>>Yeah, yeah. Okay. Welcome back, everyone to the cubes. Coverage of reinvent 20 twenty-one Jon, your host of the Cube. We're here. Live in person for a real event. It's a hybrid event is a live stream of action to cube sets here, wall to wall coverage dot com. And, of course, you don't need to check the coverage out. And Amazon has got their own live event site. Go check out all the action. Stewart, See two of Micro Focus, the company That was part of the big announcement involving the mainframe modernization that Adam announced on stage and his first keynote CEO. And under the covers Micro Focus powering a lot of that functionality. Stuart, thanks for coming on. The break it down with >>Thanks. >>So what does the announcement? I mean that that Adam gave the i b. M. I mean the mainframe announcement that I've known for the main frame, but he had the mainframe modernization program. What's that all about? >>I think I'd like to think of this is the next evolution of the main frame for those customers that have been running on the main thing for 40 years. They had their business on it. Where do they go next? What does the future? What does the future hold? And this is all part of the announcement yesterday is this is the journey that many, many customers are going to decide to go on. >>So it's all about the relationship between A. W S and micro Focus. Obviously, Um, yeah. I was talking about migration for the Oracle, and a lot of our customers have these main friends that are in the classic data centers. And he told me personally when I interviewed him that the main part of that data center mindset that people are chipping away at now they want to move them out and keep some functionality, but for the most part, migrated out eventually. Yeah, This is where you guys are involved. Take us through why that's important. >>I think it's the next level of agility that it is actually delivered for many customers. They need to move a hell of a lot faster than they currently are. Let's face it, the world is changing at pace. The applications support these customers need to also a change of pace. What a W s does give this market and momentum which is, Where do we go next? Where do we take customers where workloads have been running the business? Where? How are they going to run the business in five years time? How they're gonna run their business in 10. >>Well, congratulations on microphone. Big part of the announcement. Specifically explained to me, Micro focuses role in the announcement with a W S. What's the relationship? >>I think they're too old to call it out. Actually, we've been working with A W S for many, many years. This isn't something that radically new. We've been engaging with them for literally 10 years, at least. But the key elements Microphone provides technology That's an enabler to facilitate delivering the service as well as the competency partner to help customers actually accelerate their journey to take advantage of it. >>So we're bundling micro focus into that capability. Is it software that you guys have? What's going on the covers? >>I think it's software. It's capability. It's expertise. It's everything that a customer might need to help and be successful. Our job is to a W S H A W s job to make sure the customer is absolutely satisfied. >>Give me an example of a customer mainframe. I'm a bank. I've been using the main frame and just squeaked Time to get my back up before I turned the light in the morning. It's just working. It's coming. It's pumping it all cylinders, my cobalt program or just quit. What do I do? How do you help me? >>Well, I think there are two reasons why you can give us a call Is number one? Yeah, You need to move your business of pace. So what's going to run your business going forward? So you need to understand your applications. Number two, the cost profile of your existing infrastructure is going to be incredibly expensive. So what you wanna do is essentially make the change accelerate the change delivered at a much lower cost. >>So it looks like the application. So the software Okay, what's the app? And then create a replica of digital twin? I'm just trying to visualized. Now I see what you mean. What happens because, I mean, you know what? That is A big deal with that animal for a long time. What happens next is a container eyes. That application, >>the customer determines how far they want to go if they would like the application to run in the cloud exactly as is so it supports their customers exactly as they expect today. We can do that. On the other hand, if they need to enhance the experience for their customers if they need to take it into a completely different environment. If they do want to contain, arise if they want to take it into new levels of service. If they do want to leverage artificial intelligence and machine learning, then again they can determine the journey. Micro focus is that essentially support them. Do that first step, which is get the applications ready to be delivered into cloud as fast as possible. >>Congratulations. Relationship. I guess I've got to ask you a question. Which on my mind is that Okay? It's the death of the mainframe. Long live the mainframe. You know the expression, uh, mainframe dying. I'm gonna hang around for a while. The dinosaurs are out there. >>I think it is. We like to position there is an evolution. We don't think the main friends gonna die. There will be customers who want to stay there, and we respect their choices. But on the other hand, this is a way to truly accelerate the future of mainstream applications. >>You know, student, I talked to a lot of success and C E O. S. And they tell me the same thing when they moved into the cloud. White hardcore is pretty much the main or critical laps to get the edges first moved into the cloud. And then they come and they start chipping away at the main, the main core and then slowly move it out because they don't want to get in there and disrupt so disruptions. A huge concerns. How does this new, um, modernization Tranz, uh, migration program for the mainframe ensure that disruption doesn't happen? What? I'm sure that's on their mind >>as well. I think what you're describing is what's the cut over when you're running on the main street today? You wanna run on the main from tomorrow, You know, if that's the case, or do you want to run the main from today and you want to run the cloud tomorrow? Essentially, the cut over is the same. The process is fairly separate from the mainframe itself. You obviously bringing applications off. We're getting them ready to go tested, you know, regulated. So it's been approved securities all in place, and then essentially, it's literally a switch cut. We literally have customers that turn off the main frame and, you know, they're already running in the cloud, and then we don't even have some that photographs of them shipping mainframe out the door. >>So I've got to ask, Is there a party at that point? You know, some people do >>that. It's certainly true. Remember that people are also going along for this journey, and they're not, You know, it's a big moment for them. >>You know, I hate the sound of today's my birthday. So I have to say this, Um, I remember when I was breaking into the business in my twenties. I never I never program punch cards, But remember pointing at the mainstream guys are seeing those old relics. I guess that's what I would be today. But the young guns coming into the industry, they want containers. They want micro services. They want cloud and see what's going on here. I mean, some really cool stuff happening. >>Uh, they want to take advantage of all the stuff that is there and every single announcement has been made today and yesterday on the days ahead. All of those great capabilities if you can get them into the core of your business. And so the key is to actually take us running your business today, enhance it and improve it and take it forward. I >>think I think the key points great insight on your part about this cut over because people know what that means. It's a project plan. Cut it over, get set up. And I think that's the hard part. How hard is that? On the cloud side, In terms of staging, can you share some timetables with me? Just kind of Give me a feel for order of magnitude Mainframe. Assuming, pumping it snap I'm using. I really can't shut it down, but I want to put it on. How much time to prepare to get into the cloud? Um, roughly just order of magnitude. Most >>customers, they tend to face these things they're not trying to. If you're a really big bank, you are not gonna do that overnight. That isn't gonna come as a surprise. But what we're gonna do is we're gonna take it in chunks and typically 12 to 15 months, which is the biggest step of the journey, which is going from mainframe to cloud. The next generation is going to be modernizing those applications, and it's going to be much short timeframes. Then you're getting into months, weeks, days >>after that. Is there any category that you see that are more susceptible to migration? You mentioned banks. I know some banks that they will never going to touch the mainstream because it's just so critical that the migration longer is there. Other areas of your insurance is a big market mainframe. Is the verticals that kind of like a more converting than others? >>Well, yes. But actually, I take