>>from the Silicon Angle Media Office in Boston, Massachusetts. It's the cue. Here's your host Still, Minutemen >>Hi and welcome to the Boston area studio. Happy to welcome back two of our Cube alumni, both from Active e o Brian Regan, the C M O of the company. And it took Rommel. Who's the vice president and general manager of Cloud? Gentlemen, thanks so much for joining us. >>Happy New Year's too great to be here. >>Yeah, 2020 way we're talking about. We don't all have flying cars and some of these things, but there are a lot of exciting things and ever changing in the tech world. We're gonna talk a lot about N. C. Which, of course, is active use announcement. If I heard the sea, it's about clouds, about containers and about copy data management. With course, you know we know act as always quite well, Brian. Let's start with a company update first. Of course, you know, copy data management is where activity really created a category, but all of these new waves of technology that activity is fitting into Well, 2000 >>19 was an incredible year for us, you know, continued accelerating our growth in the market in the enterprise particularly, You know that the secular trends around hybrid and multi cloud really played well to our existing strengths. And 10 c really builds on those strengths will talk more about that. I know in a moment we also saw continued, you know, as digital transformation as as application modernization initiatives to cold. In just about every enterprise, our database capabilities really played again a cz a strength that we could capitalize on to land significant enterprise accounts, get started with them and then really start to expand overall data platform data management platform in those accounts >>s Oh, sure, before we get into the 10 see stuff specifically. But Brian, Brian teed up some of those cloud trends and how I think about data protection. Data management absolutely has changed. You know, I remember a couple years ago we said, Oh, well, you know, people are adopting all these clouds. All of these concerns still exist. You know. It doesn't go away. It's not magically Oh, I did office 3 65 I don't need to think about all the things that I thought about without. Look, when I do public cloud and build new applications. Oh, wait. You know, somebody needs to take care of that data. So bring us inside your customers. The team that's building these products and some of those big trends should >>happen. You're still so happy to be back in the Cube. So 2019 really defined. There were a lot of for enterprises really started moving. Production will look to the cloud multi cloud become a reality for active field way. We're running production workloads on seven o'clock platforms. So the key elements off being infrastructure agnostic wherein active you can do everything in all clark platforms. Basically, infrastructure neutral was a key element. On the other element was a single pane of glass. You could have an Oracle worker running on prime with the logic application running in azure and not know the difference. S o. The seamless mobility of data was the key element. That lot of our enterprises took advantage from elective standpoint on a lot of the 10 see capabilities adds onto those capabilities and you see more of these adoptions happening in 2020. So I think 10 seat eases up absolutely perfectly for that market. >>Yeah, let's talk a little bit about activities, place in the market, that differentiation there, that direct connection with the application and the partner's eyes. Real big piece of it. >>It's a huge piece and something we really not just double triple down on in 2019. Certainly for us our database capabilities, which we believe are really second to none in the industry, we continue to expand and enrich the capabilities, including ASAP Hana obviously already Oracle and sequel server D B two, as well as the linen space databases, the new and no sequel databases. We also understood, and as our customers were talking to us about their application modernization, they were moving Maur of their front and capabilities two containers, and they wanted that the data to come with it a t east temporarily on. So that was a big focus for us as well was making sure that we could bring the data whether it was into a V M, into a container into a physical server into any number of clouds in order to support that application. At that time, it was a critical part of our differentiation. For two dozen 1 19 >>I'd love just a little more on the database piece because you go to Amazon, reinvent and you know, the migrations of databases to the cloud, of course, is a major conversation. You look at Amazon, they have a whole number of their offerings as well, as if you want to use any database out there, they'll let you use it. Course Oracle might charge him or if you're doing it on the Amazon, the Amazon partner. The azure partnership with Oracle was big news in the back and 1/2 of 2019. So when you're working with their customers, you know, databases still central to you know how they run their business and one of the bigger expenses on the books, they're So you know what we look at 2020. You know, what is the landscape specifically from a database? Well, we continue >>to see and in most of our large enterprise accounts that Oracle and sequel servers continue to dominate the majority of the payload of databases. We don't see that changing, although we do see net new applications being built on new database platforms. Thio complement the oracle and sequel server back end. So we are seeing a rise of the bongos and the new and no Sequels out there. We're also seeing Maur consideration of building in the cloud, as opposed to starting on Prem and then potentially leveraging the cloud sort of post facto and in