(upbeat music) >> Hello, everyone. Welcome to the theCUBE's presentation of the AWS Startup Showcase. The theme, this showcase is MarTech, the emerging cloud scale customer experiences. Season two of episode three, the ongoing series covering the startups, the hot startups, talking about analytics, data, all things MarTech. I'm your host, John Furrier, here joined by Christian Wiklund, founder and CEO of unitQ here, talk about harnessing the power of user feedback to empower marketing. Thanks for joining us today. >> Thank you so much, John. Happy to be here. >> In these new shifts in the market, when you got cloud scale, open source software is completely changing the software business. We know that. There's no longer a software category. It's cloud, integration, data. That's the new normal. That's the new category, right? So as companies are building their products, and want to do a good job, it used to be, you send out surveys, you try to get the product market fit. And if you were smart, you got it right the third, fourth, 10th time. If you were lucky, like some companies, you get it right the first time. But the holy grail is to get it right the first time. And now, this new data acquisition opportunities that you guys in the middle of that can tap customers or prospects or end users to get data before things are shipped, or built, or to iterate on products. This is the customer feedback loop or data, voice of the customer journey. It's a gold mine. And it's you guys, it's your secret weapon. Take us through what this is about now. I mean, it's not just surveys. What's different? >> So yeah, if we go back to why are we building unitQ? Which is we want to build a quality company. Which is basically, how do we enable other companies to build higher quality experiences by tapping into all of the existing data assets? And the one we are in particularly excited about is user feedback. So me and my co-founder, Nik, and we're doing now the second company together. We spent 14 years. So we're like an old married couple. We accept each other, and we don't fight anymore, which is great. We did a consumer company called Skout, which was sold five years ago. And Skout was kind of early in the whole mobile first. I guess, we were actually mobile first company. And when we launched this one, we immediately had the entire world as our marketplace, right? Like any modern company. We launch a product, we have support for many languages. It's multiple platforms. We have Android, iOS, web, big screens, small screens, and that brings some complexities as it relates to staying on top of the quality of the experience because how do I test everything? >> John: Yeah. >> Pre-production. How do I make sure that our Polish Android users are having a good day? And we found at Skout, personally, like I could discover million dollar bugs by just drinking coffee and reading feedback. And we're like, "Well, there's got to be a better way to actually harness the end user feedback. That they are leaving in so many different places." So, you know what, what unitQ does is that we basically aggregate all different sources of user feedback, which can be app store reviews, Reddit posts, Tweets, comments on your Facebook ads. It can be better Business Bureau Reports. We don't like to get to many of those, of course. But really, anything on the public domain that mentions or refers to your product, we want to ingest that data in this machine, and then all the private sources. So you probably have a support system deployed, a Zendesk, or an Intercom. You might have a chatbot like an Ada, or and so forth. And your end user is going to leave a lot of feedback there as well. So we take all of these channels, plug it into the machine, and then we're able to take this qualitative data. Which and I actually think like, when an end user leaves a piece of feedback, it's an act of love. They took time out of the day, and they're going to tell you, "Hey, this is not working for me," or, "Hey, this is working for me," and they're giving you feedback. But how do we package these very messy, multi-channel, multiple languages, all over the place data? How can we distill it into something that's quantifiable? Because I want to be able to monitor these different signals. So I want to turn user feedback into time series. 'Cause with time series, I can now treat this the same way as Datadog treats machine logs. I want to be able to see anomalies, and I want to know when something breaks. So what we do here is that we break down your data in something called quality monitors, which is basically machine learning models that can aggregate the same type of feedback data in this very fine grained and discrete buckets. And we deploy up to a thousand of these quality monitors per product. And so we can get down to the root cause. Let's say, passive reset link is not working. And it's in that root cause, the granularity that we see that companies take action on the data. And I think historically, there has been like the workflow between marketing and support, and engineering and product has been a bit broken. They've been siloed from a data perspective. They've been siloed from a workflow perspective, where support will get a bunch of tickets around some issue in production. And they're trained to copy and paste some examples, and throw it over the wall, file a Jira ticket, and then they don't know what happens. So what we see with the platform we built is that these teams are able to rally around the single source of troop or like, yes, passive recent link seems to have broken. This is not a user error. It's not a fix later, or I can't reproduce. We're looking at the data, and yes, something broke. We need to fix it. >> I mean, the data silos a huge issue. Different channels, omnichannel. Now, there's more and more channels that people are talking in. So that's huge. I want to get to that. But also, you said that it's a labor of love to leave a comment or a feedback. But also, I remember from my early days, breaking into the business at IBM and Hewlett-Packard, where I worked. People who complain are the most loyal customers, if you service them. So it's complaints. >> Christian: Yeah. >> It's leaving feedback. And then, there's also reading between the lines with app errors or potentially what's going on under the covers that people may not be complaining about, but they're leaving maybe gesture data or some sort of digital trail. >> Yeah. >> So this is the confluence of the multitude of data sources. And then you got the siloed locations. >> Siloed locations. >> It's complicated problem. >> It's very complicated. And when you think about, so I started, I came to Bay Area in 2005. My dream was to be a quant analyst on Wall Street, and I ended up in QA at VMware. So I started at VMware in Palo Alto, and didn't have a driver's license. I had to bike around, which was super exciting. And we were shipping box software, right? This was literally a box with a DVD that's been burned, and if that DVD had bugs in it, guess what it'll be very costly to then have to ship out, and everything. So I love the VMware example because the test cycles were long and brutal. It was like a six month deal to get through all these different cases, and they couldn't be any bugs. But then as the industry moved into the cloud, CI/CD, ship at