>>from around the globe. It's the Cube presenting Cuban cloud brought to you by Silicon Angle. Hi, this is David Linton. You're watching the Cubes coverage of the Cube on Cloud, our own virtual event where we're trying to understand the future of cloud, where we've come from and where we're going. And we're bringing in visionaries to really have that detailed conversation. Daniel Jones is here. He's the CEO of automation specialist. You. I path Daniel. Thanks for coming on and sharing your insights here. >>Thank you so much for inviting me. They've appreciated. >>That's always a pleasure to get together with folks that have started companies with a seed of a vision and have exploded in tow. You know, great success. And when I wanna go back to the the the founding days of you, I path 2005. It was a pre cloud. There's certainly pre cloud as we know it today. A w s came out in 2006. Aw, and then we saw the clouds Ascendancy. But but your original founding premise there was no cloud, you know, it wasn't like a startup could just spend up stuff in the cloud. But what you've seen that evolution. So when you first started to see cloud evolved, What did you think? Did you think Oh, well, we'll see what happens. Or did you? Did you know at the time that this was gonna be a bigas? It actually has become. What were your thoughts back then? >>Well, I honestly, I thought that we are kind of agent. And maybe it's stupid to not to pie foot in tow, The new trends in technology like Cloud Mobile social and I we kept, you know, working on this computer vision technology that 15 years ago, war was not really hot. But with the evolution of self driving cars and the latest development in AI, we we've been able to capture our investments in the domain that was not hot. But suddenly, you know, became the word the of the greatest minds in I t. And we definitely we specialize Our computer vision toe a narrow use case, but still, it's the It's the key of what we've done in, uh, in the end, the robots are powered by computer vision technology. This kind of a robot emulate how human user work. So obviously we use vision a lot in our day by day work and having the best technology that allows our robots to interact with the computer screen more like human user is quintessential and, uh, making our business reliable and easy to use. So we were lucky. But I always felt that maybe I should change it. And we were feeling I remember you know, many discussions with my, you know, initial developers because we like what you're doing. What we felt a bit left outside my door. What way? Got lucky in the end. >>So So I have a premise here and that when you go back to the early days of cloud, what they got right was they were attacking the human labor problem and they automate it was storage. It was it was networking. It was compute. But really the automation that they brought toe i t. And the quality that that drove and the flexibility was, you know, a game changer. Of course, we know that now. And you know, many of us at the time were very excited about Cloud. I'm not sure we predicted the impact that it had, but my premise is that there's a parallel in your business with the automation that you're driving into the business. We've talked toe people, for instance, that some of your customers have said, You know I can't do Six Sigma. I can't afford to do six Sigma before things like R P. A. For business process. I do that for Mission critical things, but now I can apply six Sigma thinking across my entire business that drives quality. It takes costs out of my business. So what do you think about that premise? That there's a parallel between the early days of cloud taking human labor out of the equation and driving quality and flexibility, cost saving speed and revenue, etcetera and what you're doing on the business side, >>it is clearly a parallel. I can tell that the cloud was built by looking at ICTY Automation use cases first of all, because this is all software engineers understand the most software engineers. Let's be you little on this. They don't understand the business work. They don't understand all how the rial work is performing a big enterprise and they don't care. Sometimes when in my own discussions with our CFO, he is surprised that I don't know all the use cases in the world. Yes, of course. I don't know exactly how an insurance company work All the processes in a health care, all the banking processes. I have intellectual curiosity how they were. But what interests me the most is our computer vision technology that works uniformly well across different. That was the same from the cloud. So initially they built and they build a cow cloud one toe, help them when what they know the best. And now, for we were put in the face of having great technology, this computer region technology, but without having a great use case in the I t world that we understood. And when we when I'm speaking about our early days like 12, 13, 14, I believe this technology has a lot less applicable bility in the real world. Because again, we were thinking of some sorts of small I T automation gigs that were not possible just doing the AP ice. But when I discovered the messy world of business processes and how important is to emulate people when you think automation, that was a big ah ha moment. So I believe that we can do for business processes what the cloud has done for I t processes on. We are really patient now about this business processes on helping people toe eliminate all the repetitive work that is their delegate. This work two robots and have the people that are required to do this work do do better. A smaller number of tasks every day. Everyone has own, as on her or him played today like, let's say, 10, 20 different activities. Some of them can be completely delegated to rob to robots, and they are the low value type of activities, while they can focus on the high value activities like interaction with people, creativity, decision making and this type of human like things that we as humans really love. >>I love that you shared that story, but you thought it was a very narrow, sort of set of use cases when you first started and then, you know, that's