 Hello from Las Vegas. It's theCUBE live at AWS re-invent 2021. Lisa Martin and Dave Nicholson here. We're on our fourth day, Dave. We have two live sets at theCUBE. There's a dueling set right across them. It's kind of like dueling pianos, only a little bit louder. We have had about 100 guests on the program at AWS re-invent this year and we're pleased to welcome back one of our alumni. Richard Potter joins us, the CEO of Peak. Richard, welcome back to theCUBE. Thanks Lisa, great to be here. Talk to us, so we haven't seen you in a couple of years. Talk to us about what's going on at Peak. I know there's some news coming on this week. Yeah, yeah, loads of things going on at Peak. I mean, we've been growing really quick. So since the last time you saw us, which was, yeah, in London a few years ago, we've grown to be the sort of, essentially the global leader in decision intelligence systems. Us as an AI company, we specialize in putting artificial intelligence right into the heart of how companies run their businesses and make their day to day decisions, which is why we call it decision intelligence. We think it's the biggest thing in software and probably the biggest new category of software. We will see this decade. So it's super exciting to be in that position and great to be back chatting to you guys on theCUBE. Yeah, when were you guys founded? We were founded in 2016 and you can probably tell by my accent, English company, headquartered in Manchester, but we're global now. We have operations in India. We have a couple of development centers in India. We have a growing customer base in Asia and a growing customer base in the US as well. So yeah, we're kind of international, but born out of Northern English roots. I like it. Talk to me about, back in 2016, what were some of the gaps in the market that you saw from a, because you know, as here we are in almost 2022, every company's a data company, they have to be. You're being able to extract intelligence timely, hard. What gaps did you see back in 2016? Well, actually back then, read on the market was really simple, which was that companies that are going to harness data to run themselves well will win, but that most companies were struggling to make that change to be data-driven. So our itch was, you know, as founders as three of us who started the business was trying to explore that problem. Like what stops companies running on data? And there's loads of reasons, right? Tech ones, skills ones, even just like business people using data in their day-to-day decision-making rather than say their gut feel, which I think is also a data-driven decision. They just don't understand that necessarily. So we really honed in on that problem and we grew quite quickly to be the leading business in that sort of applied data space in the UK. You know, a market leader in helping companies perform better with data. And over time that's taken us on this journey to be the sort of global leader in decision intelligence, which is really cool. But the itch we were scratching was that, hey, you know, there's something in this. We think companies that do this and do it well are going to win, but no one's doing it. So why is that? And then we've built software that effectively responds to that opportunity. You mentioned harnessing data. How do you balance the harnessing of data successfully with being harnessed by data? Because if you're talking about the concept of DI, who's making the decision? If the machine is making the decision, I better trust it. Why should I trust it? So how do you strike that balance to get people to trust what you're doing, the work you're doing for them behind the scenes? Yeah, I think it's really important that humans trust the machines that they're working alongside. And I think that's the big change we're seeing, right? So this is a new industrial revolution, the intelligence era that we're in, but all previous industrial revolutions have all amplified human potential. They've amplified like our physical potential, whether it was machinery, steam power and so on, or computers have amplified our cognitive capability. But humans have always controlled those machines, if you think about it. Now in the intelligence era, our machines can think with us, they can think alongside us. So we have to learn how to, as people, how to coexist with those machines and let those machines amplify us and essentially make us super human in what we do. And that's part of the challenge we face at peak, is to how do we humanize that? How do we make it such that everyone trusts the machine? And we always have that. Human in the loop is the way we think about it. Decision intelligence empowers us to be awesome at our jobs, make the great decisions all the time. If we trust the machine so much that we just want it to make the decision for us, we can let it, but we're always in control. And we're in control of how it thinks and what it does. And it's our job as a software company to build software that lets you understand why that recommendation or that decision is being suggested to you. So I think the coexistence of our machines alongside people in a new way, that human-to-machine interface can completely change with artificial intelligence and decision intelligence. And as people, we're going to have to relearn how we work with our technology. You just mentioned a couple of really good words in terms of the people part of people process and technologies amplify and empower. Those are two things that stuck out at me is that's what you're giving people in any, whether they're in operations or finance or marketing, it's the amplification to do their jobs, empowering them to do their jobs with data that will help make them more skilled and better able to make decisions that benefit themselves, the company, consumers, et cetera. Yeah, because if you redact doing business to its basics, it's actually