will. And if you look at the modern company, you'll have at least 20 plus integrations into your product. Analytics, add that's the case, authentication, that's the case, and so forth. And these integrations, they morph, and they break. And you have connectivity issues. Is your product working as well on Caltrain, when you're driving up and down, versus wifi? You have language specific bugs that happen. Android is also quite a fragmented market. The binary may not perform as well on that device, or is that device. So how do we make sure that we test everything before we ship? The answer is, we can't. There's no company today that can test everything before the ship. In particular, in consumer. And the epiphany we had at our last company, Skout, was that, "Hey, wait a minute. The end user, they're testing every configuration." They're sitting on the latest device, the oldest device. They're sitting on Japanese language, on Swedish language. >> John: Yeah. >> They are in different code paths because our product executed differently, depending on if you were a paid user, or a freemium user, or if you were certain demographical data. There's so many ways that you would have to test. And PagerDuty actually had a study they came out with recently, where they said 51% of all end user impacting issues are discovered first by the end user, when they serve with a bunch of customers. And again, like the cool part is, they will tell you what's not working. So now, how do we tap into that? >> Yeah. >> So what I'd like to say is, "Hey, your end user is like your ultimate test group, and unitQ is the layer that converts them into your extended test team." Now, the signals they're producing, it's making it through to the different teams in the organization. >> I think that's the script that you guys are flipping. If I could just interject. Because to me, when I hear you talking, I hear, "Okay, you're letting the customers be an input into the product development process." And there's many different pipelines of that development. And that could be whether you're iterating, or geography, releases, all kinds of different pipelines to get to the market. But in the old days, it was like just customer satisfaction. Complain in a call center. >> Christian: Yeah. >> Or I'm complaining, how do I get support? Nothing made itself into the product improvement, except for slow moving, waterfall-based processes. And then, maybe six months later, a small tweak could be improved. >> Yes. >> Here, you're taking direct input from collective intelligence. Okay. >> Is that have input and on timing is very important here, right? So how do you know if the product is working as it should in all these different flavors and configurations right now? How do you know if it's working well? And how do you know if you're improving or not improving over time? And I think the industry, what can we look at, as far as when it relates to quality? So I can look at star ratings, right? So what's the star rating in the app store? Well, star ratings, that's an average over time. So that's something that you may have a lot of issues in production today, and you're going to get dinged on star ratings over the next few months. And then, it brings down the score. NPS is another one, where we're not going to run NPS surveys every day. We're going to run it once a quarter, maybe once a month, if we're really, really aggressive. That's also a snapshot in time. And we need to have the finger on the pulse of product quality today. I need to know if this release is good or not good. I need to know if anything broke. And I think that real time aspect, what we see as stuff sort of bubbles up the stack, and not into production, we see up to a 50% reduction in time to fix these end user impacting issues. And I think, we also need to appreciate when someone takes time out of the day to write an app review, or email support, or write that Reddit post, it's pretty serious. It's not going to be like, "Oh, I don't like the shade of blue on this button." It's going to be something like, "I got double billed," or "Hey, someone took over my account," or, "I can't reset my password anymore. The CAPTCHA, I'm solving it, but I can't get through to the next phase." And we see a lot of these trajectory impacting bugs and quality issues in these work, these flows in the product that you're not testing every day. So if you work at Snapchat, your employees probably going to use Snapchat every day. Are they going to sign up every day? No. Are they going to do passive reset every day? No. And these things are very hard to instrument, lower in the stack. >> Yeah, I think this is, and again, back to these big problems. It's smoke before fire, and you're essentially seeing it early with your process. Can you give an example of how this new focus or new mindset of user feedback data can help customers increase their experience? Can you give some examples, 'cause folks watching and be like, "Okay, I love this value. Sell me on this idea, I'm sold. Okay, I want to tap into my prospects, and my customers, my end users to help me improve my product." 'Cause again, we can measure everything now with data. >> Yeah. We can measure everything. we can even measure quality these days. So when we started this company, I went out to talk to a bunch of friends, who are entrepreneurs, and VCs, and board members, and I asked them this very simple question. So in your board meetings, or on all hands, how do you talk about quality of the product? Do you have a metric? And everyone said, no. Okay. So are you data driven company? Yes, we're very data driven. >> John: Yeah. Go data driven. >> But you're not really sure if quality, how do you compare against competition? Are you doing as good as them, worse, better? Are you improving over time, and how do you measure it? And they're like, "Well, it's kind of like a blind spot of the company." And then you ask, "Well, do you think quality of experience is important?" And they say, "Yeah." "Well, why?" "Well, top of fund and growth. Higher quality products going to spread faster organically, we're going to make better store ratings. We're going to have the storefronts going to look better." And of course, more importantly, they said the different conversion cycles in the product box itself. That if you have bugs and friction, or an interface that's hard to use, then the inputs, the signups, it's not going to convert as well. So you're going to get dinged on retention, engagement, conversion to paid, and so forth. And that's what we've seen with the companies we work with. It is that poor quality acts as a filter function for the entire business, if you're a product led company. So if you think about product led company, where the product is really the centerpiece. And if it performs really, really well, then it allows you to hire more engineers, you can spend more on marketing. Everything is fed by this product at them in the middle, and then quality can make that thing perform worse or better. And we developed a metric actually called the unitQ Score. So if you go to our website, unitq.com, we have indexed the 5,000 largest apps in the world. And we're able to then, on a daily basis, update the score. Because the score is not something you do once a month or once a quarter. It's something that changes continuously. So