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 […]

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 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 PodcastsOvercast, Pocket Casts, Downcast and all the casts.

Website builder Strikingly raises $10M Series A+ to continue growth in China

Almost exactly one year after announcing its Series A, website building platform Strikingly said today that it has raised a $10 million Series A+. The new round was led by Cathay Capital, with participation from CAS Holding, the lead investor in Strikingly’s Series A. This brings Strikingly’s total funding so far to $17.5 million. Co-founder and […]

Almost exactly one year after announcing its Series A, website building platform Strikingly said today that it has raised a $10 million Series A+. The new round was led by Cathay Capital, with participation from CAS Holding, the lead investor in Strikingly’s Series A. This brings Strikingly’s total funding so far to $17.5 million.

Co-founder and CEO David Chen tells TechCrunch that the funding is “technically a Series B level round for us,” but the team wanted to call it a Series A+ because the capital will be used to continue the momentum of products launched around the time of its Series A, including a mobile website editor and a reseller program, as well as its growth in China. (Series A+ rounds are also more common in China, where Strikingly has an office in Shanghai and is one of the most popular website building services).

“The A+ is a natural continuation of what we’ve been doing since our Series A,” Chen says.

Founded in 2012, Strikingly doubled the size of its team over the past year from 150 to 300 employees. The reseller program, launched in early 2017 after the company realized many Strikingly customers use the platform to build sites for other people, now has users in 70 countries. This year, Strikingly’s goal is to continue growing the program in Asia and introduce more features to help resellers with customer acquisition. The reseller program allows them to buy websites in bulk and gives them a dashboard to manage their clients’ sites. While Strikingly’s core product will continue being its website builder, Chen says its reseller program has helped boost its growth in many markets, particularly Southeast Asia.

When Strikingly launched back in 2012, it set itself apart from other website builders by focusing on easy to build, but polished-looking mobile responsive sites. Now mobile responsive sites are de rigueur for any website builder, but one of the things that continues to differentiate Strikingly from its competitors (a partial list includes Wix, Weebly, Squarespace and WordPress) is its ease of use. The company claims that the average time to launch a new website with Strikingly’s editor is just 10 minutes.

Strikingly also has another edge over competitors in China, where it’s already dealt with the hurdles faced by content management software providers. “Content is very strictly regulated and just being able to enter China was a big step forward from any of our counterparts in the U.S.,” says Chen. Over the past two years, he says Strikingly has become the leading website-building SaaS solution in China, thanks to partnerships with Alibaba Cloud, Tencent Cloud and ZBJ, China’s largest market for freelancers. For example, Tencent Cloud users were offered free week-long trails of Strikingly and it is integrated into ZBJ’s platform.

“China is a huge market obviously and we have already done the hard work of being able to enter China,” says Chen. “We see a lot of opportunities here even beyond website building, but that being our core product gives us a very good entry point to any enterprise service marketplace in China.”

Website builder Strikingly raises $10M Series A+ to continue growth in China

Almost exactly one year after announcing its Series A, website building platform Strikingly said today that it has raised a $10 million Series A+. The new round was led by Cathay Capital, with participation from CAS Holding, the lead investor in Strikingly’s Series A. This brings Strikingly’s total funding so far to $17.5 million. Co-founder and […]

Almost exactly one year after announcing its Series A, website building platform Strikingly said today that it has raised a $10 million Series A+. The new round was led by Cathay Capital, with participation from CAS Holding, the lead investor in Strikingly’s Series A. This brings Strikingly’s total funding so far to $17.5 million.

Co-founder and CEO David Chen tells TechCrunch that the funding is “technically a Series B level round for us,” but the team wanted to call it a Series A+ because the capital will be used to continue the momentum of products launched around the time of its Series A, including a mobile website editor and a reseller program, as well as its growth in China. (Series A+ rounds are also more common in China, where Strikingly has an office in Shanghai and is one of the most popular website building services).

“The A+ is a natural continuation of what we’ve been doing since our Series A,” Chen says.