that's just an awesome founders, you know, really ization. I love it when we've often said in the Cube that, you know, for decades we've marched to the tune of Moore's Law. That was the innovation engine. No longer is that case. It's a combination of of data, applied machine intelligence and cloud for scale. And I guess the computer vision pieces How you in just the data you've you've made some investments in a I and there's many more to come the industry in general and the cloud is sort of the piece of that equation that we see for scale. So I wonder how you see those pieces fitting to your business. Uh, and how important is the cloud for your scale? At last? Uh, at last year, I path forward. There was a lot of talk amongst your customers about scaling. Is the cloud critical for that scale? >>Yeah, I believe so. And we are thinking of clouds in tow. Distinct ways number one. We're offering Onda manage automation service in our own close, using where we host everything by ourselves, including our orchestrator, and then be next to have the plans to include our the robots that execute the automation And people simply can't connect to our cloud building automation and just scheduled to run without any maintainers. And they will have access to oh, great analytics, Everything integrated. So this is a major force to us, and the way we launching G a. This cloud offering in April this year, and I can tell you that until now, 20% of our customers already are in a shape or another in this type of offering, not 20% dollar amount, but 20% of our customers. And it's clear that at this point this has mawr applicability into the long tail, a smaller customers than in the on our biggest customers. But the second, this thing type of cloud offering that we focus on is toe have best in class support and best in class multi cloud support for the cloud of choice of our customers. For instance, if you go in if you go in a w, g, c, p usher and you buy a subscription there, you wear buildings. Specialized editions were with one click. You will be able to install our technology in those clouds and you'll be ableto scale up and down your robots. You can connect your robots to our many service were within your tenant, but basically the angle is toe lesson. Ah lot the administration, the maintainers footprint of your installation, either on our own cloud, even on your cloud of choice. I'm a strong believer that we will see an accelerated transition from the completely on Prem Workloads into these two source of cloud workloads. >>I wanna ask you, is a a technologist if you see. So you mentioned that you're gonna take your products and your support. Multiple clouds will run on any cloud in A lot of companies are talking about that, you know, for their respective whether it's a database or, you know, whatever storage device, etcetera. Do you see the day where you'll actually start? You're collaborating across clouds. Where the user, uh, maybe maybe the user today doesn't know, but maybe a developer does know which cloud it's running on. But do you see any value in actual, you know, connecting across clouds where the data and one cloud is relevant for the data? Another cloud is I know there are latent see issues. Is that you know, technically feasible. And is it it? Will it drive business value? What do you think about that cross cloud connection? >>I believe it is already happening. There is a mesh between between various services and who knows in which cloud they are awful. Already. I feel the Leighton see is less and less of a problem as much as the biggest cloud provider have have a very distributed geographically president. So as long as I can playing AWS in East Coast, on on Asia in East Coast, it's not such a big Leighton see issue. Uh huh. Frankly, in the past, our customers at least start telling us they seen how it is to be completely looking toe one technology on people would like Toa have optionality. It's not necessarily that I will use three clothes, but I would like to use the vendor that gives me optionally even. And this is what we're trying to offer. >>Do you, when you think about the future of work? I mean, e said before the cloud one dato was infrastructure storage, networking, computing Uh, it seems like to Dato we're bringing in more ai new workloads. We're seeing, you know, analytics and machine intelligence applied to the data and then, you know, distributed at scale self serve to the business. How do you see the future of work specifically as it relates toe automation affecting that, uh on you know what role does cloud play there? What's your vision? >>So as the workloads will move to cloud. It's absolutely critical that the processes will move to cloud, so there is no way back. I think, that moving in tow, moving from home for and software into cloud will make even easier toe automate this type of workloads into the cloud. It's gonna be less maintain us. You will deal less with legacy applications that require some special care. It's kind of a bit more easier to automate modern Onley, Web based type of application so that Z we'll see an acceleration on the moving to cloud. But again, there will be different sorts of cloud from a completely manage automation service from us toe managing yourself the automation in your cloud tenant, but not on prayer. I'm not a big believer that we will accept unless very few critical sectors I don't think that we will see home Primor roads in the past five years. >>I mean, I agree in this case, the business case for on Prem just gets, you know, less and less. I mean, it'll be a certain applications for sure. My last question is, when thinking about from a software developer standpoint, you obviously you're gonna wanna run in a W S and G, C P and Azure. Uh, perhaps Alibaba, Uh, do you look at other clouds? Whether their regional clouds, of course. You got your own cloud. Maybe Oracle. IBM. How do you think about those? Do you just sort of evaluated on a case by case basis? You let customers, you know, tell you where you need to be. >>Yeah, way focus on the on the three big clouds today, but we're building on the top off Q Burnett is most of our way. We have a big shift in tow building