now, you can get a score between zero and 100. If you get the score 100, that means that our AI doesn't find any quality issues reported in that data set. And if your score is 90, that means that 10% will be a quality issue. So now you can do a lot of fun stuff. You can start benchmarking against competition. So you can see, "Well, I'm Spotify. How do I rank against Deezer, or SoundCloud, or others in my space?" And what we've seen is that as the score goes up, we see this real big impact on KPI, such as conversion, organic growth, retention, ultimately, revenue, right? And so that was very satisfying for us, when we launched it. quality actually still really, really matters. >> Yeah. >> And I think we all agree at test, but how do we make a science out of it? And that's so what we've done. And when we were very lucky early on to get some incredible brands that we work with. So Pinterest is a big customer of ours. We have Spotify. We just signed new bank, Chime. So like we even signed BetterHelp recently, and the world's largest Bible app. So when you look at the types of businesses that we work with, it's truly a universal, very broad field, where if you have a digital exhaust or feedback, I can guarantee you, there are insights in there that are being neglected. >> John: So Chris, I got to. >> So these manual workflows. Yeah, please go ahead. >> I got to ask you, because this is a really great example of this new shift, right? The new shift of leveraging data, flipping the script. Everything's flipping the script here, right? >> Yeah. >> So you're talking about, what the value proposition is? "Hey, board example's a good one. How do you measure quality? There's no KPI for that." So it's almost category creating in its own way. In that, this net new things, it's okay to be new, it's just new. So the question is, if I'm a customer, I buy it. I can see my product teams engaging with this. I can see how it can changes my marketing, and customer experience teams. How do I operationalize this? Okay. So what do I do? So do I reorganize my marketing team? So take me through the impact to the customer that you're seeing. What are they resonating towards? Obviously, getting that data is key, and that's holy gray, we all know that. But what do I got to do to change my environment? What's my operationalization piece of it? >> Yeah, and that's one of the coolest parts I think, and that is, let's start with your user base. We're not going to ask your users to ask your users to do something differently. They're already producing this data every day. They are tweeting about it. They're putting in app produce. They're emailing support. They're engaging with your support chatbot. They're already doing it. And every day that you're not leveraging that data, the data that was produced today is less valuable tomorrow. And in 30 days, I would argue, it's probably useless. >> John: Unless it's same guy commenting. >> Yeah. (Christian and John laughing) The first, we need to make everyone understand. Well, yeah, the data is there, and we don't need to do anything differently with the end user. And then, what we do is we ask the customer to tell us, "Where should we listen in the public domain? So do you want the Reddit post, the Trustpilot? What channels should we listen to?" And then, our machine basically starts ingesting that data. So we have integration with all these different sites. And then, to get access to private data, it'll be, if you're on Zendesk, you have to issue a Zendesk token, right? So you don't need any engineering hours, except your IT person will have to grant us access to the data source. And then, when we go live. We basically build up this taxonomy with the customers. So we don't we don't want to try and impose our view of the world, of how do you describe the product with these buckets, these quality monitors? So we work with the company to then build out this taxonomy. So it's almost like a bespoke solution that we can bootstrap with previous work we've done, where you don't have these very, very fine buckets of where stuff could go wrong. And then what we do is there are different ways to hook this into the workflow. So one is just to use our products. It's a SaaS product as anything else. So you log in, and you can then get this overview of how is quality trending in different markets, on different platforms, different languages, and what is impacting them? What is driving this unitQ Score that's not good enough? And all of these different signals, we can then hook into Jira for instance. We have a Jira integration. We have a PagerDuty integration. We can wake up engineers if certain things break. We also tag tickets in your support system, which is actually quite cool. Where, let's say, you have 200 people, who wrote into support, saying, "I got double billed on Android." It turns out, there are some bugs that double billed them. Well, now we can tag all of these users in Zendesk, and then the support team can then reach out to that segment of users and say, "Hey, we heard that you had this bug with double billing. We're so sorry. We're working on it." And then when we push fix, we can then email the same group again, and maybe give them a little gift card or something, for the thank you. So you can have, even big companies can have that small company experience. So, so it's groups that use us, like at Pinterest, we have 800 accounts. So it's really through marketing has vested interest because they want to know what is impacting the end user. Because brand and product, the lines are basically gone, right? >> John: Yeah. >> So if the product is not working, then my spend into this machine is going to be less efficient. The reputation of our company is going to be worse. And the challenge for marketers before unitQ was, how do I engage with engineering and product? I'm dealing with anecdotal data, and my own experience of like, "Hey, I've never seen these type of complaints before. I think something is going on." >> John: Yeah. >> And then engineering will be like, "Ah, you know, well, I have 5,000 bugs in Jira. Why does this one matter? When did it start? Is this a growing issue?" >> John: You have to replicate the problem, right? >> Replicate it then. >> And then it goes on and on and on. >> And a lot of times, reproducing bugs, it's really hard because it works on my device. Because you don't sit on that device that it happened on. >> Yup. >> So now, when marketing can come with indisputable data, and say, "Hey, something broke here." And we see the same with support. Product engineering, of course, for them, we talk about, "Hey, listen, you you've invested a lot in observability of your stack, haven't you?" "Yeah, yeah, yeah." "So you have a Datadog in the bottom?" "Absolutely." "And you have an APP D on the client?" "Absolutely." "Well, what about the last mile? How the product manifests itself? Shouldn't you monitor that as well using machines?" They're like, "Yeah, that'd be really cool." (John laughs) And we see this. There's no way to instrument everything, lowering the stack to capture these bugs that leak out. So it resonates really well there. And even for the engineers who's going to fix it. >> Yeah. >> I call it like empathy data. >> Yup. >> Where I get assigned a bug to fix. Well, now, I can read all the feedback. I can actually