Founded in 2012, Strikingly doubled the size of its team over the past year from 150 to 300 employees. The reseller program, launched in early 2017 after the company realized many Strikingly customers use the platform to build sites for other people, now has users in 70 countries. This year, Strikingly’s goal is to continue growing the program in Asia and introduce more features to help resellers with customer acquisition. The reseller program allows them to buy websites in bulk and gives them a dashboard to manage their clients’ sites. While Strikingly’s core product will continue being its website builder, Chen says its reseller program has helped boost its growth in many markets, particularly Southeast Asia.

When Strikingly launched back in 2012, it set itself apart from other website builders by focusing on easy to build, but polished-looking mobile responsive sites. Now mobile responsive sites are de rigueur for any website builder, but one of the things that continues to differentiate Strikingly from its competitors (a partial list includes Wix, Weebly, Squarespace and WordPress) is its ease of use. The company claims that the average time to launch a new website with Strikingly’s editor is just 10 minutes.

Strikingly also has another edge over competitors in China, where it’s already dealt with the hurdles faced by content management software providers. “Content is very strictly regulated and just being able to enter China was a big step forward from any of our counterparts in the U.S.,” says Chen. Over the past two years, he says Strikingly has become the leading website-building SaaS solution in China, thanks to partnerships with Alibaba Cloud, Tencent Cloud and ZBJ, China’s largest market for freelancers. For example, Tencent Cloud users were offered free week-long trails of Strikingly and it is integrated into ZBJ’s platform.

“China is a huge market obviously and we have already done the hard work of being able to enter China,” says Chen. “We see a lot of opportunities here even beyond website building, but that being our core product gives us a very good entry point to any enterprise service marketplace in China.”

Integrate.ai pulls in $30M to help businesses make better customer-centric decisions

Helping businesses bring more firepower to the fight against AI-fuelled disruptors is the name of the game for Integrate.ai, a Canadian startup that’s announcing a $30M Series A today. The round is led by Portag3 Ventures . Other VCs include Georgian Partners, Real Ventures, plus other (unnamed) individual investors also participating. The funding will be […]

Helping businesses bring more firepower to the fight against AI-fuelled disruptors is the name of the game for Integrate.ai, a Canadian startup that’s announcing a $30M Series A today.

The round is led by Portag3 Ventures . Other VCs include Georgian Partners, Real Ventures, plus other (unnamed) individual investors also participating. The funding will be used for a big push in the U.S. market.

Integrate.ai’s early focus has been on retail banking, retail and telcos, says founder Steve Irvine, along with some startups which have data but aren’t necessarily awash with AI expertise to throw at it. (Not least because tech giants continue to hoover up talent.)

Its SaaS platform targets consumer-centric businesses — offering to plug paying customers into a range of AI technologies and techniques to optimize their decision-making so they can respond more savvily to their customers. Aka turning “high volume consumer funnels” into “flywheels”, if that’s a mental image that works for you.

In short it’s selling AI pattern spotting insights as a service via a “cloud-based AI intelligence platform” — helping businesses move from “largely rules-based decisioning” to “more machine learning-based decisioning boosted by this trusted signals exchange of data”, as he puts it.

Irvine gives the example of a large insurance aggregator the startup is working with to optimize the distribution of gift cards and incentive discounts to potential customers — with the aim of maximizing conversions.

“Obviously they’ve got a finite amount of budget for those — they need to find a way to be able to best deploy those… And the challenge that they have is they don’t have a lot of information on people as they start through this funnel — and so they have what is a classic ‘cold start’ problem in machine learning. And they have a tough time allocating those resources most effectively.”

“One of the things that we’ve been able to help them with is to, essentially, find the likelihood of those people to be able to convert earlier by being able to bring in some interesting new signal for them,” he continues. “Which allows them to not focus a lot of their revenue or a lot of those incentives on people who either have a low likelihood of conversion or are most likely to convert. And they can direct all of those resources at the people in the middle of the distribution — where that type of a nudge, that discount, might be the difference between them converting or not.”

He says feedback from early customers suggests the approach has boosted profitability by around 30% on average for targeted business areas — so the pitch is businesses are easily seeing the SaaS easily paying for itself. (In the cited case of the insurer, he says they saw a 23% boost in performance — against what he couches as already “a pretty optimized funnel”.)

“We find pretty consistent [results] across a lot of the companies that we’re working with,” he adds. “Most of these decisions today are made by a CRM system or some other more deterministic software system that tends to over attribute people that are already going to convert. So if you can do a better job of understanding people’s behaviour earlier you can do a better job at directing those resources in a way that’s going to drive up conversion.”