terms of the application architecture's. So our ability to support both the the legacy big iron database platforms as well as the new generation platforms, regardless of application architectural, regardless of the geometry of the application, is a big part of our differentiation >>going forward. >>All right, so let let's Wave hinted about it. But 10 c major announcement. Let's get into how that extends what we've been talking about. >>Absolutely so you know, we've made a lot of the new databases, particularly the no sequel databases, the Mongols and Hannah's first class citizens intensity, which means we understand not just the database. He also he also the ecosystem that the database lives. We all know Hannah's a fairly big database in terms of the number of machines that consumes number off, you know, applications that you use it and toe capture and actually provide value for Hannah. You need to understand where the Honda database lifts and so some of the capabilities we've added in 10 C's to kind of figure out this ecosystem, and when you migrate, you might need the ecosystem, not just the holiday. The peace because you know that is that is a key element. On the second aspect is the containers that that Brian touched on. Now we're seeing legacy data being presented into containers, and there's a bridge too quiet for that. Now. How do you present that bridge containers could be brought up, but they're lifeless unless you give them data. So the actors of bridge ready and you bring up the container using communities of whatever framework you have and be married the data into the container framework. So most organizations, you know, as they evolved from yesterday's architecture to today's architect. And they need this bridge, which helps them navigate that that my creation process and an active field being the data normalization platform is helping them live on both segments, Right? Nobody does us turn the switch off of the old one and move to the new That'll be co exist. That is the key element >>way spent a lot of time over the last couple of years hearing about cloud native architectures and that discussion of data, it is kind of something you need to kind of dig in to understand. I'm glad to hear you talking about, You know, when you talk about storage and container ization, you know where that fits today? Because originally it was only stateless. But now we know we could do state full environment here. But while container ization is, you know, growing at huge leaps and bounds, customers aren't taking their Oracle database and shoving Brian A lot of discussion about the partnerships. I think it was seven. You know, major cloud providers. That activity is there talk a little bit about the common native. The relationships with some >>of those partners? Absolutely. I mean, way made great strides from a go to market standpoint with our cloud partners this past year. Google Cloud is probably our most significant go to market partner. From a cloud standpoint, we've done a lot of joint engineering works in order to support both our existing, uh, software platform as well as our SAS control plane in the Google Cloud. We have landed many significant deals with with Google this past year on dhe. They have been as they continue to really increase their focus on enterprise accounts and both hybrid as well as public cloud sort of architectures. We are hand in glove with them as their backup in D R partner for those club >>workloads. >>Great eso We talked quite a bit about the database peace, but in general, back into the cloud archive in the cloud. What is 10 see specifically an active you, in general, enhance in those environments >>so tense he bring It brings in you know, the key elements of the recovery orchestration. So if I have to bring up, let's say, 500 machines in any club platform, how did I do it? Well, I can go and bring up one machine at a time and take two days to bring it up or with active fuels. Resiliency. Director. You can create a recovery plan and a push pardon Recovery happens, so we've seen a lot of customers adopt that, particularly customers that want to leverage the Google platform for its infrastructure capabilities. Wants an orchestration, that is, that is, that understands the applications that are coming up, so there is a significant benefit from a PR standpoint of the recovery orchestrations will be invested a lot of time and tuning the performance and understanding Google and Amazon and Azure to make sure this was built, right. The other big push we're seeing for the clock platforms ASAP, ASAP, as an enterprise has taken a mission to say, there's no more data centers. Everything is going to the cloud. So an escapee workloads are not the easiest were close to manage. And so they did the the intersection point of S A P and the cloud is very active. Field becomes really valuable because, though, did this data sets by definition or large, their complex and there were distributed. And the D artists of paramount importance because these air crown jewels So so those segments of the R orchestration forward with, you know ASAP and Hannah, which is to get our strength of databases. It's kind of their tense. He really hits, hits, hits a home run >>when we're talking to users in the discussion of multi Cloud in general, one of the challenges is Yoon hee. Different skill sets across. One of those powerful things I've heard from active use really is a normalization across any cloud or even in a cloud. Oh, wait. I was gonna stuck six up again in an archive. That means I'm never going to touch it again. Ingress and egress fees. You know, I have to figure these out or I need toe dedicated engineer to those kind of environments. So it seems that just fundamentally the architecture that you built it active eo is