see, and I can see the feedback coming in. >> Yeah. >> Oh, there's users out there, suffering from this bug. And then when I fix it and I deploy the fix, and I see the trend go down to zero, and then I can celebrate it. So that whole feedback loop is (indistinct). >> And that's real time. It's usually missed too. This is the power of user feedback. You guys got a great product, unitQ. Great to have you on. Founder and CEO, Christian Wiklund. Thanks for coming on and sharing, and showcase. >> Thank you, John. For the last 30 seconds, the minute we have left, put a plug in for the company. What are you guys looking for? Give a quick pitch for the company, real quick, for the folks out there. Looking for more people, funding status, number of employees. Give a quick plug. >> Yes. So we raised our A Round from Google, and then we raised our B from Excel that we closed late last year. So we're not raising money. We are hiring across go-to-markets, engineering. And we love to work with people, who are passionate about quality and data. We're always, of course, looking for customers, who are interested in upping their game. And hey, listen, competing with features is really hard because you can copy features very quickly. Competing with content. Content is commodity. You're going to get the same movies more or less on all these different providers. And competing on price, we're not willing to do. You're going to pay 10 bucks a month for music. So how do you compete today? And if your competitor has a better fine tuned piano than your competitor will have better efficiencies, and they're going to retain customers and users better. And you don't want to lose on quality because it is actually a deterministic and fixable problem. So yeah, come talk to us if you want to up the game there. >> Great stuff. The iteration lean startup model, some say took craft out of building the product. But this is now bringing the craftsmanship into the product cycle, when you can get that data from customers and users. >> Yeah. >> Who are going to be happy that you fixed it, that you're listening. >> Yeah. >> And that the product got better. So it's a flywheel of loyalty, quality, brand, all off you can figure it out. It's the holy grail. >> I think it is. It's a gold mine. And every day you're not leveraging this assets, your use of feedback that's there, is a missed opportunity. >> Christian, thanks so much for coming on. Congratulations to you and your startup. You guys back together. The band is back together, up into the right, doing well. >> Yeah. We we'll check in with you later. Thanks for coming on this showcase. Appreciate it. >> Thank you, John. Appreciate it very much. >> Okay. AWS Startup Showcase. This is season two, episode three, the ongoing series. This one's about MarTech, cloud experiences are scaling. I'm John Furrier, your host. Thanks for watching. (upbeat music)

>> From Santa Clara, in the heart of Silicon Valley it's theCUBE, covering the Churchills, 2019. Brought to you by SiliconANGLE Media. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're in Santa Clara, California at the Churchills. It's the ninth annual awards banquet put on by the Churchills Club, and this year is all about leadership. We're excited to be joined by our next guest who knows a little bit about leadership. He's Carl Guardino, the president and CEO of the Silicon Valley Leadership Group. Carl, great to see you. >> Great to see you, too, Jeff. >> So what is the Silicon Valley Leadership Group all about? >> The Silicon Valley Leadership Group is an association of about 360, primarily innovation economy employers that want to make a positive, proactive difference here in the region, as well as in our state and across the United States. >> What are some of the hot topics that are on top of the plate right now? Because there is a lot of craziness kind of going on here in Silicon Valley. >> There is. But what we try to do is impact those issues that are as important to families in their living rooms as they are to CEOs in their board rooms. And here in the bay area, we call those THEE issues. An acronym, T-H-E-E. The T, traffic; H, housing affordability; E, education; and the fourth E, the economy. And we try to bring together diverse points of view for those areas that unite us, where we can actually solve some of those challenges. >> Right, and those are big, big challenges. And you work both with public as well as private groups to try to bring them together to make movement on those things. >> We're a bridge. And the first thing about a bridge is that you try to bring folks together to cross the bridge and work together. The second most important thing about a bridge is that you build them, you don't burn them down. And that's the role that we try to play with 360 highly engaged CEOs and c-suite officers. >> And it's only appropriate, because tonight you'll be sitting down in a conversation with the mayor of San Jose, Sam Liccardo, to kind of get into some of these issues. San Jose seems to be on a roll right now, a positive roll. A lot of positive news coming out of San Jose. >> Yes, and that always starts with leadership rather than luck. San Jose mayor Sam Liccardo, 10th largest city in the United States, has been able to strike that balance of being pro-innovation economy, while also caring deeply about his citizens, the residents of San Jose, 1,053,000, and how we make sure that we have a strong and vibrant economy, but also a great quality of life. >> Right. So how do you even begin to - we'll start with traffic. The T in the THEE. To address that issue, it's so multifaceted, right, it's so tied to jobs, it's tied to housing, it's tied to the growth of the economy, you know, unfortunately freeways are slow to build, public transportation's expensive, but we continue to see growth there. How do you kind of eat that elephant, one bite at a time, with something like traffic? >> Well the role of the leadership group is, again, by bringing people together to solve complex problems in a democracy with winning solutions. So we'd rather win than whine. And when it comes to traffic, one of our core competencies is actually to lead and run ballot initiatives to fund transportation improvements throughout the region and the state. In fact, in the last 30 years alone, I've had the pleasure of going on loan from the leadership group to run ballot campaigns for transportation improvements that have totaled 30 billion dollars in revenue through those measures, approved by voters to reach into our own wallets, rather than our neighbors, to build improvements that, this Christmas, in time to go into your stocking, we'll be bringing BART to San Jose, and working on the electrification of Caltrain, linking transit and better road improvements, making it better for all of us trying to travel throughout this region. >> Right. Good, we need it. >> We do. >> And on the housing, you know, because the housing is also very closely tied to traffic, and we see that the old days of single-family homes on big pieces of dirt, those are going away. They just can't support it in higher density areas like San Fransisco, San Jose, to bring those jobs next to that. So we're seeing a huge transformation in the housing space as well. >> And we need a huge transformation, both in transportation and in housing. And it's