The former Facebook marketing exec, who between 2014 and 2017 ran a couple of global marketing partner programs at Facebook and Instagram, left the social network at the start of last year to found the business — raising $9.6M in seed funding in two tranches, according to Crunchbase.

The eighteen-month-old Toronto based AI startup now touts itself as one of the fastest growing companies in Canadian history, with a headcount of around 40 at this point, and a plan to grow staff 3x to 4x over the next 12 months. Irvine is also targeting growing revenue 10x, with the new funding in place — gunning to carve out a leadership position in the North American market.

One key aspect of Integrate.ai’s platform approach means its customers aren’t only being helped to extract more and better intel from their own data holdings, via processes such as structuring the data for AI processing (though Irvine says it’s also doing that).

The idea is they also benefit from the wider network, deriving relevant insights across Integrate.ai’s pooled base of customers — in a way that does not trample over privacy in the process. At least, that’s the claim.

(It’s worth noting Integrate.ai’s network is not a huge one yet, with customers numbering in the “tens” at this point — the platform only launched in alpha around 12 months ago and remains in beta now. Named customers include the likes of Telus, Scotiabank, and Corus.)

So the idea is to offer an alternative route to boost business intelligence vs the “traditional” route of data-sharing by simply expanding databases — because, as Irvine points out, literal data pooling is “coming under fire right now — because it is not in the best interests, necessarily, of consumers; there’s some big privacy concerns; there’s a lot of security risk which we’re seeing show up”.

What exactly is Integrate.ai doing with the data then? Irvine says its Trusted Signals Exchange platform uses some “pretty advanced techniques in deep learning and other areas of machine learning to be able to transfer signals or insights that we can gain from different companies such that all the companies on our platform can benefit by delivering more personalized, relevant experiences”.

“But we don’t need to ever, kind of, connect data in a more traditional way,” he also claims. “Or pull personally identifiable information to be able to enable it. So it becomes very privacy-safe and secure for consumers which we think is really important.”

He further couches the approach as “pretty unique”, adding it “wouldn’t even have been possible probably a couple of years ago”.

From Irvine’s description the approach sounds similar to the data linking (via mathematical modelling) route being pursued by another startup, UK-based InfoSum — which has built a platform that extracts insights from linked customer databases while holding the actual data in separate silos. (And InfoSum, which was founded in 2016, also has a founder with a behind-the-scenes’ view on the inners workings of the social web — in the form of Datasift’s Nic Halstead.)

Facebook’s own custom audiences product, which lets advertisers upload and link their customer databases with the social network’s data holdings for marketing purposes is the likely inspiration behind all these scenes.

Irvine says he spotted the opportunity to build this line of business having been privy to a market overview in his role at Facebook, meeting with scores of companies in his marketing partner role and getting to hear high level concerns about competing with tech giants. He says the Facebook job also afforded him an overview on startup innovation — and there he spied a gap for Integrate.ai to plug in.

“My team was in 22 offices around the world, and all the major tech hubs, and so we got a chance to see any of the interesting startups that were getting traction pretty quickly,” he tells TechCrunch. “That allowed us to see the gaps that existed in the market. And the biggest gap that I saw… was these big consumer enterprises needed a way to use the power of AI and needed access to third party data signals or insights to be able to enabled them to transition to this more customer-centric operating model to have any hope of competing with the large digital disruptors like Amazon.

“That was kind of the push to get me out of Facebook, back from California to Toronto, Canada, to start this company.”

Again on the privacy front, Irvine is a bit coy about going into exact details about the approach. But is unequivocal and emphatic about how ad tech players are stepping over the line — having seen into that pandora’s box for years — so his rational to want to do things differently at least looks clear.

“A lot of the techniques that we’re using are in the field of deep learning and transfer learning,” he says. “If you think about the ultimate consumer of this data-sharing, that is insight sharing, it is at the end these AI systems or models. Meaning that it doesn’t need to be legible to people as an output — all we’re really trying to do is increase the map; make a better probabilistic decision in these circumstances where we might have little data or not the right data that we need to be able to make the right decision. So we’re applying some of the newer techniques in those areas to be able to essentially kind of abstract away from some of the more sensitive areas, create representations of people and patterns that we see between businesses and individuals, and then use that as a way to deliver a more personalized predictions — without ever having to know the individual’s personally identifiable information.”