it back. One of the reasons are these applications absolutely critical to these businesses. If they are, that's the reason why they're still running where they are, because they're really truly valuable. They are the business, so you're you're taking the business into new framework. So in that context actually tends to be financial services insurance, as you say, but also government, For example, the federal government, state and local as well as you move into retail. And it's surprising how often as you go into some of the other verticals where some of these mainframe applications are still existing. >>I hate to ask a question, because I don't know. So I want to ask, Um, and you can see it's a dumb question. If you think it is. Just tell me, Are there still cobalt programmers out there? >>There are to be clear. Actually, it's not a problem. You can train a new guy and literally weeks. If the issue is, yeah, actually use the mainstream itself, the mainstream experience about how it works as getting rarer. And so the key element is, how can how can you take the new young guns, give them, give them the application and see what they can do? This is a mechanism to do that. >>Great, Great announcement. Congratulations. I was really impressed at the moment. I'm actually surprised to see Adam kind of focus on that. But again, in the spirit of the traditional, uh, reinvent jazzy before Adam and he did the same thing with Oracle and all the other kind of big the legacy old guard they call them Technologies maintains one. You guys are part of that. So congratulations. Final word. Your take on the event so far. What's been the feedback on the announcement? Share some color commentary on what the feedback for you guys >>were. Actually, since the announcement, we've had some great customer conversations. I mean, there are a lot of businesses that really do want to make this change. We're kind of there to help them. And that's really the next step, which is what needs to happen to make that a reality. >>Amazon may not like me saying it, but I think there's some cases where you keep them in there and you don't touch. It works there. You keep it unless you wanna move. But if you want to move it, people, sometimes we want to move faster. And just there >>even a W s respects customer choice. The purpose is to meet the demand for the customer. And if the customer to sounds great, if they want to move off, we're there to help >>with the mainframe. Long live the main friends. The Cube coverage here in Las Vegas. I'm John. I love the mainframe Thirty-seven terminal. When I worked at the back in the eighties getting myself, um, thanks for coming in. And I appreciate it. Okay. Coverage here in Las Vegas. The Cube. You're watching the leader in global tech event coverage? I'm your host. Thanks for watching. Yeah, Yeah, yeah, yeah, yeah. Uh, mhm, yeah.

>>Hi, welcome to this cube conversation here in Palo Alto, California. I'm John fur, host of the cube here at our headquarters on the west coast in Palo Alto, California. Got a great news guest here. Matt McGill, Wayne managing director of Madrona venture group is here with me on the big news and drone raising their record 690 million fund and partnering with their innovative founders. Matt, thanks for coming on and, and talking about the news and congratulations on the dry powder. >>Well, Hey, thanks so much, John. Appreciate you having me on the show. >>Well, great news here. Oley validation. We're in a new market. Everyone's talking about the new normal, we're talking about a recession inflation, but yet we've been reporting that this is kind of the first generation that cloud hyperscale economic scale and technical benefits have kind of hit any kind of economic downturn. If you go back to to 2008, our last downturn, the cloud really hasn't hit that tipping point. Now the innovation, as we've been reporting with our startup showcases and looking at the results from the hyperscalers, this funding news is kind of validation that the tech society intersection is working. You guys just get to the news 430 million in the Madrona fund nine and 200. And I think 60 million acceleration fund three, which means you're gonna go stay with your roots with seed early stage and then have some rocket fuel for kind of the accelerated expansion growth side of it. Not like late stage growth, but like scaling growth. This is kind of the news. Is that right? >>That's right. You know, we, we've had a long time strategy over 25 years here in Seattle of being early, early stage. You know, it's like our friends at Amazon like to say is, well, we're there at day one and we wanna help build companies for the long run for over 25 years. We've been doing that in Seattle. And I think one of the things we've realized, I mean, this is, these funds are the largest funds ever raised by a Seattle based venture capital firm and that's notable in and of itself. But we think that's the reason is because Seattle has continued to innovate in areas like consumer internet software cloud, of course, where the cloud capital of the world and increasingly the applications of machine learning. And so with all that combination, we believe there's a ton more companies to be built here in the Pacific Northwest and in Seattle in particular. And then through our acceleration fund where we're investing in companies anywhere in the country, in fact, anywhere in the world, those are the kinds of companies that want to have the Seattle point of view. They don't understand how to work with Amazon and AWS. They don't understand how to work with Microsoft and we have some unique relationships in those places and we think we can help them succeed in doing that. >>You know, it's notable that you guys in particular have been very close with Jeff Bayo Andy Jesse, and the success of ABUS as well as Microsoft. So, you know, Seattle has become cloud city. Everyone kind of knows that from a cloud perspective, obviously Microsoft's roots have been there for a long, long time. You go back, I mean, August capital, early days, funding Microsoft. You remember those days not to date myself, but you know, Microsoft kind of went up there and kind of established it a Amazon there as well. Now you got Google here, you got Facebook in the valley. You guys are now also coming down. This funding comes on the heels of you appointing a new managing director here in Palo Alto. This is now the migration of Madrona coming into the valley. Is that right? Is that what we're seeing? >>Well, I think what we're trying to do is bring the things that we know uniquely from Seattle and the companies here down to Silicon valley. We've got a terrific partner in Karama Hend, Andrew he's somebody that we have worked together with over the years, co-investing in companies. So we knew him really well. It was a bit opportunistic for us, but what we're hearing over and over again is a lot of these companies based in the valley, based in other parts of the country, they don't know really how to best work with the Microsoft and Amazons are understand the services that they offer. And, you know, we have that capability. We have those relationships. We wanna bring that to bear and helping build great companies. >>What is your expectation on the Silicon valley presence here? You can kind of give a hint here kind of a gateway to Seattle, but you got a lot of developers here. We just reported this morning that MEA just open source pie, torch to the Linux foundation again, and Mary material kind of trend we are seeing open source now has become there's no debate anymore has become the software industry. There's no more issue around that. This is real. I >>Think that's right. I mean, you know, once, you know, Satya became CEO, Microsoft, and they started embracing open source, you know, that was gonna be the last big tech holdout. We think open source is very interesting in terms of what it can produce and create in terms of next generation, innovative innovation. It's great to see companies like Facebook like Uber and others that have had a long track record of open source capabilities. But what we're also seeing is you need to build businesses around that, that a lot of enterprises don't wanna buy just the open source and stitch it together themselves. They want somebody to do it with them. And whether that's the way that, you know, companies like MongoDB have built that out over time or that's, you know, or elastic or, you know, companies like opt ML and our portfolio, or even the big cloud, you know, hyperscalers, you know, they are increasingly embracing open source and building finished services, managed services on top of it. So that's a big wave that we've been investing in for a number of years now and are highly confident gonna >>Continue. You know, I've been a big fan of Pacific Northwest for a while. You know, love going up there and talking to the folks at Microsoft and Amazon and AWS, but there's been a big trend in venture capital where a lot of the, the later stage folks, including private equity have come in, you seen tiger global even tiger global alumni, that the Cubs they call them, you know, they're coming down and playing in the early state and the results haven't been that good. You guys have had a track record in your success. Again, a hundred percent of your institutional investors have honed up with you