que Burnett is micro services. And my guess is that all mother clouds would offer fantastic support for kubernetes. So what What it takes when you create a new edition for another cloud is toe is toe have the underlying services. Like if we plan to use snowflake, for instance in our analytics offering, you better have snowflake in another cloud. Otherwise, probably the the analytics will will have toe be delayed or use a less of one part technology. So it's not only about what we are building, but it's also, you know, the vast availability of other set of technologies that we try toe use when you choose a technology. Now, first of all, we are looking. We need to choose something that is multi cloud. There's who's dedicated from one cloud vendor. That's that's our first priority. This is why I've mentioned snowflake and then when when we moved into a cloud. We are limited by the offerings that are there, but I my belief is in the main clouds, probably in the US I don't know one of the region's what's gonna happen, but in the main crowds in the U. S. In I believe that they will. In the end, they will catch up in terms off offering and convincing of other defenders toe have kind of kind of similar offering on their own. I don't know if, besides, the Big Three, or you'll see someone and that is able to compete could be too much fragmented. Maybe they will be dedicated clouds for certain services. But for General Cloud, I think three is more than enough. >>Yeah, and so, you know, in the early days of cloud, people talked about dial tone, and essentially, that's what's becoming. It's the it's the value that's running on top of the cloud from software companies like ey Path and others that is really driving. So the cloud to Dato the next generation Daniel Dennett is thanks so much for sharing your vision on participating in the Cuban cloud. Really appreciate it. >>My pleasure, Dave. Thank you so much for inviting. >>You're welcome. You always great to talk to you. And thank you for watching everybody keep it right there. We'll be back with our next guest right into this short break. This is Dave Volonte for the Cube. Yeah.

>>from around the globe. It's >>the Cube with digital coverage of Dev >>Ops Virtual Forum Brought to You by Broadcom. Welcome to Broadcom, Step Ups, Virtual Forum I and Lisa Martin and I'm joined by another Martin very socially. Distance from me all the way. Coming from Birmingham, England, is Glynn Martin, head of Q. A transformation at BT Glenn. It's great to have you on the program. >>Thank you, Lisa. I'm looking forward, Toa. >>As we said before, we went live to Martin's for the price of one in one segment. So this is gonna be an interesting segment, Guesses. What we're gonna do is Glen's gonna give us a really kind of deep inside out view of Dev ops. From an evolution perspective, Soglo's Let's start transformation is at the heart of what you dio. It's obviously been a very transformative year. How have the events of this year affected the transformation that you are so responsible for driving? >>Yeah. Thank you, Leigh. So I mean, yeah, it has been a difficult year Bond, although working for BT, which is ah, global telecommunications company. Relatively resilient, I suppose, as an industry through covert, it obviously still has been affected and has got its challenges on bond. If anything is actually caused us to accelerate of our transformation journey, you know, we had to do some great things during this time around. You know, in the UK for our emergency and health workers give them unlimited data and for vulnerable people to support them and that spent that we've had to deliver changes quickly. Um, but what? We want to be able to do it, deliver those kind of changes quickly, but sustainably for everything that we do, not just because there's an emergency eso we were already on the kind of journey to by John, but ever so ever more important now that we are what we're able to do, those that kind of work, do it more quickly on. But it works because the implications of it not working is could be terrible in terms of, you know, we've been supporting testing centers, new hospitals to treat covert patients, so we need to get it right and therefore the coverage of what we do, the quality of what we do and how quickly we do. It really has taken on a new scowling what was already a very competitive market within the telco industry within the UK. Um, you know, what I would say is that you know, we are under pressure to deliver more value, but we have small cost challenges. We have to obviously deal with the fact that you know, Cove in 19 has hit most industries kind of revenues and profits. So we've got this kind of paradox between having less cost, but they're having to deliver more value quicker on bond, you know, to higher quality. So, yeah, certainly the finances is on our minds. And that's why we need flexible models, cost models that allow us to kind of do growth. But we get that growth by showing that we're delivering value, especially in, you know, these times when there are financial challenges on companies. >>So one of the things that I want to ask you about again looking at, develops from the inside out on the evolution that you've seen you talked about the speed of things really accelerating in this last nine months or so. When we think Dev ops, we think speed. But one of the things I love to get your perspective on we've talked about in a number of the segments that we've done for this event is cultural change. What are some of the things that scene there as as needing to get, as you said, get things right but done so quickly to support essential businesses, essential workers? How have you seen that cultural shift? >>Yeah, I think you know, before, you know, test test team saw themselves of this part of the software delivery cycle. Andi, actually, now, really, our customers were expecting their quality and to deliver for our customers what they want. Quality has to be ingrained throughout the life cycle. Obviously that you know, there's lots of buzzwords like shift left. How do you do? Shift left testing. But for me, that's really instilling quality and given capabilities shared