“We do do some work with differential privacy,” he adds when pressed further on the specific techniques being used. “There’s some other areas that are just a little bit more sensitive in terms of the work that we’re doing — but a lot of work around representative learning and transfer learning.”

Integrate.ai has published a whitepaper — for a framework to “operationalize ethics in machine learning systems” — and Irvine says it’s been called in to meet and “share perspectives” with regulators based on that.

“I think we’re very GDPR-friendly based on the way that we have thought through and constructed the platform,” he also says when asked whether the approach would be compliant with the European Union’s tough new privacy framework (which also places some restrictions on entirely automated decisions when they could have a significant impact on individuals).

“I think you’ll see GDPR and other regulations like that push more towards these type of privacy preserving platforms,” he adds. “And hopefully away from a lot of the really creepy, weird stuff that is happening out there with consumer data that I think we all hope gets eradicated.”

For the record, Irvine denies any suggestion that he was thinking of his old employer when he referred to “creepy, weird stuff” done with people’s data — saying: “No, no, no!”

“What I did observe when I was there in ad tech in general, I think if you look at that landscape, I think there are many, many… worse examples of what is happening out there with data than I think the ones that we’re seeing covered in the press. And I think as the light shines on more of that ecosystem of players, I think we will start to see that the ways they’ve thought about data, about collection, permissioning, usage, I think will change drastically,” he adds.

“And the technology is there to be able to do it in a much more effective way without having to compromise results in too big a way. And I really hope that that sea change has already started — and I hope that it continues at a much more rapid pace than we’ve seen.”

But while privacy concerns might be reduced by the use of an alternative to traditional data-pooling, depending on the exact techniques being used, additional ethical considerations are clearly being dialled sharply into view if companies are seeking to supercharge their profits by automating decision making in sensitive and impactful areas such as discounts (meaning some users stand to gain more than others).

The point is an AI system that’s expert at spotting the lowest hanging fruit (in conversion terms) could start selectively distributing discounts to a narrow sub-section of users only — meaning other people might never even be offered discounts.

In short, it risks the platform creating unfair and/or biased outcomes.

Integrate.ai has recognized the ethical pitfalls, and appears to be trying to get ahead of them — hence its aforementioned ‘Responsible AI in Consumer Enterprise’ whitepaper.

Irvine also says that raising awareness around issues of bias and “ethical AI” — and promoting “more responsible use and implementation” of its platform is another priority over the next twelve months.

“The biggest concern is the unethical treatment of people in a lot of common, day-to-day decisions that companies are going to be making,” he says of problems attached to AI. “And they’re going to do it without understanding, and probably without bad intent, but the reality is the results will be the same — which is perpetuating a lot of biases and stereotypes of the past. Which would be really unfortunate.

“So hopefully we can continue to carve out a name, on that front, and shift the industry more to practices that we think are consistent with the world that we want to live in vs the one we might get stuck in.”

The whitepaper was produced by a dedicated internal team, which he says focuses on AI ethics and fairness issues, and is headed up by VP of product & strategy, Kathryn Hume.

“We’re doing a lot of research now with the Vector Institute for AI… on fairness in our AI models, because what we’ve seen so far is that — if left unattended, if all we did was run these models and not adjust for some of the ethical considerations — we would just perpetuate biases that we’ve seen in the historical data,” he adds.

“We would pick up patterns that are more commonly associated with maybe reinforcing particular stereotypes… so we’re putting a really dedicated effort — probably abnormally large, given our size and stage — towards leading in this space, and making sure that that’s not the outcome that gets delivered through effective use of a platform like ours. But actually, hopefully, the total opposite: You have a better understanding of where those biases might creep in and they could be adjusted for in the models.”

Combating unfairness in this type of AI tool would mean a company having to optimize conversion performance a bit less than it otherwise could.

Though Irvine suggests that’s likely just in the short term. Over the longer term he argues you’re laying the foundations for greater growth — because you’re building a more inclusive business, saying: “We have this conversational a lot. “I think it’s good for business, it’s just the time horizon that you might think about.”