on this two fund strategy of close to 700 million. What's this formula says, why aren't they winning what's is it, they don't have the ecosystem? Is it they're spraying and praying without a lot of discipline? What's the dynamic between the folks like Madrona, the Neas of the world who kind of come in and Sequoia who kind of do it right, right. Come in. And they get it done in the right way. The early stage. I just say the private equity folks, >>You know, I think that early stage venture is a local business. It is a geographically proximate business when you're helping incredible founders, try to really dial in that early founder market fit. This is before you even get to product market fit. And, and so the, the team building that goes on the talking to potential customers, the ITER iterating on business strategy, this is a roll up your sleeves kind of thing. It's not a financial transaction. And so what you're trying to do is have a presence and an understanding, a prepared mind of one of the big themes and the kinds of founders that with, you know, our encouragement and our help can go build lasting companies. Now, when you get to a, a, a later stage, you know, you get to that growth stage. It is generally more of a financial, you know, kind of engineering sort of proposition. And there's some folks that are great at that. What we do is we support these companies all the way through. We reserve enough capital to be with them at the seed stage, the series B stage the, you know, the crossover round before you go public, all of those sorts of things. And we love partnering with some of these other people, but there's a lot of heavy lifting at the early, early stages of a business. And it's, it's not, I think a model that everybody's architected to do >>Well, you know, trust becomes a big factor in all this. You kind of, when you talk about like that, I hear you speaking. It makes me think of like trusted advisor meets money, not so much telling people what to do. You guys have had a good track record and, and being added value, not values from track. And sometimes that values from track is getting in the way of the entrepreneur by, you know, running the certain meetings, driving board meetings and driving the agenda that you see to see that trend where people try too hard and that a force function, the entrepreneur we're living in a world now where everyone's talking to each other, you got, you know, there's no more glass door it's everyone's on Twitter, right? So you can see some move, someone trying to control the supply chain of talent by term sheet, overvaluing them. >>You guys are, have a different strategy. You guys have a network I've noticed that Madrona has attracted them high end talent coming outta Microsoft outta AWS season, season, senior talent. I won't say, you know, senior citizens, but you know, people have done things scaled up businesses, as well as attract young talent. Can you share with our audience that dynamic of the, the seasoned veterans, the systems thinkers, the ones who have been there done that built software, built teams to the new young entrepreneurs coming in, what's the dynamic, like, how do you guys look at at those networks? How do you nurture them? Could you share your, your strategy on how you're gonna pull all this together, going forward? >>You know, we, we think a lot about building the innovation ecosystem, like a phrase around here that you hear a lot is the bigger pie theory. How do we build the bigger pie? If we're focusing on building the bigger pie, there'll be plenty of that pie for Madrona Madrona companies. And in that mindset says, okay, how are we gonna invest in the innovation ecosystem? And then actually to use a term, you know, one of our founders who unfortunately passed away this year, Tom Aber, he had just written a book called flywheel. And I think it embodies this mindset that we have of how do you create that flywheel within a community? And of course, interestingly enough, I think Tom both learned and contributed to that. He was on the board of Amazon for almost 20 years in helping build some of the flywheels at Amazon. >>So that's what we carry forward. And we know that there's a lot of value in experiential learning. And so we've been fortunate to have some folks, you know, that have worked at some of those, you know, kind iconic companies, join us and find that they really love this company building journey. We've also got some terrific younger folks that have, you know, some very fresh perspectives and a lot of, a lot of creativity. And they're bringing that together with our team overall. And you know, what we really are trying to do at the end of the day is find incredible founders who wanna build something lasting, insignificant, and provide our kind of our time, our best ideas, our, our perspective. And of course our capital to help them be >>Successful. I love the ecosystem play. I think that's a human capital game too. I like the way you guys are thinking about that. I do wanna get your reaction, cause I know you're close to Amazon and Microsoft, but mainly Jeff Bezos as well. You mentioned your, your partner who passed away was on the board. A lot of great props on and tributes online. I saw that, I know I didn't know him at all. So I really can't comment, but I did notice that Bezos and, and jazz in particular were complimentary. And recently I just saw Bezos comment on Twitter about the, you know, the Lord of the rings movie. They're putting out the series and he says, you gotta have a team. That's kinda like rebels. I'm paraphrasing, cuz these folks never done a movie like this before. So they're, they're getting good props and reviews in this new world order where entrepreneurs gotta do things different. >>What's the one thing that you think entrepreneurs need to do different to make this next startup journey different and successful because the world is different. There's not a lot of press to relate to Andy Jassey even on stage last week in, in, in LA was kind of, he's not really revealing. He's on his talking points, message, the press aren't out there and big numbers anymore. And you got a lot of different go-to market strategies, omnichannel, social different ways to communicate to customers. Yeah. So product market fit is becomes big. So how do you see this new flywheel emerging for those entrepreneurs have to go out there, roll up their sleeves and make it happen. And what kind of resources do you think they need to be successful? What are you guys advocating? >>Well, you know, what's really interesting about that question is I've heard Jeff say many times that when people ask him, what's gotta be different. He, he reminds them to think about what's not gonna change. And he usually starts to then talk about things like price, convenience, and selection. Customer's never gonna want a higher price, less convenience, smaller selection. And so when you build on some of those principles of, what's not gonna change, it's easier for you to understand what could be changing as it relates to the differences. One of the biggest differences, I don't think any of us have fully figured out yet is what does it mean to be productive in a hybrid work mode? We happen to believe that it's still gonna have a kernel of people that are geographically close, that are part of the founding and building in the early stages of a company. >>And, and it's an and equation that they're going to also have people that are distributed around the country, perhaps around the world that are some of the best talent that they attract to their team. The other thing that I think coming back to what remains the same is being hyper focused on a certain customer and a certain problem that you're passionate about solving. And that's really what we look for when we look for this founder market fit. And it can be a lot of different things from the next generation water bottle to a better way to handle deep learning models and get 'em deployed in the cloud. If you've got that passion and you've got some inkling of the skill of how to build a better solution, that's never gonna go away. That's gonna be enduring, but exactly how you do that as a team in a hybrid world, I think that's gonna be different. >>Yeah. One thing that's not changing is that your investor, makeup's not changing a hundred percent of your existing institutional investors have signed back on with you guys and your oversubscribed, lot of demand. What is your flywheel success formula? Why is Tron is so successful? Can you share some feedback from your investors? What are they saying? Why are they re-upping share some inside baseball or anecdotal praise? >>Well, I think it's very kind to you to frame it that way. I mean, you know, it does for investors come back to performance. You know, these are university endowments and foundations that have a responsibility to, to generate great returns. And we understand that and we're very aligned with that. I think to be specific in the last couple years, they appreciated that we were also not holding onto our, our stocks forever, that we actually made some thoughtful decisions to sell some shares of companies like Smartsheet and snowflake and accolade in others, and actually distribute capital back to them when things were looking really, really good. But I think the thing, other thing that's very