toe help customers really get their arms around those multi cloud >>environments? Absolutely. And I think there are two additional components that really one of which has lived with activity from the very beginning of the company, which is a p a p I. First, the cloud is very much an AP I centric type of operating model on with active fio We don't change the management system were operating model. But in fact we incorporate in eso all of this orchestration that it shook talked about can be actuated via a P I. The second piece, which we really started in 2017 with our eight Dato platform release, is the the consumption and the intelligent consumption of object with 10 see, we've continued to advance our object capabilities. In fact, we published a paper with the SG in late 2019 that talked about mounting 50 terabyte Oracle databases directly out of object with actually increased performance versus the production block >>storage behind it. >>So we have really with 10 C, actually added cashing to even further performance optimized object workloads, which speaks to both the flexibility but also the economic flexibility of being able. Thio contemplate running workloads in the cloud out of object at a lower cost platform without necessarily the compromise of performance that you would normally expect >>absolutely. And like you said, the skill set required. Do I need to put it in object to any reported in block? We can eliminate that right. Be neutralized that to say you want to leverage the cloud, give us your cost point and you can dial the cost up or down, depending on what you see for performance, and we will be the day that back and forth, so that flexibility is enormous for customers. >>That's greater if you talk to anybody that's been in the storage industry for a while, and you want to make them squirm, say the word migration s O. We know how painful it has been if you go talk to any of the triple vendors, they have so many tools and so many service is to help do that in a cloud era. It should be a little bit easier, but it sounds like that's another key piece. Intensity? >>Absolutely, absolutely. I mean, 10 See, you know, hits the home. I think with the A P. I integration. So the other element 2019 Saul, was the scale of deployment effective. You know, when you have to manage hundreds of thousands of machines across different geo's, that is a scale that comes to the data protection that you know, people. Really? You have a seat to actually build for it and and work with it and be sorry in 2019 and 10 See, incorporates a lot of that capabilities as well, making it ask Cloud needed as possible. So basically, around these applications globally. All >>right, uh, I was wondering if you might have a customer example toe really highlight the impact that NBC's having understand if you can't name them specifically, but, uh, yeah, >>well, actually, shook has already talked about 11 customer slash partner. Who is I think still the world's largest software company in the world based out of Germany. And they are powering their enterprise cloud on the data management data protection. Beneath that enterprise cloud across four different hyper scale er's using, active you on. I think they're on record in a weapon. Our earlier in December, talking about their evaluation of pretty much every technology out there on the one that could really deliver on performance at scale across clouds was activity >>on. The key element was they wanted a single platform with a single pane of glass across all platforms, and an active feel was the solution to each other. So >>and certainly I think we credit them and are the rest of our enterprise customers for pushing us to make 10 see more powerful and more a capable across any clout, you know, Ultimately, an inter enterprise is going to make a decision that they've probably already made the decision to incorporate cloud into their enterprise architecture. What we give them is the freedom and the flexibility to choose any cloud. And, by the way, any cloud today that might change tomorrow and having the ability to seamlessly migrate and or convert from cloud eight o'clock be. Is something that active powers as well? >>Yeah, just make sure we're clear as to what's happening there. It's great that you've got flexibility there when we're talking about data and data gravity. Of course, we're not talking about just lifting an entire database land, you know, ignoring the laws of physics there. But it's the flexibility of using a ll These various things, any way Talk about A S, A P, of course, needs to live across all these clouds. But when you talk about an enterprise, you know what is kind of that? That killer use case? Because we said we're not at a point where cloud is not a utility. I don't wake up in the morning and look at the sheet and say, Oh, I'm gonna, you know, use Cloud a versus cloud be s o. You know what is? You know the importance of that flexibility for us >>today. The majority of our business starts with company saying I need to deliver my data faster to my developers or my tester's, or even increasingly, my data scientists and analysts and my data sets have become so large that it's becoming increasingly difficult for me to do that with regularity. So the currency of the data is starting to suffer. That is the first use case for us and that that powering that enterprise transformational initiative around a new application or an updated application based on a historical app using those enterprise databases delivering that seamlessly quickly, regardless of how big the data is still remains our first use case. And then, increasingly, those customers air realizing that they can start to achieve the other benefits of active eo, including I can start to back that up to the cloud. Aiken actually