“We’ve got this window of time right now, that I think is a really precious window, where people are moving over from more deterministic software systems to these more probabilistic, AI-first platforms… They just operate much more effectively, and they learn much more effectively, so there will be a boost in performance no matter what. If we can get them moved over right off the bat onto a platform like ours that has more of an ethical safeguard, then they won’t notice a drop off in performance — because it’ll actually be better performance. Even if it’s not optimized fully for short term profitability,” he adds.

“And we think, over the long term it’s just better business if you’re socially conscious, ethical company. We think, over time, especially this new generation of consumers, they start to look out for those things more… So we really hope that we’re on the right side of this.”

He also suggests that the wider visibility afforded by having AI doing the probabilistic pattern spotting (vs just using a set of rules) could even help companies identify unfairnesses they don’t even realize might be holding their businesses back.

“We talk a lot about this concept of mutual lifetime value — which is how do we start to pull in the signals that show that people are getting value in being treated well, and can we use those signals as part of the optimization. And maybe you don’t have all the signal you need on that front, and that’s where being able to access a broader pool can actually start to highlight those biases more.”

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 […]

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).

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 […]

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).

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, 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 datasets, 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 the Elastic’s financials. The company brought in $159.9 million in revenue in the 12 months ended July 30, 2018, up roughly 100% 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 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%, 10.2% and 8.2% 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.

 

Avrios has quietly raised $14M for an AI-fueled fleet management platform

Swiss startup Avrios reckons business mobility is going to get a whole lot more interesting as companies adopt more tailored mobility solutions, rather than sticking with the traditional one car per person model. And at the same time as businesses are seeking to accelerate their progressive cred by moving away from combustion cars to greener alternatives, new […]

Swiss startup Avrios reckons business mobility is going to get a whole lot more interesting as companies adopt more tailored mobility solutions, rather than sticking with the traditional one car per person model.

And at the same time as businesses are seeking to accelerate their progressive cred by moving away from combustion cars to greener alternatives, new urban mobility choices are starting to spring up to offer consumers a multi-modal spectrum of personal transport choice. So the days of businesses offering staff just a few choices of car model are numbered, is the thesis.

But with increased choice to balance, the job of the fleet manager looks set to get more challenging — both when it comes to negotiating with (more and smaller) suppliers; understanding costs and utility; and intelligently matching transportation solutions with business needs and staff desires, argues Avrios. Hence it believes AI will be a key aid to manage increasingly complex fleets.

Its platform, which focuses on passenger car and van fleets and is being used by ~700 customers (predominantly in Europe) to manage ~70,000 vehicles at this stage, is already using machine learning technology to help fleet managers stay on top of data related to car leasing costs.

But Avrios sees this as its foundational play, and is positioning its platform to support a much bigger shift it envisages coming down the pipe — as technologies such as electric cars gain in popularity and get increasingly slotted into business’ fleets.

The rich spectrum of possibility for personal urban mobility can already be glimpsed on the consumer side as ride-hailing giants like Uber turn their attention to car alternatives such as e-bikes and e-scooters.

Businesses, surely, won’t want to be left behind. Which means fleet management platforms will need to be up to challenge of handling all these newer and finer-grained transport options, argues Avrios co-founder and CEO Andreas Brenner.

After running a study on its own customer base last year, the 2015 founded startup estimates that at least 30% of the €60BN annual budget that European businesses currently spend on combustion cars will shift to other options over the next five years.

Its findings also suggest the vast majority of businesses (80%) are currently managing the looming shift in spreadsheets and Access databases — hence Avrios spying an opportunity to step in and support the disruptive market evolution. (And claiming spreadsheets as its main competitor.)

The initial play for its fleet management SaaS platform was also a supporting role (it launched as a dashboard in 2015, but was calling itself a platform by fall 2017), with the team building a system to ingest and process invoices and leasing documents for fleet managers, which Brenner says it has now almost entirely automated.

“You wouldn’t believe but, for example, almost none of the large leasing companies have APIs to import invoices or leasing data — so we essentially had to build a system where we would be able to process these contracts and invoices,” he tells TechCrunch.

“In the early days it all started out manually. But now we can process 99% of the documents fully automatically and this is not just the normal structured form recognition — it’s a true kind of AI system that we’re using. So that’s where most of the magic is happening.”

