decade including what his company is monitoring these days.
Cirne certainly recognizes that his company has come a long way since those first days. The monitoring world is going through a seismic shift as the ways we develop apps changes. His company needs to change with it to remain relevant in today’s market.
In the early days, they monitored Ruby on Rails applications, but gone are the days of only monitoring a fixed virtual machine. Today companies are using containers and Kubernetes, and beyond that, serverless architecture. Each of these approaches brings challenges to a monitoring company like New Relic, particularly the ephemeral nature and the sheer volume associated with these newer ways of working.
‘We think those changes have actually been an opportunity for us to further differentiate and further strengthen our thesis that the New Relic way is really the most logical way to address this.” He believes that his company has always been centered on the code, as opposed to the infrastructure where it’s delivered, and that has helped it make adjustments as the delivery mechanisms have changed.
Today, the company introduced a slew of new features and capabilities designed to keep the company oriented toward the changing needs of its customer base. One of the ways they are doing that is with a new feature called Outlier Detection, which has been designed to address changes in key metrics wherever your code happens to be deployed.
Further, Incident Context lets you see exactly where the incident occurred in the code so you don’t have to go hunting and pecking to find it in the sea of data.
Outlier Detection in action. Gif: New Relic
The company also introduced developer.newrelic.com, a site that extends the base APIs to provide a central place to build on top of the New Relic platform and give customers a way to extend the platform’s functionality. Cirne said each company has its own monitoring requirements, and they want to give them ability to build for any scenario.
In addition, they announced New Relic Query Language (NRQL) data, which leverages the New Relic GraphQL API to help deliver new kinds of customized, programmed capabilities to customers that aren’t available out of the box.”What if I could program New Relic to take action when a certain thing happens. When an application has a problem, it could post a notice to the status page or restart the service. You could automate something that has been historically done manually,” he explained.
Whatever the company is doing it appears to be working It went public in 2014 with an IPO share price of $30.14 and a market cap of $1.4 billion. Today, the share price was $103.65 with a market cap of $5.86 billion (as of publishing).
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Elastic’s IPO filing is here
Elastic, the provider of subscription-based data search software used by Dell, Netflix, The New York Times and others, has unveiled its IPO filing after confidentially submitting paperwork to the SEC in June. The company will be the latest in a line of enterprise SaaS businesses to hit the public markets in 2018.
Headquartered in Mountain View, Elastic plans to raise $100 million in its NYSE listing, though that’s likely a placeholder amount. The timing of the filing suggests the company will transition to the public markets this fall; we’ve reached out to the company for more details.
Elastic will trade under the symbol ESTC.
The business is known for its core product, an open-source search tool called ElasticSearch. It also offers a range of analytics and visualization tools meant to help businesses organize large data sets, competing directly with companies like Splunk and even Amazon — a name it mentions 14 times in the filing.
“Amazon offers some of our open source features as part of its Amazon Web Services offering. As such, Amazon competes with us for potential customers, and while Amazon cannot provide our proprietary software, the pricing of Amazon’s offerings may limit our ability to adjust,” the company wrote in the filing, which also lists Endeca, FAST, Autonomy and several others as key competitors.
This is our first look at Elastic’s financials. The company brought in $159.9 million in revenue in the 12 months ended July 30, 2018, up roughly 100 percent from $88.1 million the year prior. Losses are growing at about the same rate. Elastic reported a net loss of $18.5 million in the second quarter of 2018. That’s an increase from $9.9 million in the same period in 2017.
Founded in 2012, the company has raised about $100 million in venture capital funding, garnering a $700 million valuation the last time it raised VC, which was all the way back in 2014. Its investors include Benchmark, NEA and Future Fund, which each retain a 17.8 percent, 10.2 percent and 8.2 percent pre-IPO stake, respectively.
A flurry of business software companies have opted to go public this year. Domo, a business analytics company based in Utah, went public in June raising $193 million in the process. On top of that, subscription biller Zuora had a positive debut in April in what was a “clear sign post on the road to SaaS maturation,” according to TechCrunch’s Ron Miller. DocuSign and Smartsheet are also recent examples of both high-profile and successful SaaS IPOs.
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New Knowledge just raised $11 million more to flag and fight social media disinformation meant to bring down companies
Back in January, we told you about a young, Austin, Tex.-based startup that fights online disinformation for corporate customers. Turns out we weren’t alone in finding it interesting. The now four-year-old, 40-person outfit, New Knowledge, just sealed up $11 million in new funding led by the cross-border venture firm GGV Capital, with participation from Lux Capital. GGV had also participated in the company’s $1.9 million seed round.