important here is that we've created a flywheel with our core strategy being Seattle based and then going out from there to try to find the best founders, build great companies with them, roll up our sleeves in a productive way and help them for the long term, which now leads to multiple generations of people, you know, at those companies. And beyond that we wanna be, you know, partner with and back again. And so you create this flywheel by having success with people in doing it in a respectful. And as you said earlier, a trusted way, >>What's the message for the Silicon valley crowd, obviously bay area, Silicon valley, Palo Alto office, and the center of it. Obviously you got them hybrid workforce hybrid venture model developing what's the goals. What's the message for Silicon valley? >>Well, our message for folks in Silicon valley is the same. It's always been, we we're excited to partner with them largely up here again, cause this is still our home base, but there'll be a, you know, select number of opportunities where we'll get a chance to partner together down in Silicon valley. And we think we bring something different with that deep understanding of cloud computing, that deep understanding of applied machine learning. And of course, some of our unique relationships up here that can be additive to what the they've already done. And some of them are just great partners and have built, you know, help build some really incredible companies over >>The years. Matt, I really appreciate you taking the time for this interview, given them big news. I guess the question on everyone's mind, certainly the entrepreneur's mind is how do I get some of that cash you have and put it into work for my opportunity. One what's the investment thesis can take a minute to put the plug in for the firm. What are you looking to invest in? What's the thesis? What kind of entrepreneurs you're looking for? I know fund one is seed fund nine is seed to, to a and B and the second one is beyond B and beyond for growth. What's the pitch. What's the pitch. >>Yeah. Well you can, you can think of us as you know, any stage from pre-seed to series seed. You know, we'll make a new investment in companies in all of those stages. You know, I think that, you know, the, the core pitch, you know, to us is, you know, your passion for the, for the problem that you're trying to, trying to get solved. And we're of course, very excited about that. And you know, at, at, at the end of the day, you know, if you want somebody that has a distinct point of view on the market that is based up here and can roll up their sleeves and work alongside you. We're, we're, we're the ones that are more than happy to do that. Proven track record of doing that for 25 plus years. And there's so much innovation ahead. There's so many opportunities to disrupt to pioneer, and we're excited to be a part of working with great founders to do that. >>Well, great stuff. We'll see you ATS reinvent coming up shortly and your annual get together. You always have your crew down there and, and team engaging with some of the cloud players as well. And looking forward to seeing how the Palo Alto team expands out. And Matt, thanks for coming on the cube. Appreciate your time. >>Thanks very much, John. Appreciate you having me look forward to seeing you at reinvent. >>Okay. Matt, Matt here with Madrona venture group, he's the partner managing partner Madrona group raises 690 million to fund nine and, and, and again, and big funds for accelerated growth fund. Three lot of dry powder. Again, entrepreneurship in technology is scaling. It's not going down. It's continuing to accelerate into this next generation super cloud multi-cloud hybrid cloud world steady state. This is the cubes coverage. I'm John for Silicon angle and host of the cube. Thanks for watching.

>>okay. >>Just about a year ago, governments around the world forced shutdowns of their respective economies. We've never seen anything like it. Central banks took immediate action and effective monetary policy like none we've ever seen before. They dropped interest rates to near zero, injected a huge amount of cash into the system, and they fueled this liquidity boom to support those individuals and businesses that were in greatest need. Banks were overwhelmed with the volume of paperwork, for instance, small business P, P P loans and other things. Home buying boomed as mortgage rates hit all time lows for several weeks in the spring, it was complete chaos, but the tech industry stepped up and accommodated work from home. Cloud infrastructure was spun up instantly as access to data centers was really restricted, and Saas companies became a fundamental staple of not only keeping the lights on but helping customers thrive in the face of a pandemic. Automation became a >>mandate >>as humans, they couldn't possibly keep up with the tidal wave of demand, a document overload that was hitting the system. Now, one of the companies that was there to help financial firms in particular, get through the knothole was Oculus, a company that focuses on intelligent automation to deploy the power of machines to allow humans to focus on what they do best. Hello, everyone. And welcome to this cube conversation. My name is Dave Volonte, and we're profiling the most interesting SAS startups that are reimagining how we work. And with me is Sam Bobbly, the co founder and CEO of Oculus. Sam, welcome to the Cube. First time. >>Hey, Dave. Thanks so much for having me excited to have the conversation. >>Yeah, me too. So, listen, I know you've told the story of a zillion times, but I want a community here. How and why did you start the company >>for sure. So when I was in college, I was having a conversation with my dad. Uh, he was telling me about a meeting he just had with his elder law attorney. And the other law attorney was complaining about having to review hundreds or thousands of pages of financial documents for every long term care Medicaid application. When you apply for Medicaid coverage to enter a nursing home, you're required to submit 60 months of financials along with your application. And traditionally the elder law attorney or a nursing home would review those documents literally page by page, line by line to find high value transactions, transfers and other financial trends. And when I heard about this, it just it didn't make sense to me. I said, You know why? In this day and age isn't there? Why isn't there a technology solution that can ingest the documents and spit out a digital report replacing the cumbersome manual page by page review? So it really just started as a research project, trying to learn more about optical character recognition, which is the technology of transforming images into text. And, you know, as we kind of kicked around different products in the market, we we realized that there was an opportunity to build a unique platform that could ingest documents of any format quality and produce perfectly accurate results. And that was the genesis behind what ultimately became Oculus. >>You were a young man at this time. How old were you at that time? >>I was 22 when we started >>so fearless. And, uh, now my friend Eddie Mitchell started a company about 20 years ago. We hacked together a >>Dell >>system and this camera. It was all about the modern operating room in the future, and he showed it to a doctor and and it was just a prototype, she said. How much? He said 10 grand. She wrote a check right there. You have a similar story? How did you see the company? >>So we we we do have a pretty similar experience. You know, Our our concept was we want to get perfect results the customer every time. So if a customer sends us a clean bank statement from Chase or a blurry cell phone image with someone's thumb in the picture from a community bank in Maine, and it's rotated sideways or upside down like we want to give consistent, perfectly active results every single time. And you know, our our view was to completely solve the business problem. So the very first version of the software that we built, we had a rudimentary machine process to extract 60 or 70% of the data, and then we had a little tool built on the back end, where literally, me, myself and some of our early employees would clean up the data output, make sure it's perfect and then return When we couldn't submit, we'd returned to the customer accurate data that could be used at the time for for a Medicaid decision. And what happened is, while we were in our beta period, customers fell in love with the product. They felt it was magical and really just superior from an accuracy standpoint to anything they had ever tested before. And And one of our beta testers said to us, uh, where do I submit credit card information? So at that time, I turned to my colleagues and I said, I think we're ready to I think we're ready. Start charging for this thing and and roll it out for prime time. >>When I was researching the company, I learned that you leveraged. At least some of the idea came from the capture, and I never knew this, But the capture that we all hate came from Google where they write, they had at one point you could maybe you still can. You can go online. You can read books and have to It's just scanned. You can't even read the stuff half the time. So they were putting the capture in front of us, quite brilliant to try