“The unique thing that we’re able to do is that we’re the only platform that’s able to help our customers import all of the unstructured data from multiple languages. And that’s a lot of information that’s necessary for fleet management, and that saves a lot of time,” he adds.

What he sees coming down the road is more exciting than tech that can automatically ingest French PDF invoices though — howsoever handy that might be — as businesses shift their policies to be able to accommodate a more richly fragmented mobility mix.

Another bit of research it carried out was to look at its customer data to consider how vehicles are currently being used — by looking at mileage and vehicle type — to “deduct the use-case of the vehicle”, as Brenner puts it.

“Our assumption is that any vehicle that isn’t driving a lot or isn’t carrying goods doesn’t make sense from an economic perspective — and is kind of the prime candidate for replacement by other options. At the very least by an electric car,” he suggests. “If I have a car that I’m only driving in the city for 10-20km a day it absolutely doesn’t make sense from an economic perspective to have that be a combustion car.”

That’s how they got to that 30% predictive shift away from combustion cars over the next five years.

They found customers were already implementing car policies that added electric vehicles to their mix (“the more progressive companies are even enforcing a certain share of electric vehicles in their 2019 car policies”, he says).

They also found a “big demand” for corporate car sharing — so the platform offers a booking module to cater to that.

Even more excitingly, they found that some customers were already piloting even greater flexibility — such as offering e-bikes to their staff.

“They’re really thinking hard about how to use all of the new possibilities to further drive employee motivation and retention,” Brenner suggests, arguing that offering staff multi-modal mobility options could be seen as an attractive corporate benefit. “And even expand the addressable groups of their current mobility policy.”

“It can be pretty motivating if, as an intern, you get access to an electric bicycle,” he continues, adding: “These are the kinds of things that we see our customers wrapping their heads around.”

That said, this level of flexibility is only at pilot stage in Europe at present now though.

But he “definitely” sees the European fleet market including electric vehicles in its car policies next year. And, beyond that, there’s potentially all sorts of mobility twists coming down the pipe in the next several years.

“The more creative or advanced options we see more pilots happening in 2019 — and then we think, based on the results of those, we’ll see more disruption in 2020,” he ventures, fleshing out the challenges that this will create for fleet managers.

“If you would put yourself in the shoes of a fleet manager, what you used to do is you used to have… typically two, three large preferred leasing providers. With those you would negotiate terms so that your employees could then choose from typically… 15 models plus some equipment options. That’s what it used to be and that was already considered complex, given all the different maintenance options, financing options etc available. And that’s the first problem we help our customers solve — to understand how is their car policy working?

“But as soon as you add more specialized, smaller suppliers you’re really faced with less volume negotiation. You’re faced with additional overhead. You’re faced with additional number of suppliers, and that’s what we see happening — if you look at the rental car companies they’re offering ever more specific offerings for individual use cases, if you look at shared mobility they’re offering ever more specific offers for specific use cases. And as a fleet manager if you want to somehow provide all that for your employees, for you it just means an explosion of the number of contracts you have to maintain, an explosion of the number of options you have to put into your mobility policy, and that’s an explosion in the complexity of decision making and also in kind of delivery to your employees.

“So that’s what it means for fleet managers — and that’s what we’re helping them with: The cost control, and also the delivery to the employees so they can book a pool car directly through our platform, they can order a leased car, a rental car directly through our platform. So that it all automatically aligns with the policy.”

The company claims its platform helps customers reduce their fleet administration overhead by 30% now and their fleet cost by up to 10%, as well as touting additional benefits around data privacy, and compliance with environmental and owner’s liability laws.

If the quantity and variety of mobility options proliferates, and gets as niche and nuanced as futuregazers suggest, then having a platform to manager cost, compliance and policy complexity starts to look essential — certainly for businesses with large staff and fleet bases to manage.

The majority of Avrios’ current business is in Europe, with customers which include insurance companies, retailers, fashion companies, machine manufacturers and professional service providers.

Brenner says they also have a handful of US and Middle Eastern and African customers (further noting that lots of its customers also have a global fleet footprint).

On the competitive front, he bills what it offers as “a true fleet management platform” — arguing it’s the first such player to do so, suggesting longer-in-the-tooth rivals have only offered fleet administration software and/or fleet management services (while the online portals of incumbents such as AFleetLogistics, Leaseplan and Arval are, as he tells it, “customer retention tools that suggest but don’t really provide transparency”).