orchestrate recoveries in the cloud. Not just bulk sort of transfer, but actually the entire application stack. And bring that up in the cloud. I can start Thio, take those those data sets and actually amount them into containers for my next generation application. So that starting point of give me my data as quickly as possible, regardless of how big it is, starts to become universal in terms of its applicability for all use cases. >>Yeah, I guess I shook. The last thing I wanna understand from you is in 2019. We saw a lot of large providers putting out their vision for how I manage in this multi cloud environment. You were at the Google Cloud event where Anthros was unveiled. I was at Microsoft ignite when as your ark was unveiled. VM wear has things like tans you out there. So this moldy cloud environment how do I manage across these disperse environments? What? What What are all those move mean to active you on how you look at things. >>And I think you know, the Tennessee release and with the core architecture that if you had in place, which was multiple already and a P I ready. So those are the two elements that are kind of building blocks that you can tie into any one of those construct you talked about. All right, so we've had we have customers, innovated us with Antos. If customers get up service now we have customers doing Vieira with us, right? So there are many, many integration platforms. The latest I saw was an Alexa app, but we were mounting an oracle database on a voice command. So So you know, there's endless possibilities as thes equal systems evolve because active feel stays behind the cowards powering the data delivering the data available if needed on the target. So that is the key element in the neighbor that we see that helps all these other platforms become super successful. >>So, Brian, it sounds very much a hell wind. The big trends that we're seeing here keep partnerships and, you know, meeting your customers where they need to >>pay. Absolutely. We continue Thio play in the enterprise market, where these thes are absolutely top of mind of every CEO and top of their agenda. Onda, we are working hand in glove with them to make sure that our platform not only anticipates their needs but delivers on their current state of needs as well. >>Brian, thank you so much. Congratulations on the 10 sea launch Cloud containers. Copy data management. Look forward to watching your customers and your continued Thanks. As always, Very much. All right, I'm still Minutemen. Lots more coverage here in 2020. Check out the cube dot net for all of it. And thank you for watching the Cube

>> Live from Washington DC, it's theCUBE covering Inforum DC 2018 brought to you by Inforum. >> Well we are back here at Inforum 2018 in Washington DC John Walls with Dave Vellante. We are in the nation's capital and joined right now by Massimo Capoccia who is SVP of Info OS and Rick Rider, product director at for common at Infor. Gentlemen, thanks for joining us, >> Thank you >> Good to see you both. >> Thank you for having us >> Thank you >> Let's start first off good job by the way >> Welcome to keynote.. thanks stage this morning we had some time to shine out there. Your thoughts about the show in general so far? We've been a couple of days in now, how is it going for you? >> Yeah, very very well the customers have received the Infor OS and the technology innovation and what we do with the AI very very well. You know lots of people in the hub, lots of sessions, so lots of interest on the technology innovation for Infor OS and for Infor as well. >> Sure, Rick for you? >> Yeah, its been great, it's been interesting. What we are finding out is getting a lot of this out in front of customers and partners is bringing up some interesting opportunities for us moving forward. So it is not everyday we get the opportunity to get in front of these many people within our network, so it's been great. >> So we'll be hearing from folks Let's talk about AI, especially for those who maybe don't know, haven't embraced it yet. What are the Hesitation, reservations, I mean what are you hearing from them as far as what's going to trigger them to make a decision? >> Yeah, to be honest I think they have been hesitant in the past just because it hasn't really been clear. We have talked about AI in the technology community, it's been hard to define. Some people might in fact define incorrectly, because we are making assumptions about what technology can and can't do. I think what we are uncovering. I feel we've got a pretty unique approach to what we are doing here with Infor OS and common connected to it. We are working directly with customers to identify use cases on how we can apply AI. Rather than just starting at the top and saying, "hey we should be doing all these great things and let's see how we can make it work for our customers." It's kind of we are flipping the script and starting backwards and saying, "hey what are the issues? What are the opportunities the customers have? How can we build the technology using AI to make it meaningful?" So we have business impact they want. And by doing that, I think it's a lot more understandable, it's a lot more relatable, it's a lot more trust able from our customers. >> We from in theCUBE here, watch and observe the ascendancy of the hype and so called big data. And which is sort of moderated now. But in data is plentiful, insights aren't. and so we feel we have come to the conclusion that the innovation recipe, if you will, for the next decade or so, is data, applying machine intelligence, that data and having a cloud to be able to scale it. Having cloud economics to be able to track innovation. You guys seem to have all three >> Yeah >> Of those pieces But AI without the data is just.. I don't