to solve for those those those white spaces that they didn't know. So So how did you learn from that? Was there an A P I that you could plug into Google's data set, or did you do your own? What was that? How did that all work? >>The the concept of humans in the loop is super powerful, right? So when we first started, we recognize that OCR and machine data capture couldn't do the job completely. OCR, generally speaking, can process financial documents with roughly 80 to 85% accuracy plus or minus machines, particularly struggled with semi structured and unstructured documents where the format is unpredictable as well as lower quality images. So pretty early on, we recognized that we needed human intervention in the process in order to achieve perfect accuracy every single time, and also to create training data to constantly teach our machine learning models to get smarter and drive additional automation. So, as I mentioned, the very first version was myself and other employees verifying the data on our own. But as we started thinking about how to scale this up and, you know, take on millions and millions of documents, we needed to, uh, you know, learn how to better parallelized task and really build the system for for efficiency and for scanning. So we we we learned about the Google Books Initiative and their ability to leverage capture technology and a distributed workforce to verify pieces of information that their systems couldn't automatically read from books. And we took a lot of those learnings into building our human in the loop infrastructure. And, you know, a way to think about our our product is it's the marriage of machines and humans that makes us unique. As much of the heavy lifting as we can do with machines we do. But whatever we can't do automatically, we slice into smaller tasks and intelligently route those tasks to humans to perform verification. We then layer in algorithmic checks to make sure our humans did the review correctly. The customer gets perfect results, and that same perfect output is used in a feedback loop to train our machine learning models to get smarter and smarter, which dynamically improves the product on an ongoing basis. And, you know, the folks at Google were we're onto this pretty early with the capture technology, and we were following in their footsteps with our own unique take on it, but specifically applying it to financial documents. >>I mean on the Cube. We know a lot about this because we were looking at transcriptions of video all the time, and it just keeps getting better and better and better in our systems. Get smarter and smarter, smarter. So we're sort of closing that gap between what humans can can do and machines can't. And I would expect that you're seeing the same thing. I mean, you think there's always going to be kind of humans in the loop in terms of the quality or is that gap going to be, you know, six nines in the, you know, near near term. >>I think it's gonna take a while to get rid of all the edge cases. You know, you mentioned the PPB program like we've been on the back end processing P p P loans for some of the leading players, like Cross River Bank, blue Vine, Square Capital and others. And you know, what we've seen during the ppb process is just a a wide variety of different documents and inputs, Uh, and a lot of difficult to read documents that are, you know, very challenging to automate. So I think we will, you know, incrementally continue to automate more and more of the process. But the value of having humans plus machines is much more powerful than just having machines alone or just having humans alone. And as it relates to the end customer, our our goal is to do as much of the mundane work as possible to free our customer up to do the more cerebral analysis. So in a lending context and and for the record, you know, our our biggest market opportunity is in the limbic space. Despite the fact that we started with medicating attorneys, we quickly pivoted and realized that our technology was super valuable to to lenders to help them automate the underwriting process. And our our thesis is, if we can take out all of the necessary evils like document review and allow underwriters to focus on the actual analysis of financial health, it's a win win win and creates a really fantastic, complementary relationship between us and our customers. >>Yes, I want to ask you about the pivot to financial services. You said you started well, you have the inspiration from elder law because Jimmy McGill. Okay. Saul Goodman breaking bad. You got started. An elder law. But then you made the pivot to financial services. Really pretty early on. You had really good, great product market fit, but you kind of went for it. I get early twenties. You know, you didn't have a big family at the time. I didn't have a lot of a lot of risks. So you went for it, right? But talk about that pivot because a lot of companies wouldn't do that. They get comfortable and just, you know, stay where they're at. But you made that >>call. It was a big risk, for sure. I mean, look, the product was working. We launched the paid version of our product in 2016. Pretty quickly were onboarding dozens of accountants and attorneys, you know, doing Medicaid work. Um, in mid to late 2016, we got introduced to a large small business lender in New York City called strategic funding Source. They've since renamed them their company Capital as the current name, but we met with the CEO and the head of product and showed them a demo of the technology. And they said, You know, quote unquote, we've been looking for this for years. We've been looking for something exactly like this for years, and we said back to them about how many pages of financial documents to review every single month. They pointed out to a bullpen of dozens of people sitting there tearing through bank statements, page by page, line by line. And they said, You know, it's hundreds of thousands. My eyes almost fell out of my head. I couldn't believe the volume, and it was much bigger than what the, you know, single accountants or attorneys were doing. Uh, so we made the strategic decision to pivot at that time and focus on FINTECH. Lenders continue to tailor the product and build additional features for the fintech lending space. And and, you know, lending in general had the perfect mix of short sale cycle and high average customer value that allowed a company like ours to scale and ramp our revenue quite quite quickly. Um, and then the other thing that happened is kind of as we were getting deeper and deeper into the space, the fintech space as a whole started growing massive. So we we kind of had the perfect storm of product market fit, plus the market growing that allowed us to really ramp significantly grow revenue. And, uh, you know, despite the fact that it was the risk it was, it was totally right. Decision to to focus the business on financial services >>much bigger Tam. And you could subjectively measure it by the size of the stack of papers. Um, how how does this relate to our p A. As you know, the R p. A hot space. You probably get this question a lot, and it sounds like there are some similarities with software bots. What's the similarity? What's the difference? >>Good question. It's It's totally a synergistic offering, right? So rrp a companies like UI path and automation anywhere they typically provide a horizontal toolkit to allow you know, banks and lenders to automate much of the mundane work like, for example, collecting information from emails or doing onboarding for a new employee. Or, you know, different types of tasks that a manual worker would have done but could be automated with relatively simple code. Um, what happens in our p a. Workflows is they get hung up on tasks that can't be completely automated. So, for example, a robot might be, uh, trying to complete an intend lending flow. But when a bank statement is submitted as part of that flow, the robot can't parse it. So what they do instead, is they routed to an underwriter who performs a manual analysis, keys information into a back office system that the bank is using and that information then gets handed back to a robot and continues the automation flow. What we do is we plug the gaps that used to be manual so a robot can pass US documents like bank statements or pay stubs or tax stops. We run our unique human in the loop process. We return structure Jason output directly to a robot, and it continues into the, you know, to the next step of the flow. And, you know, in in summary, the combination of robotic process automation and human in the loop, which is what we're doing, creates true and and automated flows rather than R P. A mite by itself might get you 80% of the way there. >>So do you have, like, software integrations or partnerships with those companies. How are you integrating with them? >>We do. We have software integrations with both UI path and automation anywhere in our core fintech lending business. R P A isn't as prevalent, but we are now expanding beyond fintech lenders into mortgage lending and traditional banks. And we're also expanding use cases, right? Like historically small business lending was the core of our business. More recently, we've moved into consumer auto mortgage, additional asset classes. And as we've gotten deeper with financial institutions, we've seen even more