“We have a platform approach, providing elements of what software providers would (structured data, reporting, etc) but also elements of what fleet management providers like FleetLogistics would (procurement automation, benchmarking cost against other fleets, optimizing the bidding process for the procurement of new fleets and fleet leases),” he adds. “We are neutral and help customers understand where they are truly losing money.”

The funding being disclosed to TechCrunch now covers a seed round raised in December 2015; a Series A in June 2017; and ~$4M of extension/acceleration funding which it closed in July 2018 — all previously unannounced. The funding total to date adds up to ~$14M — and investors in the business include Lakestar, Notion, Siraj Khaliq (Atomico) and Andrew Flett (Fleetmatics).

Brenner says the extension of the Series A will be used for product development — to “accelerate the transition from a fleet management dashboard towards adding more transportation options”.

It will also be used for scaling the business faster than initially planned. “We’re now considered growth stage so for a growth state startup it’s the typical stuff — product and sales and marketing,” he adds.

“Now we feel like we understand our story, we understand the long term direction we want to take the company, we understand who are customers are, what our position in the market is etc, so it felt like it was the right time to talk to the market a bit more publicly,” he says, explaining why they’ve keep their powder dry on funding announcements up to now.

“It was just a matter of focus on customers and product development rather than anything else.”

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 […]

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?

RD: 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.

Spotinst, excess cloud capacity management service, snares $35M Series B

Spotinst, the startup that helps companies purchase and manage excess cloud infrastructure capacity, announced a hefty $35 million Series B today led by Highland Capital. Existing investors Leaders Fund, Intel Capital and Vertex Ventures also participated. Today’s round brings the total investment to over $52 million. Cloud infrastructure vendors like Amazon Web Services, Microsoft Azure […]

Spotinst, the startup that helps companies purchase and manage excess cloud infrastructure capacity, announced a hefty $35 million Series B today led by Highland Capital.

Existing investors Leaders Fund, Intel Capital and Vertex Ventures also participated. Today’s round brings the total investment to over $52 million.

Cloud infrastructure vendors like Amazon Web Services, Microsoft Azure and Google Cloud Platform run massive data centers to have enough capacity at any given moment to respond to customer demand. That means there are always going to be some machines sitting idle. To make use of this excess capacity, the vendors offer deep discounts of up to 80 percent, but there’s a catch.

If the vendor needs that virtual machine at any given moment, the discount customers are going to get kicked off. That leaves developers wary of putting anything critical on the discounted servers, no matter how much they are saving.

That’s where Spotinst comes in. “With machine learning and artificial intelligence, Spotinst can predict trends of availability. We know how long an instance will live and we can smoothly move our customers from one instance to another, allowing them to run complex or mission critical applications,” Spotinst co-founder and CEO Amiram Shachar told TechCrunch.

He sees the two trends of developers moving toward serverless and containerization really helping to drive his business growth. The company announced support for Lambda, AWS’s serverless product, last fall and they are also seeing a big rise in the use of containers. “What we’ve seen in the past six months is that our containers offering is growing exponentially month over month. And as customers are deploying containers we’re able to run them on excess capacity, and save them huge amounts of money,” he explained.

Spotinst management console. Screenshot: Spotinst.

Shachar is clear that they are not offering a brokerage service here. Instead, his customers sign up for Spotinst as a cloud service, and his company makes money by taking a percentage of the money customers save by using this spot capacity.

The company began by working with AWS spot instances, but has since expanded its market to include Google and Microsoft extra capacity as well. In the future, depending on their requirements, customers could potentially move across clouds seamlessly if they wish, moving to wherever the best available price is at any given moment, using Spotinst to manage the transitions. While that’s not something they offer now, it is on the roadmap, he says.

It’s worth noting that just yesterday, VMware bought CloudHealth Technologies, a company that helps customers manage a multi-cloud environment from a single console. Shachar acknowledges that a company like his could be also be an attractive target for a large company, but he and his co-founders are only looking toward building the business and continuing to improve the product.

The company currently has 100 employees, but with the additional investment, Shachar expects to double that in the next year between their U.S. office in San Francisco and their engineering office in Tel Aviv.