really the flip side to the same coin. T, for tails, or transportation; H, for head, or housing. And you have to make sure that you keep those linked. In fact, one of our initiatives right now is to work with all six, fixed rail transit operators throughout the nine bay area counties. What are the current and future uses of those half miles around every fixed rail transit stop that you have? How do we maximize those uses? Here's a great example. What Google wants to do in downtown San Jose, at the Diridon SAP station, is only because of the Silicon Valley Leadership Group's work to bring BART to that station, electrify Caltrain, light rail is there, Amtrak, ACE, et cetera, and they want to have 20 to 25 thousand future Google employees there within the next 10 to 12 years. Why? Because it is a sustainable location that doesn't rely on you and I slogging through traffic in our single-occupant cars. >> Right. I can't wait to see what you guys do to El Camino. That's the next one that's going to - as somebody once said in one of these traffic things, it's just a bunch of old retail stores with empty parking lots, just placed by Microsoft. Or excuse me, by Amazon. So I think we'll see a big transformation with housing and jobs, you know, along that quarter, which happens to parallel the Caltrain, and is near and dear to my heart. So a lot of good opportunities I think to make improvements. >> Jeff, there is. And as hard as transportation and traffic solutions are to put into place, housing is even tougher. And while Bay Area residents think housing is the bigger crisis, the solutions are tougher to come about, because the community isn't as united on those solutions. So the role that a group of employers like ours play, is how do we bring people together around solutions that make sure that we build homes, that are good for everyone in our society. >> Well Carl, I like your positive attitude, a lot of winning and no whining, so I wish you nothing but success. And we'll be watching. >> Thank you, Jeff. >> You're welcome. He's Carl, I'm Jeff, you're watching theCUBE. We're at the Churchills in Santa Clara, California. Thanks for watching. We'll see you next time.

(music) >> Everyone, welcome to a special CUBE Conversation. We're here in Palo Alto, theCUBE Studios, I'm John Furrier, the host of theCUBE video, we're here with a very special guest and the new CEO of a hot startup, Christine Heckart, CEO Scalyr. Welcome to theCUBE, great to see you. >> Thank you. >> Thanks for coming on. So, you're the new CEO of Scalyr, the CEO transitioned. >> Super great founder, great engineering team. >> Yes, yes. >> Hot startup, lot of finance and a lot of customers. Tell us about Scalyr. >> So, Scalyr was founded by a guy named Steve Newman. He is a serial entrepreneur. Scalyr is his 7th company. His 6th company was called Writely and it got bought by Google and is what we all know and love as Google Docs today. So, when he was inside Google, building out Google Docs he had the same problem that a lot of engineers do right now especially if they're on a modern stack. It's really hard to troubleshoot. It's hard to figure out what's running well and if there's a problem where it's at and fix it quickly. And so he left in 2011 and he founded Scalyr. >> And so, the company has how many employees? Just give us the quick numbers of employees, funding, venture involved, customers... Give us the quick numbers. >> The company has a little over 50 employees. It just took a Series A round about a year, a little under a year-and-a-half ago. Led by Shasta Ventures. There are 300 paying customers. We grew the core customer base last year by 170% revenue. So, it's growing very quickly. We more than doubled the employees in the last year. So, like you say, it's on fire and we're trying to scale up ourselves as we help our customers scale. >> So growth is obviously rocket ship growth is an attractive, enticing opportunity for you. You've been there, done that. So, what else attracted you to the opportunity? What made you make the move to take the leadership helm as the chief of Scalyr? >> The thing that attracted me most to Scalyr is that the world runs on code right now. And for companies for whom the code is the company downtime is money, it's critical. But, in these modern stacks, it's really hard to figure out where the problem is. Everything's been so abstracted. And if you're cloud-based, if you're moving to serverless, if you're on Kubernetes or some kind of container platform trying to do orchestration... Any of that makes it faster and easier to build a service but a lot harder to figure out if and where there's a problem within the service. And Scalyr's designed by engineers for engineers on modern stacks to help them figure out where that problem is and get it solved very quickly. >> So obviously the new wave is the cloud. Cloud natives search for big opportunities converging. What's the market opportunity? What are you guys going after in terms of, if you look at the marketplace, what's the segment you're going after? Lay that out, what segment are you in? Is it just cloud, is it a piece of cloud native, what's the market opportunity? >> We serve customers who have applications built on a new stack a cloud-based stack. And typically the people who use us most and who love us most are the site-reliability engineers, responsible for keeping it up and running. Dev Ops, true developers... One of our largest customers is a company called Zalando. They're an older company that did a digital transition, and so they do online e-commerce now, one of the largest in Europe. And for their engineers, 25% of their engineers use the product daily. 50% use it weekly. So, it's part of the workflow. It helps them do their jobs better. So, it's a utility. And the founder, you said, worked at Google, obviously he saw the scale there. They have a site reliability engineer concept that's obviously run a huge infrastructure. Is that kind-of the market you're going after? Dev Ops, SRE types? >> Yep, so we're an observability tool. There's kind-of two camps of observability. We've started in the logging space. So, what we're really known for is the fast logging tool. And the reason why we're known for being fast is unlike all the other architectures that were optimized for the more traditional stack, we've been written and optimized for the new stack and we're the only architecture that doesn't use keyword index in order to do that search. And that's what makes us fast. But it's also what makes us more affordable. And it contributes to, the architecture contributes to the simplicity of how you can use the tool and how the tool is written. >> So, the core tech is, under the hood would be, what, what's the core tech in that. Because speed obviously means you've got some technology there. What's the core technology that makes that speed work? >> So, we're a true multi-tenancy product, we run on Amazon ourself, it's a multi-tenancy system, it uses massive parallel processing. And basically we can ingest any data, in fact we're designed for machine data, for logs, for things that don't, they're not full documents, it's not like a video or something on the World Wide Web. These are little tiny events that come in and there's lots and lots and lots of them. Scalyr is the name of the company, we scale up and