capabilities throughout the life cycle. That Dr you know, Dr Automation drive improvements. I always say that you know, you're only as good as your lowest common denominator on one thing that we're finding on our Dev Ops Journey Waas that we were you know, we would be trying thio do certain things quicker and had automated build automated tests. But if we were taking weeks to create test scripts or we were taking weeks to manly craft data, and even then when we had taken so long to do it that the coverage was quite poor and that led to lots of defects later in the lifecycle or even in in our production environment, we just couldn't afford to do that. And actually, you know, focusing on continuous testing over the last 9 to 12 months has really given us the ability Thio delivered quickly across the the whole life cycle and therefore actually go from doing a kind of semi agile kind of thing where we did you use the stories we did a few of the kind of, you know, as our ceremonies. But we weren't really deploying any quicker into production because, you know, our stakeholders were scared that we didn't have the same control that we had when we had more water for releases. And, you know, when way didn't think ourselves. So we've done a lot of work on every aspect, especially from a testing point of view, every aspect of every activity, rather than just looking at automated test, you know, whether it is actually creating the test in the first place, Whether it's doing security testing earlier in the light and performance testing. Learn the life cycle, etcetera. So, yeah, it Z It's been a riel key thing that for for C T for us to drive, develops, >>talk to me a little bit about your team. What are some of the shifts in terms of expectations that you're experiencing and how your team interacts with the internal folks from pipeline through life cycle? >>Yeah, we've done a lot of work on this, you know, there's a thing. I think people were pretty quiet. Customer experience. Gap. It reminds me of a cart, a Gilbert cartoon where, you know, we start with the requirements here on Do you know, we almost like a Chinese whisper effects and what we deliver eyes completely, completely different. So we think the testing team or the the delivery team, you know, you know, you think they've done a great job. This is what it said in the acceptance criteria, but then our customers the same Well, actually, that's not working. This isn't working, you know, on there's this kind of gap Way had a great launched this year of actual Requirement Society, one of the board common tools Onda that for the first time in in since I remember actually working within B. T, I had customers saying to may, Wow, you know, we want more of this. We want more projects, um, to have a actual requirements design on it because it allowed us to actually work with the business collaboratively. I mean, we talk about collaboration, but how do you actually, you know, do that have something that both the business on technical people can understand? And we've actually been working with the business using at our requirement. Designer Thio, you know, really look about what the requirements are. Tease out requirements to the hadn't even thought off and making sure that we've got high levels of test coverage. And so what we actually deliver at the end of it, not only have you been able Thio generate test more quickly, but we've got much higher test coverage and also can more smartly, you're using the kind of AI within the tour and with some of the other kind of pipeline tools actually deliver to choose the right tests on the bar, still actually doing a risk based testing approach. So that's been a great launched this year, but just the start of many kind of things that we're >>doing. But what I hear in that Glenn is a lot of positives that have come out of a very challenging situation. Uh, talk to me about it and I like that perspective. This is a very challenging time for everybody in the world, but it sounds like from a collaboration, perspective is you're right. We talk about that a lot critical with Dev Ops. But those challenges there you guys were able to overcome those pretty quickly. What other challenges did you face and figure out quickly enough to be able to pit it so fast? >>I mean, you talked about culture. I mean, you know, Bt is like most come countries companies. So, um, is very siloed. You know, we're still trying to work to become closer as a company. So I think there's a lot of challenges around. How do you integrate with other tools? How do you integrate with you know, the various different technologies and bt we have 58 different whitey stacks? That's not systems that stacks all of those stacks of can have, you know, hundreds of systems on we're trying to. We're gonna drive at the moment a simplified program where we're trying Thio, you know, reduce that number 2 14 stacks. And even then they'll be complexity behind the scenes that that we will be challenged. Maurin Mawr As we go forward, how do you actually hired that to our users on as an I T organization? How do we make ourselves Lena so that even when we you know, we've still got some of that legacy and we'll never fully get rid of it on that's the kind of trade off that we have to make. How do we actually deal with that and and hide that for my users a say and and and drive those programs so we can actually accelerate change. So we take, you know, reduce that kind of waste, and that kind of legacy costs out of our business. You know, the other thing is, well, beating. And I'm sure you know telecoms probably no difference to insurance or finance we've got You know, when you take the number of products that we do and then you combine them, the permutations are tens and hundreds of thousands of products. So we as a business to trying to simplify. We are trying Thio do that in a natural way and haven't trying to do agile in the proper way, you know, and really actually work it paste really deliver value. So I think what we're looking Maura, Maura, at the moment is actually, um is more value focus? Before we used to deliver changes, sometimes into production, someone had a great idea or it was a great idea