opportunity to partner and coexist with broader r p a player's >>Yeah, great. I mean, I was just staring at their s one. I guess it was came up Monday. Half over half a billion dollars in a are are they're actually cash flow positive as you iPad. So we're going to see we're going to see them hit the public market shortly. Um, hang on, folks. Uh, now it's okay. So this is you sell a sas, right? A SAS service. Even though there's that human in the loop, that's all part of the service. How do you How do you price? >>So usage based model. So we we kind of try to model are themselves nerve. A massive company is super powerful. We apply that same concept document processing, so it's a usage based model. Customers will pay us either per application per document or per page, and if they want to subscribe for, you know, one document per month or millions of documents per month, it's up to them. And we're able to flex up and flex down to meet the supply and demand. Um and that that concept that scalability and flexibility was particularly powerful in the P P P program, right? P P. P. Was kind of a very unique situation in the sense that lenders weren't able to predict the amount of loans they needed to process in normal lending. A small business lender can tell you Hey, we expect to get roughly 10,000 applications in the month of April with P P p. They could tell us, Hey, we're going to send out 200,000 marketing emails and we expect 30% of people might reply, but we really don't have any idea, right? So what happened is the big banks ended up hiring without exaggeration. Thousands of temporary employees to come in and review documents and kind of scrambled to do this in a work from home setting during the pandemic. Whereas Cross River, they took a technology first approach. They implemented our A P I in the back end, and it enabled them to instantly scale up their resources. And the result of that is Cross River ended up becoming a top three pp, a top three p p. P lender nationally, outperforming many of the big banks with a super efficient and fast document review process. Because we were able to help them on the back end with the automation. >>That's awesome. I love the pricing model you mentioned. You mentioned Amazon. Is that the cloud you use or >>we do Our Our product is hosted in AWS and we, you know, take a lot of learnings from them from a business model and and positioning point of view. >>Yeah, and and I'm thrilled to hear you say I mean, I think a lot of forward thinking startups are doing the consumption model. I mean, you certainly see that with companies like snowflake and data dog and stripe. I mean, I think that that SAS model of okay, we're gonna lock you into a one year, two year, three year term. Sorry if if you get acquired, you're stuck with some, you know, stranded licenses. That's your problem. I think that, you know, you really thought that out. Well, um, you mentioned you're sort of expanding your your your total available market now, looking at at new markets, what are some of the big trends that you want to ride over the coming decade as you scale your company? >>The biggest one for us is mortgage automation. You know, the kind of the one of fintech small business and consumer loans were optimized, and we went from a place where, uh, you know, you would deal with a loan officer and have an in person transaction to modern day. You can get a loan from small business. If you're a small business, you can get a loan from PayPal online effectively instantly. If you're a consumer, you can get a loan from Sofia or lending club super smooth digital experience and really revolutionized the way that you know, the market thinks about financial products. I think the next wave of that is mortgage, and that's what we're focused on. Uh, you know, mortgage is a massive market in the sense of thousands of lenders. The average application contains a couple 100 pages worth of financial documents, and the pain points of the back end of the mortgage process were really accentuated. During covid, right refi Valium went way up and mortgage lenders were forced to process that volume in a work from home setting. So what happened is mortgage lenders were struggling with the concept of sending personally identifiable financial information to underwriters who aren't working in an office there, working at home and, you know, kids running around a million things going on. And it's just more difficult to manage than ever before. Um, and you know, as as the the volume kind of normalized debate and mortgage lenders thought about their own future of automation, I think there was just clear recognition across the board that these these mortgage lenders needed to learn from some of the fintech and really focus on automating the back office peace and you know, to your point earlier about business model, what we think about is translating cost that used to be a fixed cost and turning them into a variable costs So now, instead of worrying about having to match supply and demand and hire or fire people, depending on the volume that's coming in on any given month, a mortgage lender can instantly flex up, reflects down and have a super fast, accurate process to handle the darks. Um, and you know, we're seeing just awesome traction in the market with that with the mortgage space and we're excited to push >>forward there. That's great. Thank you. I mean you, Sam. You describe the chaos that work from home. The financial industry is very overly officious. If you know it's very security conscious. How do you handle security? Maybe you could comment on that. How you think about that? >>Sure. I mean, we we take a compliance first approach. We built the product from the ground up with compliance in mind, knowing that we were selling into financial institutions. We have a sock to type one and type two certification, which is, you know, an industry standard. All of our our verification happens with the Oculus employees. So there's no third parties involved in our process whatsoever. Um and then lastly, But perhaps most importantly, our product in and of itself is innately, um, you know, innately drives compliance. So every data point that we process from a financial document, we not only return the data, we return an exact bounding box coordinates of where that data field appeared on the original source so that that audit trail lives with the loan throughout its life cycle. What we saw prior to Oculus is a mortgage would go through an underwriting process. They make a decision, and then that loan might be sold downstream and a diligence firm as to come in. And they don't have the resources to review all the loans. So they review 15% of the loan tape and then they say, you know, they give a rating and what we do is we proactively tackle that by creating a a perfect audit trail upon origination that can live with the loan throughout its life cycle and that that process and that traceability has been super valuable to our mortgage and banking partners. >>So you can ensure the providence there. So let me end just by talking about the company a little bit. So you incubated you nailed the product market fit the and you pivoted and re nailed the product market fit. And like a lot of companies in your position, I would imagine you saw your growth come from just having a great product. You know, initially, word gets around, but then you got a scale. Uh, maybe you could talk a little bit about how how you did that. How you're doing that. You know where your hiring how you're hiring, what your philosophy is on on scaling. >>Sure. Look, I think the key for us is just surrounding ourselves with the right people. You know, the right mentors, advisors and investors to help us really take the business to the next level. Uh, you know, we had no pride of authorship. We're building this and recognize that there are a lot of people out there who have been there, done that and can really guide us and show us the way. I know you had interviewed Marc Roberge on on the show previously. Formerly the C r. O of hubspot. Mark was someone that we you know, we we read his book and had taken sales advice from him from an early age. And over the over time, we got him a little bit more familiar with the company. And and ultimately, Mark and his partner, J Po at Stage two Capital ended up investing in Oculus and really helping us understand how to build the right go to market engine. Um, as the company got bigger, we took on investments from really reputable firms in the financial services space. So our largest investors are okay, H C F T fintech collective and and QED investors. Uh, you know, QED was was founded by Nigel Morris, who is the co founder of Capital One. They backed Sophia and Prosper and a lot of big fintech lenders and, you know, bringing the collective expertise from the fintech sector as well as you know, from a sales and go to market strategy. Point of view created the right mix of ingredients for us to to really ramp up significantly. Uh, we had an awesome run over the years. We were pretty recently recognized by magazine as the number one fastest growing fintech company. And, you know, as the momentum is increased and the market conditions have been very favorable to us, we we just want to double down and expand. Mortgage is the biggest area of opportunity for us. And what we're seeking from