we scale out. And what we do is, when you go to run a query we throw every processor in our system at every query that comes in. And the reason why that becomes important in this multi-tenancy architecture is the more customers we have, the more data that we ingest, the more servers we have to throw at every query for every customer. So as we grow, the service gets better, it gets faster, it gets more affordable for all customers. >> That's the best thing about the cloud, you can bring that compute to bear so you have a little flywheel of acceleration. Talk about the role of data, because this is interesting, one of the core problems we hear a lot in the cloud native world is that so many, now, sets of services being deployed Kubernetes is becoming the de-facto sceme for orchestration around micro-services, containers obviously they're our standard as well. Which means there's more instrumentation, right? So, I could almost see how the founder saw this future because he lived it. >> Exactly. >> He lived the future, and now the real world's going "hey, we have that Google-like problem, we have tons of services playing around but it's not just logging and getting a query back in minutes. These services are talking to applications through each other. This is like mission critical. >> Very mission critical. >> Is this what you guys are doing? >> Right, if you are running in a traditional environment and you're running sort-of traditional applications there are really good logging solutions out there for that. That's what Splunk was founded on, they're amazing at doing that. But, nobody had built an optimized logging system and an observability system for the new stack. And that's what we're designed to do. And you use, you said, in minutes. And minutes is what it takes for most log queries in a traditional environment. 96% of all of our queries happen in less than a second. We're fast. >> So, this is really what the Agile teams need, Dev Ops teams need. >> Yes. When code is money, when it's the company, when every second of downtime, or even a service that's impaired, it might not be hard down but it's not running the way that it should, that impacts the customer experience, it impacts how many customers you can get if you're a real-time business, it impacts revenue. It's important to get that service up and running quickly. >> So, you guys are re-imagining logging, which is more mission critical rather than okay, where the breach is, what's going on in the basic logs, like Splunk used to do. So, talk about the product. Who's the target persona, how is it consumed, you mentioned on the cloud, is it SAS? How does someone get involved, do they just download it, do they get a consult, talk about the product and the target audiences. >> So, it is SAS, it's delivered by SAS. We don't have a non-prime service today or an offering. And, typically it's the site-reliability engineer, the architects, the developers themselves, Dev Ops for sure, Cloud Ops, they're the ones that are using the tool day-to-day. And it's a beautiful dashboard, a lot of it is just point and click. You can go in, if you want to add English-language query, you don't have to learn a special query language to use this, that's why people say it's so fast and easy to learn to use and I think that's why we get the kind of daily usage we have. You don't have to be an expert in the tool, it's very intuitive, you get a dashboard, you can just keep clicking down off of a chart and get all the way to the code. In fact, we can link you from where the problem is straight into the code that underlies that so you can then go and solve the problem. >> So, it's really easy to get into. >> Very. >> So I don't need do any kind of elaborate configurations? >> No. You don't need to do elaborate configurations and, as importantly, you don't need to learn a new specialized query language. Which, again, in the more traditional systems you find that there's only a few people that really know how to use the product because you have to learn the query language. It's kind-of like CLI or something in networking. And so there's a few specialists and they're very good, but if you're an engineer and there's a problem and you want to use the tool, you don't have time to become an expert. You've got to just use it. And so, even though it's designed to search machine language, you can use English, it's pretty easy to figure out how to write that query, and it comes back so quickly, if you didn't get it quite right you can just refine and do the search again and narrow down. >> I can see why the V.C.'s like this, the venture capitalists, because it markets good, big wave, cloud native lot of growth there. Certainly hyper-scalers, enterprisers are coming next, so I can imagine that's more head room. Product is consumable, SAS, in the cloud, technology that's fast, compelling, >> You're good, you can be on the pitch team. >> Final check box is customers. >> Yes. >> So, how many customers do you have? >> We have 300 paying customers. That doubled in the last year, and we have some big names and a lot of small companies. So, some of the fun ones are Giphy, my kids love that, my husband, right? Using them every day. NBC Universal, kind-of on the other side of that. Companies for whom the application is the business. And it can be a traditional company that's trying to launch new digital transformation initiatives, or it can be companies that were born in the cloud. >> And that's only going to get better, again, the markup. There's more companies going to the cloud. Talk about multi-cloud, because you know we had conversations in the past before you came on Scalyr around multi-cloud. That's only going to increase the sets of microservices and the role of data. Not just code, because code is data. Data is code. It's going to be a whole data ops movement coming soon, we see that tsunami coming. How does the multi-cloud fit into all of this in your mind? Is it too early, is that coming later? Or, is it available now? Could your customers have the multi-cloud now? >> For our customers, if they are in a multi-cloud environment today, we're an ideal tool for them 'cause we can run on any of their clouds. Most customers are not yet in multi-cloud, but they're trying to get there. Just like most customers are not yet fully containerized, but you want to pick a tool today that will grow with you and get you to tomorrow. And that's where Scalyr comes in, because we are designed and optimized for that environment. And, there's kind-of no scale too big for us. The company was named very deliberately. We can scale up, we can scale out, and we can continue to be simple and fast as your business scales. >> Christine, you've had a track record, you've had a great career, you've seen a lot of waves of innovation. You've been working for big companies, a dozen start-ups, now you're back at a start-up. So, I got to ask you a personal question, how does it feel? What's it like back into the trenches? And, you've got a hot start-up here. One month on the job, what's going on there? >> I love it. I really love it. You know, there's 50 people in the company every one of them is high-energy they're so committed to the cause. You know, when the world runs on code and you help that code run better, you're making an impact on the world every single day. These