nine months ago or 12 months ago. But actually, then we end up deploying it. And then we look at the the the users, you know, the usage of that product of that application or whatever it is on. It's not being used for six months, so we're getting much we haven't got, you know, because of the last 12 months, we certainly haven't got room for that kind of waste and you know, the for not really understanding the value of changes that we we are doing. So I think that's the most important thing at the moment is really taken that waste out. You know, there's lots of focus on things like flow management. What bits of the our process are actually taking too long, and we've We've started on that journey, but we've got a hell of a long way to go, you know, But that that involves looking every aspect off the kind of software delivery cycle. >>What are some? Because that that going from, what, 58 i t stocks down to 14 or whatever it's going to be go simplifying is sounds magical. Took everybody. It's a big challenge. What are some of the core technology capabilities that you see really as kind of essential for enabling that with this new way that you're working? >>Yeah. I mean, I think we've started on a continuous testing journey, and I think that's just the start. I mean, that's really, as I say, looking at every aspect off, you know, from a Q, a point of view. It's every aspect of what we dio. But it's also looking at, you know, we're starting to branch into more like a AI ops and, you know, really, the full life cycle on. But, you know, that's just a stepping stone onto, you know, I think oughta Nomics is the way forward, right? You know all of this kind of stuff that happens um, you know, monitoring, you know, monitoring systems, what's happening in production had to be feed that back. How do you get to a point where actually we think about a change on then suddenly it's in production safely. Or if it's not going to safety, it's automatically backing out. So, you know, it's a very, very long journey. But if we want Thio, you know, in a world where the pace is ever increasing the demands of the team and you know, with the pressures on at the moment where with we're being asked to do things, you know more efficiently Ondas leaving as possible. We need to be, you know, thinking about every part of the process. And how do we put the kind of stepping stones in players to lead us to a more automated kind of, you know, their future? >>Do you feel that that plant outcomes are starting to align with what's delivered? Given this massive shift that you're experiencing, >>I think it's starting to, and I think you know, Azzawi. Look at more of a value based approach on. Do you know a Zeiss? A princess was a kind of flight management. I think that's that will become ever evermore important. So I think it's starting to people. Certainly realized that, you know, people teams need to work together. You know, the kind of the cousin between business and ICT, especially as we go Teoh Mawr kind of sad space solutions, low cold solutions. You know there's not such a gap anymore. Actually, some of our business partners expects to be much more tech savvy. Eso I think you know, this is what we have to kind of appreciate. What is I ts role? How do we give the capabilities become more for centers of excellence rather than actually doing Mount amount of work And for May and from a testing point of view, you know, amount, amount of testing, actually, how do we automate that? How do we actually generate that instead of created? I think that's the kind of challenge going forward. >>What are some? As we look forward, what are some of the things that you would like to see implemented or deployed in the next say, 6 to 12 months as we hopefully round a corner with this pandemic? >>Yeah, I think you know, certainly for for where we are as a company from a Q A perspective. We are. Yeah, there's certain bits that we do Well, you know, we've started creating continuous delivery. A day evokes pipelines. Um, there's still manual aspects of that. So, you know, certainly for May I I've challenged my team with saying, How do we do an automated journey? So if I, you know, I put a requirement injera or value whoever it is, that's why. Then click a button on bond, you know, with either zero touch of one touch, then put that into production and have confidence that that has been done safely on that it works. And what happens if it doesn't work? So you know, that's that's the next in the next few months, that's what our concentration is about. But it's also about decision making, you know, how do we actually understand those value judgements? And I think there's lots of the things Dev ops, ai ops, kind of always that aspects of business operations. I think it's about having the information in one place to make those kind of decisions. How does it all tied together, as I say, even still with kind of Dev ops, we've still got elements within my company where we've got lots of different organizations doing some doing similar kind of things but the walking of working in silos Still. So I think, having a eye ops Aziz becomes more and more to the fore as we go to the cloud. And that's what we need to. You know, we're still very early on in our cloud journey, you know. So we need to make sure the technologies work with Cloud as well as you kind of legacy systems. But it's about bringing that all together and having a full visible pipeline. Everybody can see and make decisions against >>you said the word confidence, which jumped out at me right away. Because absolutely, you've gotta have be able to have confidence in what your team is delivering and how it's impacting the business and those customers. Last question for you is how would you advise your peers in a similar situation to leverage technology automation, for example, dev ops to be able to gain the confidence that they're making the right decisions for their business? >>Yeah, I mean, I think the the approach that we've taken actually is not started with technology we've actually taken human centered design a za core principle of what we dio within the i t part of BT. So by using humans tend to design. That means