just making decisions, right? Companies that make great decisions, they win and those decisions could be anything. They could be product decisions, they could be pricing decisions, operational supply chain decisions, but it's a sequence of decisions that creates value for my company. And so that's why I believe this technology is so empowering because as people, we're actually great at making those decisions. What we're not great at is making those decisions 24 by seven, really, really quickly, very consistently. So humans are awesome at forecasting, they're awesome at choosing pricing that would appeal to other people, but alongside this technology, we can have machines that do a lot of that thinking for us, speed us up, help us make more quick, great, consistently awesome decisions and then that just makes us great at our jobs. If you're a marketer or in finance or in supply chain, you become awesome. And I think that that empowerment is key to the sort of humanization of AI in business and actually that's what it means in practice. It isn't AI coming for people's jobs or replacing jobs. It's AI helping us all be great and our companies grow faster with wider profit margins when we do that, which creates more jobs for people, which is really cool. So we talk about people trusting machines to do things for them. It's not necessarily a new concept, we just sort of take some of those things for granted. I trust my refrigerator at home to measure the internal temperature and make adjustments as necessary, turn the compressor on, turn the compressor off. And I'm sorry, you're from England. Refrigerator is this thing, it's a box, we use it to refrigerate our beer, to make it cold, which I know. We do warm beer in England, too. Yeah, so it's kind of, you know, got to love those cliches. But so can you give us an example of a situation where a customer is trusting something that it's gotten from DI, from peak, where if you as the CEO heard that anecdotal story, you would be absolutely delighted? Well, I think there's loads of great examples of that. So the reason we call decision intelligence, decision intelligence is because it's applying AI into that active decision making, right? Artificial intelligence or machine learning is making a prediction or a categorization over a huge data set, right? But that on its own is kind of useless. You need to take that prediction, that forward looking view and then effectively infuse it with business logic constraints and like knowledge of how your company works to give you a recommendation, right? So let's just say I'm a marketer and I'm trying to work out who I should send a particular offer to on Black Friday over email or even not even over email, over any channel. When, if I was CEO and I heard one of my teams say, hey, what I've done is I've used the decision intelligence platform to tell me who are my customers that are in market for X type of products at Y kind of price and what channel do they like to be communicated to over, I would think that's awesome. And then that marketer would typically infuse that message with the sort of language and content that would appeal to that customer, but they're using the artificial intelligence to be super targeted and really deliver the message to that person in the way they want to consume it, which creates a really enjoyable experience as a customer. You don't feel spammed or you don't feel like it's effectively used. You feel like you're having a direct one to one personal communication with the brand or retailer that's talking to you, which in itself creates loyalty and increases the lifetime value of that relationship, which is great for the retailer. But I think using AI for those kind of decisions is essentially a great example of amplifying the human potential of a marketing team, for example. Absolutely, because what we expect as consumers, regardless of what the product or service is, is that we want brands to know who we are, what we want, don't, if I just bought a tent on Amazon, don't show me more tents, show me other things that go with it. I want you to know that. And so we have this expectation that brands, whatever industry they're in, know, oh, Richard bought this, he needs this next. Exactly, exactly. So, and I think that it starts to really jar. Now you've got some retailers and brands doing this really well and you get really enjoyable communications at the frequency you want with the offers and the promotions that are relevant to you. When you just start to get effectively stalked around the internet for something you've already bought, it becomes really jarring and frustrating. And then that actually creates a negative brand effect for that particular brand. So it's super important that these retailers, CPG, everyone really moves to this way of thinking and tries to have a direct, and that's the beauty of AI and decision intelligence, I think, for retail. If we get into retail specifically, it allows us to treat every individual customer individually because we can use the machine to make decisions on a per customer basis and then our marketing can be amplified by that. Whereas in the past, we bucketed customers into groups and just treated them all the same. Which does create a rather impersonal experience. So yeah. Which can be a negative for a brand, as you mentioned, but give them the ability to treat people individually but at scale and in real time. Which one of the things we learned in the pandemic is that real-time data access is not a nice to have, it's an essential. Exactly. One of the themes too that Dave and I have been talking about the last few days is that we're hearing it reinvent is every company has to be a data company. Talk to me about, with that in mind, are you talking to more chief data officers, chief digital officers? Where are your customer conversations as we're in this explosion of data? It's a