a hiring perspective is, you know, go to market sales account executive type resources on the mortgage side as well as you know, deeper products expertise both on the mortgage side as well as with machine learning our product. Because we have the human in the loop piece, we create massive amounts of training data on a daily basis. So it's a, I think, a really exciting place for cutting edge machine learning developers to come and and innovate. >>What can you share with our audience about, you know, your company, any metrics and whatever you're comfortable with, how much money you've raised on my head count? If you want to get some companies comfortable giving a r r others on. But what what do you What can you share with us? >>Sure. Um, you know, we we've raised about 50 million in venture capital. We have grown from one to north of 20 million in revenue in the in the last three years. So particularly since you know, 2017, 2018 is what we really started to see. The growth take off, uh, company size. We have about 800 to 900 employees globally. Now we have about 200 corporate employees who perform the, you know, the the day to day functions of Oculus. And then we have a long tail of about 600 or so verifiers who perform data verification and quality control work again, Speaking to the human in the loop piece of the bottle. Uh, we're, you know, we're focused on expanding beyond the fintech customer base, where we serve customers like plaid PayPal lending club so fi square, etcetera into the mortgage space and ultimately into the traditional banking space where you know, the problems, frankly, are extremely similar. Just on a much larger scale. >>San Bobbly. Congratulations on all the success. You You've got a great road ahead. I really appreciate you coming on the Cube, >>Dave. Thanks so much. It's been a great chat. Look forward to keeping in touch. >>Alright, Did our pleasure. Thank you for watching everybody. This is Dave Volonte for the Cube. We'll see you next time

>> Narrator: Live from San Francisco It's theCUBE. Covering RSA Conference 2020, San Francisco. Brought to you by Silicon Angled Media >> Hi everyone, welcome to theCUBE's coverage here at RSA Conference 2020. I'm John Furrier, host of theCUBE We're on the floor getting all the data, sharing it with you here, Cube coverage. Got the best new generation shift happening as cloud computing goes to the whole other level. Multi-cloud, hybrid cloud changing the game. You're seeing the companies transition from an on-premises to cloud architecture. This is forcing all the companies to change. So a new generation of security is here and we've got a great guest, so a hot start-up. Masha Sedova, co-founder of Elevate Security. Welcome to theCUBE, thanks for joining us. >> Thank you so much for having me, John. >> So the next generation in what will be a multi-generational security paradigm, is kind of happening right now with the beginning of, we're seeing the transition, Palo Alto Networks announced earnings yesterday down 13% after hours because of the shift to the cloud. Now I think they're going to do well, they're well positioned, but it highlights this next generation security. You guys are a hot start-up, Elevate Security. What is the sea change? What is going on with security? What is this next generation paradigm about? >> Yeah, so it's interesting that you talk about this as next generation. In some ways, I see this as a two-prong move between, yes, we're moving more into the cloud but we're also going back to our roots. We're figuring out how to do asset management right, we're figuring out how to do patching right, and for the first time, we're figuring how to do the human element right. And that's what where we come in. >> You know, the disruption of these new shifts, it also kind of hits like this, the old expression, 'same wine, new bottle', all this, but it's a data problem. Security has always been a data problem, and we've seen some learnings around data. Visualization, wrangling, there's a lot of best practices around there. You guys are trying to change the security paradigm by incorporating a data-centric view with changing the behavior of the humans and the machines and kind of making it easier to manage. Could you share what you guys are doing? What's the vision for Elevate? >> Yeah, so we believe and we've seen, from our experience being practitioners, you can't change what you can't measure. If you don't have visibility, you don't know where you're going. And that's probably been one of the biggest pain-point in the security awareness space traditionally. We just roll out training and hope it works. And it doesn't, which is why human error is a huge source of our breaches. But we keep rolling out the same one-size fits all approach without wanting to measure or, being able to. So, we've decided to turn the problem on its head and we use existing data sets that most organizations who have a baseline level of maturity already have in place. Your end point protections, your DLP solutions, your proxies, your email security gateways and using that to understand what your employees are doing on the network to see if user generated incidents are getting better over time or getting worse. And using that as the instrumentation and the level of visibility into understanding how you should be orchestrating your program in this space. >> You know, that's a great point. I was just having a conversation last night at one of the cocktail parties here around RSA and we were debating on, we talk about the kind of breaches, you mentioned breaches, well there's the pure breach where I'm going to attack and penetrate the well fortified network. But then there's just human error, an S3 bucket laying open or some configuration problem. I guess it's not really a breach, it's kind of an open door so the kind of notion of a breach is multifold. How do you see that, because again, human error, insider threats or human error, these are enabling the hackers. >> Yeah >> This is not new. >> Yeah. >> How bad is the problem? >> It depends on what report you read. The biggest number I've seen so far is something like 95% of breaches have human error. But I honestly, I couldn't tell you what the 5% that don't include it because if you go far enough back, it's because a patch wasn't applied and there is a human being involved there because there is vulnerability in code, that's probably a secure coding practice when you're a development organization. Maybe it's a process that wasn't followed or even created in the first place. There's a human being at the core of every one of these breaches and, it needs to be addressed as holistically as our technologies and our processes right now in the space. >> The evolution of human intelligence augmented by machines will certainly help. >> That's it, yeah. >> I mean, I've got to ask you, obviously you're well-funded. Costanova Ventures well known in the enterprise space, Greg Sands and the team there, really strong, but you guys entered the market, why? I mean you guys, you and your founder both at Salesforce.com. Salesforce gurus doing a lot of work there. Obviously you've seen the large scale, first wave of the cloud. >> Yeah >> Why do the start-up? What was the problem statement you guys were going after? >> So, my co-founder and I both came from the world of being practitioners and we saw how limited the space was and actually changing human behavior, I was given some animated PowerPoints, said use this to keep the Russians out of your network, which is a practical joke unless your job is on the line, so I took a huge step back and I said, there are other fields that have figured this out. Behavioral science being one of them, they use positive reinforcement, gamification, marketing and advertisements have figured out how to engage the human element, just look around the RSA floor, and there's so many learnings of how we make decisions as human beings that can be applied into changing people's behaviors in security. So that's what we did. >> And what was the behavior you're trying to change? >> Yeah, so the top one's always that our attackers are getting into organizations, so, reducing phishing click-throughs an obvious one, increasing reporting rates, reducing malware infection rates, improving sensitive data handling, all of which have ties back to, as I was mentioning earlier, security data sources. So, we get to map those and use that data to then drive behavior change that's rooted in concepts like social proof, how are you doing compared to your peers? We make dinner decisions on that and Amazon buying decisions on that, why not influence security like that? >> So building some intelligence into the system, is there a particular market you're targeting? I mean, here people like to talk in segments, is there a certain market that you guys are targeting? >> Yeah, so the amazing thing about this is, and probably no surprise, the human element is a ubiquitous problem. We are in over a dozen different industries and we've seen this approach work across all of those industries because human beings make the same mistakes, no matter what kind of company they're in. We really work well with larger enterprises. We work well with larger enterprises because they tend to have the data sets that really provides insights into human behavior. >> And what's the business