we talked to our customers. We understand their pain points, we map out their current processes on. But when we mapped out, those processes also understand their aspirations as well, you know, Where do they want to be in six months? You know, Do they want to be more agile and you know, or do they want Teoh? Is this apart their business that they want thio run better? We have to Then look at why that's not running well and then see what solutions are out there. We've been lucky that, you know, with our partnership with Broadcom within the P l. A. A lot of the tortures and the P l. A have directly answered some of the businesses problems. But I think by having those conversations and actually engaging with the business, um, you know, especially if the business hold the purse strings, which is you know, in some companies, including as they do there is that kind of, you know, almost by understanding their their pain points and then saying This is how we can solve your problem We've tended to be much more successful than trying Thio impose something and say We're here to technology that they don't quite understand doesn't really understand how it could have resonate with their problems. So I think that's the heart of it is really about, you know, getting looking at the data, looking at the processes, looking at where the kind of waste is on. Then actually then looking at the right solutions. And as I say, continuous testing is a massive for us. We've also got a good relationship with capitals looking at visual ai on. Actually, there's a common theme through that, and I mean, AI is becoming more and more prevalent, and I know yeah, sometimes what is A I and people have kind of the semantics of it. Is it true, ai or not? But yes, certainly, you know, AI and machine learning is becoming more and more prevalent in the way that we work, and it's allowing us to be much more effective, the quicker and what we do on being more accurate. You know, whether it's finding defects, running the right tests or, you know, being able to anticipate problems before they're happening in a production environment. >>Welcome. Thank you so much for giving us this sort of insight. Outlook at Dev Ops, sharing the successes that you're having taking those challenges, converting them toe opportunities and forgiving folks who might be in your shoes or maybe slightly behind advice. I'm sure they appreciate it. We appreciate your time. >>It's been an absolute pleasure, Really. Thank you for inviting me of Extremely enjoyed it. So thank you ever so much. >>Excellent. Me too. I've learned a lot for Glynn Martin and Lisa Martin. You're watching the Cube?

>> live from London, England. It's the queue covering a ws summat. London twenty nineteen, Brought to you by Amazon Web services, >> come to the A. W s summit in London's Excel Center. I'm Susanna Street, and David Aunty is my co host today on the Cube. This means so much to talk about here at the summit today to do with machine learning and a I. And I'm really pleased to say that we have to really key people here to discuss this. We've got time. Tom Summerfield, who is head off commerce, a foot asylum on also Richard Potter, who is the CEO of Peak. Now you guys have really formed a partnership. Haven't you put asylum? Is a leisure wear really? Retailer started in bricks and mortar stores. Really moved online on Peak is a pioneer for artificial intelligence. System's really well to get together. What What sparked? Really your demands. Ready for their services, Tom. >> Yeah, well, so way knew that we needed to be doing something with data on A and we didn't really know exactly what it would be Way were interested in personalization, but then also in a bigger picture, like a wider digital transformation piece for the business where well established bricks, a martyr business, but then a fast growing online business. And we're interested to know how way could harness the momentum of the stores to help the digital side of the business and also vice versa. On we thought data would be the key, and we ended up having a conversation with the guys at Peak, and that's exactly what we've been able to do. Actually, on the back of that deliver, we're delivering a hyper personal experience for our consumers Now. >> I was one of the statue that I notice when looking into what you be doing, a twenty percent increase in email revenue. So that's quite remarkable, Really. So Richard, tell us, you know how you're able to do this? What kind of services that you lean on? T make those kind of result. >> It's a combination of a lot of things, really. You know, you obviously need people who know what they're doing from a returning a business perspective. Married with technical experts, data science algorithms, data. Um, I think specifically how we've done it is a pig's built, a fairly unique A I system that becomes almost like the central brain within our customers. Businesses on off that algorithms help automate certain business processes and deliver tangible uplifts in business performance like the twenty eight percent uplifting sales here, Um, in order to do it. So it's quite a long journey, I suppose. The outlook we took when we started collaborating was was that if we could deliver that hyper personalized shopping experience, we were always going to be ableto show customers the right product at the right time. And if we were doing that that we would lead Toa High brand engagement, higher loyalty higher on higher lifetime values of customers. And that's and that's what's shown to be the case in silent example. >> Yeah, definitely that echo that. You know that the high profits hypothesis wass If you can show the right custom of the right product at the right time, then their purchase frequency average order Volumetrics all start to move positively and ultimately than affecting their long term engagement with our brand, which increases revenue on also delivers a more, you know, a frictionless consumer experience, hopefully for the customer, >> because I suppose your experience is the same. So many companies out there they're sitting on this huge pile of data, yet they don't know how to best optimize that data. When did