great question that. So if every company has to be a data company and a company that's powered by AI, that means you have to be talking to everyone really. So chief information officers, chief data officers, CEO, CFOs and every sort of head of business, head of line of business, it's really important. So what we do at Peak is, as a decision intelligence platform, Peak itself unifies everything you need in one cloud platform into a single software product. That gives you all the infrastructure for your technical teams to process data, for your data scientists to create the intelligence, but then it gives you a place to work for your business teams. So it unifies your whole business around a platform. And then that means our conversations as the provider of that technology are with technical teams, they're with business teams, they're with business leaders because it has to permeate everything. So I think that's the future. Companies will have to effectively run alongside, they'll create their own intelligence basically on a dedicated platform like Peak, and that intelligence will then be distributed across the whole business in the way we do it. So I think it's really cool and exciting, yeah. Let's say hypothetically, now this is something that would never happen, but just hypothetically, say I'm an American, goes to England to take over coaching a British soccer. Oh yeah. Soccer or football. Okay Ted. Football club. Sounds crazy kind of. But how would I use Peak and DI and BI to help improve my winning percentage if I cared about winning. Because it's possible that I'm really only interested in the personal development of my team as individuals, but in athletics, is that something that is possible? Yeah, for sure. I mean, you're seeing an explosion of data science and analytics and AI techniques being used in sport, right? I mean, Peak, we're very much focused on the commercial application of AI with our platform. So we work with commercial businesses and so on. But in that space, yeah, absolutely. I mean, if you think about it, what do you need to create that intelligence? You need data and you can see it on the back of every player's shirt. They've got the little devices that are gathering data in training, in matches, constantly monitored. Those data points, feed algorithms, those algorithms can show us if a player is fatigued, you know, or they can even show us deep learning techniques can help us see patterns of play and understand like, how should we better set our teams up? How should we get players to interact on a soccer field? And yeah, and you're seeing Premier League clubs use those sort of techniques all the time. We don't do that at Peak, but yeah, I mean, I think those sort of things are readily available now for those kind of clubs to do that kind of stuff. I think Dave's angling to be a consultant on Ted Lasso. I think that's what I'm hearing. Last question for you, you guys are from an AWS relationship perspective. You guys were announced just yesterday, you were named by AWS as an ISV partner, APN partner of the year for 2021 for UK. And I, congratulations. Tell us a little bit about that. Yeah, it's really, I kind of, yeah. It's super exciting for us. It's a great recognition. Obviously they give one of those awards out every year. As a global company, it's nice to have that sort of stamp of approval that AWS sees us as their independent software vendor partner of the year. It's a great recognition for us because we come from a heritage of starting peak as a consulting company actually, just to do whatever it took to help our customers be successful. And in doing that, we had an idea for a software platform. We got some venture funding to do that. And we've turned into, you know, we became a software company a couple of years after we founded. And to get to this point now a few years later where AWS are recognizing us as their software vendor partner of the year is a huge to fantastic. Yeah, it's a huge testament to our engineering teams and the technical teams at peak that we've built something so impactful, you know? Absolutely, that validation is really, really critical. Last question in our last 30 seconds or so, what are some of the things on the roadmap that you're excited for peak for 2022? 2022 is going to be a huge year for us because I think it's the year that our platform goes out there into the wild, into the mainstream. So we made a couple of big announcements in the last few weeks. We've launched some new products on the peak platform. So there's three big platform product sets now, one very much geared around creating your AI ready data set, that's called DOC. One that's very much geared around creating your intelligence, which is factory and then an area where our business, the business teams of our customers go to work, which is called work actually. So those three big feature sets are going to be available from January and the platform is being totally opened up as a self-serve platform for anyone, anywhere to build upon. So I think it's a huge moment for decision intelligence. Gartner is saying decision intelligence is the big tech trend of next year and we feel as the market leader we've got the platform that can help everyone get on that trend really. So I think we're really looking forward to 2022 and what it brings and we think that our platform and our company is in a great shape to help more and more businesses take that leap into being powered by decision intelligence, yeah. It sounds exciting, Richard. So we'll have to follow up with you next year as to what's going on. We appreciate you joining us on theCUBE, talking about peak, what you're doing, your relationship with AWS and how impactful decision intelligence can be for everybody. We appreciate it. Awesome, thanks Issa, thanks. For Dave Nicholson, I'm Lisa Martin. You're watching theCUBE, the global leader in live tech coverage.