model you guys envision happening with your service product? >> We sell to enterprises and security, the CISO and the package as a whole, gives them the tools to have the voice internally in their organization We sell to Fortune 1000 companies, >> So it's a SAAS service? >> Yeah, SAAS service, yeah. >> And so what's the technology secret sauce? (laughing) >> Um, that's a great question but really, our expertise is understanding what information people need at what time and under what circumstances, that best changes their behavior. So we really are content diagnostic, we are much more about the engine that understands what content needs to be presented to whom and why. So that everyone is getting only the information they need, they understand why they need it and they don't need anything extra-superfluous to their... >> Okay, so I was saying on theCUBE, my last event was at, CIO's can have good days and bad days. They have good days, CISOs really have good days, many will say bad days, >> Masha: Yeah, it's a hard job. >> So how do I know I need the Elevate Solution? What problem do I have, what's in it for me? What do I get out of it? When do I know when to engage with you guys? >> I take a look at how many user generated incidents your (mumbles) responding to, and I would imagine it is a large majority of them. We've seen, while we were working at Salesforce and across our current customers, close to a 40% reduction rate in user generated incidents, which clearly correlates to time spent on much more useful things than cleaning up mistakes. It's also one of the biggest ROI's you can get for the cheapest investment. By investing a little bit in your organization now, the impact you have in your culture and investing in the future decision, the future mistakes that never get made, are actually untold, the benefit of that is untold. >> So you're really kind of coming in as a holistic, kind of a security data plane if you will, aggregating the data points, making a visualization in human component. >> You've got it. >> Now, what's the human touchpoint? Is it a dashboard? Is it notifications? Personalization? How is the benefit rendered for the customer? >> So we give security teams and CSOs a dashboard that maps their organization's strengths and weaknesses. But for every employee, we give personalized, tailored feedback. Right now it shows up in an email that they get on an ongoing basis. We also have one that we tailor for executives, so the executive gets one for their department and we create an executive leaderboard that compares their performance to fellow peers and I'll tell you, execs love to win, so we've seen immense change from that move alone. >> Well, impressive pedigree on your entrepreneurial background, I see Salesforce has really kind of, I consider real first generation cloud before cloud actually happened, and there's a lot of learn, it was always an Apple case, now it's AWS, but it's it's own cloud as we all know, what are the learnings that you saw from Salesforce that you said hey, I'm going to connect those dots to the new opportunity? What's the real key there? >> So, I had two major aha's that I've been sharing with my work since. One, it's not what people know, but it's what they do that matters, and if you can sit with a moment and think about that, you realize it's not more training, because people might actually know the information, but they just choose not to do it. How many people smoke, and they still know it kills them? They think that it doesn't apply to them, same thing with security. I know what I need to do, I'm just not incentivized to do it, so there's a huge motivation factor that needs to be addressed. That's one thing that I don't see a lot of other players on the market doing and one thing we just really wanted to do as well. >> So it sounds like you guys are providing a vision around using sheet learning and AI and data synthesis wrangling and all that good stuff, to be an assistant, a personal assistant to security folks, because it sounds like you're trying to make their life easier, make better decisions. Sounds like you guys are trying to distract away all these signals, >> You're right. >> See what to pay attention to. >> And make it more relevant, yeah. Well think about what Fitbit did for your own personal fitness. It curates a personal relationship based on a whole bunch of data. How you're doing, goals you've set, and all of a sudden, a couple of miles walk leads to an immense lifestyle change. Same thing with security, yeah. >> That's interesting, I love the Fitbit analogy because if you think about the digital ecosystem of an enterprise, it used to be siloed, IT driven, now with digital, everything's connected so technically, you're instrumenting a lot of things for everything. >> Yeah. >> So the question's not so much instrumentation, it's what's happening when and contextually why. >> That's it, why, that's exactly it. Yeah, you totally got it. >> Okay. I got it. >> Yeah, I can see the light bulb. >> Okay, aha, ding ding. All right, so back to the customer pain point. You mentioned some data points around KPI's that they might or things that they might want to call you so it's incidents, what kind of incidents? When do I know I need to get you involved? Will you repeat those again? >> There's two places where it's a great time to involve. Now, because of the human element is, or think about this as an investment. If you do non-investor security culture, one way or another, you have security culture. It's either hurting you or it's helping you and by hurting you, people are choosing to forego investing security processes or secure cultures and you are just increasing your security debt. By stepping in to address that now, you are actually paying it forward. The second best time, is after you realize you should have done that. Post-breaches or post incidents, is a really great time to come in and look at your culture because people are willing to suspend their beliefs of what good behavior looks like, what's acceptable and when you look at an organization and their culture, it is most valuable after a time of crisis, public or otherwise, and that is a really great time to consider it. >> I think that human error is a huge thing, whether it's as trivial as leaving an S3 bucket open or whatever, I think it's going to get more acute with service meshes and cloud-native microservices. It's going to get much more dynamic and sometimes services can be stood up and torn down without any human knowledge, so there's a lot of blind spots potentially. This brings up the question of how does the collaboration piece, because one of the things about the security industry is, it's a community. Sharing data's important, having access to data, how do you think about that as the founder of a start-up that has a 20 mile steer to the future around data access, data diversity, blind spots, how do you look at that and how do you advise your clients to think about that? >> I've always been really pro data sharing. I think it's one of the things that has held us back as an industry, we're very siloed in this space, especially as it relates to human behavior. I have no idea, as a regular CISO of a company, if I am doing enough to protect my employees, is my phishing click (mumbles), are my malware download rates above normal, below or should I invest more, am I doing enough? How do I do compared to my peers and without sharing industry stats, we have no idea if we're investing enough or quite honestly, not enough in this space. And the second thing is, what are approaches that are most effective? So let's say I have a malware infection problem, which approach, is it this training? Is it a communication? Is it positive reinforcement, is it punishment? What is the most effective to leverage this type of output? What's the input output relation? And we're real excited to have shared data with Horizon Data Breach Report for the first time this year, to start giving back to the communities, specifically to help answer some of these questions. >> Well, I think you're onto something with this behavioral science intersection with human behavior and executive around security practices. I think it's going to be an awesome, thanks for sharing the insights, Miss Masha on theCUBE here. A quick plug for your company, (mumbles) you're funded, Series A funding, take us through the stats, you're hiring what kind of positions, give a plug to the company. >> So, Elevate Security, we're three years old. We have raised ten million to date. We're based in both Berkeley and Montreal and we're hiring sales reps on the west coast, a security product manager and any engineering talent really focused on building an awesome data warehouse infrastructure. So, please check out our website, www.elevatesecurity.com/careers for jobs. >> Two hot engineering markets, Berkeley I see poaching out of Cal, and also Montreal, >> Montreal, McGill and Monterey. >> You got that whole top belt of computer science up in Canada. >> Yeah. >> Well, congratulations. Thanks for coming on theCUBE, sharing your story. >> Thank you. >> Security kind of giving the next generation all kinds of new opportunities to make security better. Some CUBE coverage here in San Francisco, at the Moscone Center. I'm John Furrier, we'll be right back after this break. (upbeat music)