you first realize, Richard that there was this kind of gap in the market for Pete to grow? >> Yeah, I think data and analytics have come on a bit of a journey away from common sense reporting tio more advanced analytics. But when you get a I and machine learning what you're talking about, his algorithms being our self learning make predictions about things that actually fundamentally changes the way businesses can operate on DH. And in this case, a great example is you know, we're sending hyper personalized marketing communications, Teo, every single for silent customer. They don't realize necessarily that they are tailored to them, but they just become more relevant. But it doesn't require a digital marketing to create every single one of those campaigns or emails and even trigger the sending of those materials. Brain takes care of that. It can automate it. And what the marketer needs to do is it's faded, engaging content and set up digital campaigns. And then and then and then you're left with this capability where eyes saying you might be a market for this product. Let's let's send you something that might appeal to you on DH that just gives that gives a marketing team scale. And then, as we move into other use cases like in the supply chain for film and delivery of product the same thing the team's just get huge scale out of letting algorithms do those things for them. Andi, I suppose the realization for us that there was that gap in the market was just that you can see the out performance of certain cos you can see that Amazon attributes five percent of their sales to their machine learning recommendation systems. I think Netflix says eighty five percent of all content is consumed >> because it's Al Burns. Andi. Companies >> like that can harness machine learning to such a great degree. How does how did howto other businesses do it? Who can't access that talent pool of Silicon Valley or along the global? You know, the global talent leaders in tech and that's that's where we had the insight that his peak way could create a company that gave our custom is that that technology and that capability Teo deliver that same kind results that the Amazon and Netflix >> so before the Internet brand's had all the power you could price however you wanted if you overprice, nobody even even knew. And the Internet was sort of like the revenge of the consumer. Aye, aye, And data now gives the brands the ability to learn more about its customers. But you have to be somewhat careful, don't you? Because their privacy concerns obviously DPR etcetera. So you have to have a value proposition for the customer, as you were saying, which they made are you know that machine is providing these offers, but they get value out of it. So how do you guys think about that in terms of experience for the customer? And how do you draw that balance? >> I think from my angle, that Richard touch on a couple of bits there to do it scale first and foremost across the entire alarm on Thai network of consumers is killer element to it. But to deliver that personal experience, I think consumers nowadays are so they're more expectant of this. Really. We would have considered it innovation a couple of years ago, but now actually it's expected, I think, from the consumer. So it's actually in the name ofthe You have to move forward to stand still. So but way think where we're right at the front of this at the moment. And we're really looking now how we optimize the journey for the consumer so that actually we know if we're from some transactional data that we have in a little bit of over behavioral data that, you know, we're really conscious of the whole GDP, our peace and stuff, and that's really, really relevant and super important. Andi, I'm pleased to say that you know, we have that. We know that by a peek, it's completely on lock down from that perspective as >> well. Where did the data's where the data source of comfort. You mentioned some transaction data. Where is the other day to come from using show social data and behavioral data? Where does that come? >> So those elements of social data, some of it is a little bit black box. You can't always access it, and that's a GDP, our peace there, and rightly so. Actually, in some cases we have a loyalty scheme which allows us to understand our Kashima's better in our bricks and mortar retail, which is really cool that we've got some of that transactional data on a customer level from the stars. We know that some people in our sector maybe don't have that, so that so that allows us to complete sort of single customer view, which then we can aggregate in peaks brain, then transaction data on the website in the app and bits off browsing, you know, just within our own network. You know where customs potentially being and reacted with somethin. A piece of content. Janet within the website, that's that's how we build that view. >> Do you think this is the way that more bricks and more two stores Khun survive? Because so many are closing in high streets up down the UK and in other countries because simply they're not really delivering what the customer wants? >> Yeah, I think so. We rich now. Both feel quite strongly now that wear so onto this now a little bit. It's a really As as our relationship for the two businesses has evolved, it's become clearer and clearer that actually we've armed with this. You know this data, our fingertips, we can actually breathe fresh life into the stores, and it's in the eye of proper true Omnichannel retailing way. Don't mind where the cost consumer spends the money. We just need to be always on in a connected environment so that A Z said before pushing the right product at the right time. And when they're when they're in market, we turn up the mark the message a little bit. But then understanding when they're not in market and maybe to back off him and maybe we warn them what with a little bit of a different type of message then and actually we're trapped with one challenge ourselves to send but less better marketing communications to our consumers. But absolutely that store piece is now, so we tail back. Our store opening strategy is a business to focus more on the digital