people know it, they feel it. They're very committed. And, unlike some of the much bigger companies I've been at, you can innovate so quickly. So, I just finished my first 30 days onboarding, I have talked to our big customers, a couple dozen of our really big customers. And, they all say a couple of things over and over again, there's just some consistent themes. Fast always comes up, it's usually the first word. Simple comes up. Affordable, which is nice. People pay a lot of money for these tools and they don't always feel good about all that money. We can come in and be much more affordable and they appreciate that. But, the thing that kept coming up over and over again was the customer service and the customer support. And nobody, I come from worlds where nobody ever raves about customer service and customer support. So, it was odd and I dug a little bit, and there were two pieces to that. One, because we're 50 people, when somebody has a problem, we're all-in. It gets solved quickly. A lot of times we can sort-of flag that problem for the customer because we're keeping track. But the other thing that was brought up is when they need something that maybe we don't deliver today they ask for it. And a lot of times we can give it to them pretty quickly. There's not some big, huge long roadmap process. We're a small company, we can't always do it quickly, but a lot of times we can turn stuff around and it's great. >> Well, you're hitting the ground running, got your running shoes on, sounds like a great opportunity. You've got a lot of work to do! What are some of the priorities? I'm sure hiring is big. Take a minute to give the plug on for any hirings you have. >> So, we're just moving to brand new facilities in downtown San Mateo a couple blocks from Caltrain. And that is because we doubled the company size last year, and we need to double it again this year. So, we are hiring, if you know of any great people, please send them to us. We announced some new things at Amazon Reinvent, late last year, one of which is new distributed tracing. We're on the very leading edge of this trend, and it's an important one. It's probably a conversation maybe with Steve himself. Yeah, he's very knowledgeable, and it's a fascinating area because the APM systems, again, kind-of the traditional if you can say that for APM, have all been built for the front-end, for the websites. But, once you move into these container environments you need that same kind of capability for the back end. And so you need something called distributed tracing. It turns out that if you're born in the logs like we are doing that distributed tracing which links them together and gives you a picture systemically of what's happening and how you link the events for a fuller picture. We're kind-of uniquely good at that. So, we've got that coming out later this quarter. >> That'll attract some engineers 'cause that's a hard problem. >> It's a hard, a lot of the problems we solve are hard, interesting problems, and they're problems for the new stack, and they're problems at scale. And smart engineers like to work on that. >> You know, state's a big one, stateless applications, state is a huge problem I'm sure you guys are on, this is where the tracing plays in. >> Yes, exactly. >> Final question for you before we end is competition. Certainly people who are in the new world, going cloud native, they get it, they get the complexity, they get the opportunity as well. So, there's a lot of investment there. But, the folks that are looking at Scalyr like "ooh, what's the competitive lens"? How do you answer that? What's your response to differentiate, being different from the competition? So, there's lots and lots of observability tools, and even logging tools in the market. And from that standpoint you could say there's tons of competition. They're all built on keyword indexing, so they're all optimized for looking back, for yesterday's world. We're the only ones that are built on this very new architecture, designed for the future stack, designed for the new stack. And, we're the only ones that don't use keyword indexing. And, what we have is this amazing, multi-tenancy, columnar-based approach that gives you these advantages of fast, simple, and affordable. >> So you're staking the ground in the marketplace of speed, sub-second response, 2 queries, 4 runtime applications that are mission critical to businesses. Is that right? >> Said very well, thank you. >> Well, that's what we do here at theCUBE, we figure it out, we get the data. >> Christine, thanks for coming out. Congratulations on the new role. We'll be following you guys. Love the name, Scalyr. Scaling is table stakes now in the cloud. If you don't compete at scale, or operate at scale, or develop at scale, you're probably going to be in trouble. So, theCUBE's covering it as always. Thanks for watching, I'm John Furrier.

>> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're in Mountain View, California, at a really cool start-up, Phantom Auto. They're coming at this autonomous vehicle thing from a very different direction. They're not a car company, it's not BMW and Audi and Nissan and all the other people you hear about. It's a pure software play, but it really has a huge impact on the autonomous vehicle industry. We're excited with the guy who's putting all these development, business development deals together. He's Jordan Sanders, director of business development and operations. Jordan, great to see you. >> Yeah, thanks for having me. >> So, again, when I first heard about you guys I thought, "Okay, do I order "this to drive my grandfather to the store," because he shouldn't be driving even though he has his driver's license, but no, that's not it at all. You guys have a very specific target market and it's really more a biz dev than a direct-to-consumer market. >> Yeah, exactly, so we are a B2B business and our target customers are those who are closest to getting their autonomous vehicles on the road. And so, that's frankly where we're seeing the most traction for now, at this point, from customers. As you get closer to true deployment of level four robo-taxis you realize a need for remote assistance, and we think we have the best solution on the market. >> Jeff: Right. >> To actually remotely drive the car and have a human in the loop to promote safety and service. >> So, as you look at your kind of tam, your ecosystem that you're going to market with, obviously we all know Waymo. We see the cars driving around all the time, the Nest is right up the street, but how's that landscape evolving? You know, we obviously hear about Uber, we hear about Lyft, you hear little bits and pieces about BMW and different car companies. As you sit back from where you're sitting, how do you kind of segment the market, how do you figure out where you're going to go next? >> Yeah, it's an interesting question. I mean, right now, you know, there's obviously a lot of excitement around this market and where it will be in five years. Right now the number of actual autonomous vehicles deployed is relatively low, and so that is frankly what our business is tied to. Again, it's enabling every vehicle on the road to actually operate safely, and so in terms of total addressable market, how we see it evolving, right now it's a relatively small number of cars and a