We talked yesterday with co-founder and CEO Jonathon Morgan and the company’s director of research, Renee DiResta, to learn more about its work, which appears to be going well. (They say revenue has grown 1,000 percent over last year.) Our conversation, edited for length, follows.
TC: A lot of people associate coordinated manipulation by bad actors online with trying to disrupt elections here in the U.S. or with pro-government agendas elsewhere, but you’re working with companies that are also battling online propaganda. Who are some of them?
JM: Election interference is just the tip of the iceberg in terms of social media manipulation. Our customers are a little sensitive about being identified, but they are Fortune 100 companies in the entertainment industry, as well as consumer brands. We also have national security customers, though most of our business comes from the private sector.
TC: Renee, just a few weeks ago, you testified before the Senate Intelligence Committee about how social media platforms have enabled foreign-influence operations against the United States. What was that like?
RD: It was a great opportunity to educate the public on what happens and to speak directly to the senators about the need for government to be more proactive and to establish a deterrent strategy because [these disinformation campaigns] aren’t impacting just our elections but our society and American industry.
TC: How do companies typically get caught up in these similar practices?
JM: It’s pretty typical for consumer-facing brands, because they are so high-profile, to get involved in quasi-political conversations, whether or not they like it. Communities that know how to game the system will come after them over a pro-immigration stance for example. They mobilize and use the same black market social media content providers, the same tools and tactics that are used by Russia and Iran and other bad actors.
TC: In other words, this is about ideology, not financial gain.
JM: Where we see this more for financial gain is when it involves state intelligence agencies trying to undermine companies where they have nationalized an industry that competes with U.S. institutions like oil and gas and agriculture companies. You can see this is the promotion of anti-GMO narratives, for example. Agricultural tech in the U.S. is a big business, and on the fringes, there’s some debate about whether GMOs are safe to eat, even though the scientific community is clear that they’re completely safe.
Meanwhile, there are documented examples of groups aligned with Russian intelligence using purchased social media to circulate conspiracy theories and manipulate the public conversation about GMOs. They find a grain of truth in a scientific article, then misrepresent the findings through quasi-legitimate outlets, Facebook pages and Twitter accounts that are in turn amplified by social media automation.
TC: So you’re selling software-as-a-service that does what exactly?
JM: We have a SaaS product and a team of analysts who come out of the intelligence community and who help customers understand threats to their brand. It’s an AI-driven system that detects subtle social signs of manipulation across accounts. We then help the companies understand who is targeting them, why, and what they can do about it.
TC: Which is what?
JM: First, they can’t be blindsided. Many can’t tell the difference between real and manufactured public outcry, so they don’t even know about it when it’s happening. But there’s a pretty predictable set of tactics that are used to create false public perception. They plant a seed with accounts they control directly that can look quasi-legitimate. Then they amplify it via paid automation, and they target specific individuals who may have an interest in what they have to say. The thinking is that if they can manipulate these microinfluencers, they’ll amplify the message by sharing it with their followers. By then, you can’t put the cat back in the bag. You need to identify [these campaigns] when they’ve lit the match, but haven’t yet started a fire.
At the early stage, we can provide information to social media platforms to determine if what’s going on is acceptable within their policies. Longer term, we’re trying to find consensus between governments and also social media platforms themselves over what is and what isn’t acceptable — what’s aggressive conversation on these platforms and what’s out of bounds.
TC: How can you work with them when they can’t even decide on their own policies?
JM: First, different platforms are used for different reasons. You see peer-to-peer disinformation, where a small group of accounts drives a malicious narrative on Facebook, which can be problematic at the very local level. Twitter is the platform where media gets its pulse on what’s happening, so attacks launched on Twitter are much more likely to be made into mainstream opinion. There are also a lot of disinformation campaigns on Reddit, but those conversations are less likely to be elevated into a topic on CNN, even while they can shape the opinions of large numbers of avid users. Then there are the off-brand platforms like 4chan, where a lot of these campaigns are born. They are all susceptible in different ways.
The platforms have been very receptive. They take these campaigns much more seriously than when they first began looking at election integrity. But platforms are increasingly evolving from more open to more closed spaces, whether it’s WhatsApp groups or private Discord channels or private Facebook channels, and that’s making it harder for the platforms to observe. It’s also making it harder for outsiders who are interested in how these campaigns evolve.
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