side of things, but now it's possible that way might open some more stores now, but it will be with a more reform strategy of wet, wet where, why we need to do that? >> Isn't this ironic? The brick and mortar marketplaces getting disrupted by online retailers, obviously Amazons, that big whale in the marketplace, and your answer to that is to use Amazons, cloud services and artificial intelligence to pave the way for your future. Yeah, I mean, that's astounding when you think about >> me. Yeah, this sort of unified commerce approach, Tio, you know, there's a place in the world for shops. It's like it's not Romance isn't completely dead and going shopping. It turns out, you know so on. Actually, yeah, we're using honesty in the eight of us, but we'LL hire our friends at Peak. Yeah, it's it's some irony there. I think it's really cool. >> And that decision that you made obviously wasn't made made lightly. But you saw the advantages of working with the clouds outweighing the potential trade offs of competition. >> Yeah, I mean, that's not that was never really, really no, I'm certainly not know. I think this is something that is happening, that data, and on harnessing it in a safe, responsible, effective way, I believe, is the future of all commerce. So >> that as far as security is concerned because, of course, we have had data breaches your customers, credit card details, access. How do you ensure that it's as secure as possible in the way that you you you choose the services I think >> that come that just comes down to best practice infrastructure on the way we look at it, a peak is there's no bear tools in the world to do that, then the same technologies that Amazon themselves use. It's to do with how you configure those services until ls to make it secure, you know, And if you have an unsecure open database on a public network, of course that's not secure. But you could have the same thing in your own infrastructure, and it wouldn't be secure. So I think the way we look at it is exactly the same thing on actually, being in the Amazon prime for us gives us a greater comfort, particularly in terms of co location of date centers and like making sure that our application fails over into different locations. It gives us infrastructure we couldn't afford otherwise, and then on top of that, we get all these extra pieces of technology that can make us even more secure than we could do. Otherwise we'd have to wait, have to employ an army of infrastructure engineers, and we don't have to do that because we run on Yes. >> Okay, so we were able to eliminate all that heavy lifting. That same goes. You've got this corpus of data. I'm interested in how long it took to get through. A POC trained the models how much data science was involved. How much of a heavy lift was that? Yeah, well, I think for >> us we better be pretty rapid. Actually, we started working together in January last year, so we're only just sort of year into that. >> And in that faith in that entire >> sofa length of of our relationship, we've gone from high for personalizing digital campaigns to recommendation systems on a website to now optimizing customer acquisition on social media and then finally into the supply chain and optimizing demand and so on it. And I think there's >> a lot of reasons >> why we've been able to do it quickly. But that's fundamental to the technologies that the peak is built. There's two. There's two sides to it. Our technologies cut out a lot of the friction so way didn't run a proof of concept. We were able to just pick it up, run with it and deliver value. And that's to do with I think, the product that peak is built. But then you obviously need a a customer who's who's going on a transformation journey and is hungry to make that make that stick in London on. Then when the two come together, >> I think that it's an interesting point that, though, because while suite for asylum, we always I always say it's that we're not. We're not massive, but we're not tiny, but it's the sort place you Khun turn upon a Monday and say, I've had an idea about something and we're not doing it by Friday. That's That's a nice, agile culture. It can create some drama as well. Possibly. I think it's really straightforward to get straight into it. And I think this is where some of the bigger, um, sleepier high street retailers that Amar, fixed in a in a brick from our world, needs to not be too afraid to come out and start embracing it, because I think some of them are trying now. I think it might be a little bit late for some now, but it's just it's just it just wasn't that hard really to get going >> and you've seen the business results, can you share any measurements? or quantification. We've >> got a really a really good one that we're just talking about at the moment. Actually, Way were able to use segmentation tools within within the peak brain Teo to use them on Social than Teo. Create lookalike audiences. So Facebook Custom tools, Right? We'LL help you create audiences that it thinks you're the right buyer. It's complex algorithms itself, but we almost took a leap ahead of their algorithms by fire, our algorithms uploading our own segments to create a more sophisticated lookalike audience. We produced a row US results or return on that spend. People are not familiar with that of eight thousand four hundred percent, which Wei would normally be happy as a business, we've sort of seven, eight hundred percent. If you're running that that we've say on AdWords campaign or something like that, that's quite efficient campaign. So it's at zero. We were a bit like it felt like it's a mistake that, you >> know that is >> not the right, >> Yeah, but not so that's super cool. And that's really that's really opened our eyes to the potential of punishing that the, you know, our sort of piquet I brain to then bring it onto Social on. Do more outward. Advertise on there. >> So moving the goal post meant that your teeth are really high school. Thank you. Thank you very much for telling us all about that time someone feels on which floor. Sir. Thank you for joining me and David Auntie here at the eight of US Summit in London. Merchant to come on the King.