relatively small number of players, but we see huge opportunity and huge growth in the sector over the next five years and 10 years. >> Right, and obviously a big integration challenge for you guys because each platform that you partner with is, you know, we hear all the time, some of them are using some shared infrastructure, some of them are trying to use their own, some are RADAR, some are LIDAR, some are camera, some are combination, so from a business development point of view you guys have to integrate with all those different platforms. >> That's correct, and so that's from the very beginning, we're building our end-to-end service to be very flexible and the software piece especially can integrate with any vehicle, with any vehicle manufacturer, because frankly we want to be open to the market and we don't want to just cover, you know, one customer's vehicles. We are sort of a third party who can provide a safety solution for a number of AV operators. >> Right, now the other interesting thing that people probably don't think about is, you know, we hear all about the technology in the cars and the machines, right, and IOT and it's all about machines, but in bringing a human operator into the equation it's not just to operate the vehicle, it's actually a person and all that that means. I wonder if you can kind of explain how that impacts people's autonomous car vehicle when there's actually a person involved. >> Yeah, definitely, so I think, you know, I think about this from a personal standpoint, so part of me is very excited for autonomous vehicles and I've ridden in several autonomous vehicles, feel very comfortable in them very quickly, but I also live in Silicon Valley and not everyone does just get to zip around in autonomous vehicles and is working in this industry, and so we do view there's going to be a, you know, a big consumer adoption kind of hurdle to overcome, and a piece of that is having the passengers in the car comfortable and feeling that, you know, someone has their back, right? >> Jeff: Right. >> So that's a key part of what we believe that we deliver is a human touch to self-driving cars, which we think is very important just at a psychological level, knowing that you have somebody who is monitoring your ride and is ready to intervene and protect you, you know, in the event that something goes wrong with the ride. And the other thing is by having a human in the loop it also enables all sorts of interesting ways of providing better service, and that's going to be a very, a key piece of whenever everyone inside the car is a passenger, there are no longer drivers, we're passengers. There are going to be lots of opportunities for enhancing passenger experience, and we think part of that can be, you know, providing a human service, an actual human on the other end making you feel comfortable and also connecting you with almost like a concierge. >> Right, and like OnStar has been around forever, right, that's probably the first kind of two way- >> You said that, not me, yeah. >> Two way communication, right, into the vehicle, which at first was I think mainly a safety feature. You crash and it sends out a 911 and then I think they kind of evolved it into a little bit of a concierge service. >> Exactly, so again, there's certainly that piece that we think is going to be really important for consumer adoption. I mean, I think AAA did a survey recently that showed 75% of consumers are afraid of trusting a machine, an autonomous vehicle. Now, we're very confident that the AV tech, once you get inside an autonomous vehicle that you very quickly realize, "Wow, this is a great driver," and we're very bullish on, you know, autonomous vehicle technology and believe that it's very reliable. But again, in those edge case scenarios, having a human who's going to intervene on your behalf and be able to actually operate the vehicle will be really important. >> Right, so somebody's watching this and going, "Ha-ha-ha," you know, "I'm a hacker, I'm going to hack into the stream," and it's not going to be Ben, the nice, smooth driver taking over the car but some person that maybe we don't want taking over the car. So, in terms of security and network infrastructure, how much are you leveraging your partners' infrastructure, how much are you leveraging your own, where does kind of security fit in this whole puzzle? >> Yeah, it's a great question and certainly one that, you know, we're hearing from a lot of customers. So, we are working with a variety of cybersecurity firms for making sure that our solution is extremely secure across multiple vectors, so whether it's just on the software piece or really our end-to-end solution, from the hardware that we can offer in the car, to the software, to the actual control center, the operation center where the driver's driving you, making sure that we have end-to-end security to avoid any situation like that. >> Right, so Jordan, for the people that aren't in Silicon Valley, what should they know about autonomous vehicles, how close are we, how much is it just, you know, stuff in the newspaper and you know, kind of nirvana still or just, you know, specialize Waymo vehicles that we see all the time in this neighborhood. How close is this to Main Street, how close is this to being that vehicle that picks me up when I get off the Caltrain to San Francisco and I need to go to a meeting over the Embarcadero? >> Yeah, so I think what people should know about this technology is that it is incredible technology that will be life-saving and that needs to get on the road, but that needs to happen in a safe manner and at a time where you can have full confidence in the operation and all settings, right. The technology is incredible, and so what Phantom Auto is here to do is to get these life-saving vehicles on the road quicker, and so what I would say to the average person who's a little uncertain of this technology is that it is incredible and you're going to enjoy the experience and it will be life-saving, and again, I think Phantom Auto is working to actually bring that experience to consumers by getting these robo-taxi services deployed. >> Jeff: Right. >> Pull out the safety driver and have a remote safety driver, a Phantom Auto remote operator ready to take over control of the vehicle in the event that you need assistance. >> And in terms of where you guys are as a company, right, you're a relatively small company, got this cool Lincoln here, where are you in terms of your company? Do you have POCs in place, do you have customers in place, kind of where is it in terms of the deployment of the technology within your ecosystem? >> Yeah, well we realize that we're bringing a very critical solution to these operators, so again, if you're an autonomous vehicle developer and operator and really thinking seriously about deployment you realize that you need a solution like ours, and so on the business standpoint we have several deals already closed, some pilots planned over the next few months, so you'll be seeing a lot more, I think, of us very soon out in the market. >> All right, now you're going to see more of us on the street. So, Jordan, let's stop talking and let's go take a ride in the car. >> Let's get in the car. >> All right, he's Jordan, I'm Jeff. We're getting in the car, thanks for watching. (techy music playing)