know what it is? >> Right? Excited. >> Data without the ability to extract (laughs)...you know insights... What good is it? >> Right >> Yeah. Yeah. >> Then you got to have cloud to scale it. Your thoughts on from a platform perspective with that means? >> Yeah, Absolutely. So I was seeing the interview that you were doing with Charles, says we build this platform from the beginning. And one of the big element is that we have you know, made it possible to synchronize you know real time all this data that the applications will generates, into a single place called the data lake. So when you have the data and data lake then you can do many many things and not only analytics and reporting, which is the classical use case, but now it allows you to do AI. And the difference is we don't have one domain of the data. So some of the vendors have only CRM data or ACM data or financial data. With Infor we have all different domains of data. So we can go from ACM from financials, to asset management, to IoT readings for IoT devices, to ERP and CRM also. So when you combine when you can cross and combine the relationship with this data, then your AI is much more smart and intelligent. When you have only the AI focused on a domain, is less intelligent. So that's actually the power that we do. And our Coleman will take advantage of that, you know that you know rich data lake. >> Okay and we talked a lot to someone earlier about the stack. and that the bottom layer, is the OS >> Yes >> So everybody is familiar with what the operating system does in computer science. How is your OS similar and different? What's the function that it does if we can double-click on that? >> Yeah, so we.. It's in for operating service and we call it a service. Because it's not actually in the database and operating system level, right? So we believe... We are more in the application technology. We are the layer that takes you know the bare technology and makes it usable for a business, for an enterprise. And we build applications on top of it. So what we believe at Infor, when you have an architecture with this composite of a suite of applications. Or even the new Microsoft architecture that developers built. You still have to deliver a uniform user experience, a uniform business process, uniform security and data management and even AI. So if you look at services like Facebook or Netflix, they have maybe the entire Microsoft architecture thousands of that, but the experience is one.alright? Thus what we want to bring it to the enterprise. Infor OS big.. that unify the experience both from the end user and business process, to the enterprises. And we do it for all the cloud suites. Infor OS is all the cloud suites not just one but all of them the same services. >> So, I love the Netflix example, because if you think about digital... digital transformation, digital business. My experience with Netflix is just with Netflix I don't have a... There's no marketing department, sales department service department. I do have a problem, I go to Netflix on my app(laughs) I interact with... >> Absolutely >> So that's... I considered that what's called a product. So Rick, how does this capability get translated into product? >> Yeah. You know one thing that you brought up a lot earlier is, with all this interconnectivity and how we have to package things. So we've got all these different services that OS offer. So we've got the data lake, we've got the API gateway. We've got the integration platform, and... All those pieces is what bring this together to where, we can actually deliver something to our customers. In my case, it's an AI model or it's RPA, because of all these things are packaged together. So they don't actually see what's happening, because it's already packaged for them. >> Okay, so... what I was saying the Charles, you probably you might have seen it, is when we first discovered Infor was like, "What do you guys do?" It wasn't clear exactly what you guys were doing. But he said, and I believe him, was always our vision to have a platform. Now that... the... it's not opaque anymore, the platform is pretty clear. Now you've added the Birst Analytics, you've added Coleman AI on top of that. So you know Andy Jassy AWS always talks about the flywheel effect. So I suspect that you're entering this flywheel phase. What is that phase? What does it kind of mean for you guys, for customers, in terms of innovation? >> Yeah, is a very good question. Actually I worked for years with... We started with this platform, this journey with Charles and we start really with... okay, what's the first first issue. You know, we want to solve the integration promise. We want to give an integration platform. Then we build that. Then we start to say, okay, we want to unify the experience. We build a unified portal with a single sign on. Then we say, okay, we want to unify the data, we build a data lake. So we continue to build out the platform. We are now at the level we have a platform and its unique platform because you can say it fits in one Magic Quadrant. Because yeah, it does the iPass in the past. So with all these magic quadrants. But it doesn't fit in one, it's in all of them, right? So and in... The analyst looks at that and say, Okay, we have a platform doesn't fit in one, if it's in all of them, right? >> The Magic Quadrant is now becoming outdated, because... >> Exactly. >> Because its as you said... I don't need 15 stove pipes... >> Exactly. >> With the stove pipe thinking. >> Exactly. So.. >> With all due respect to my friends at Gartner (laughs) >> But the Fly wheel is... Yeah, the platform is going to become more and more important, relevant. The customers that... you know are in the cloud, are not in the cloud, they will use the platform to get to the cloud. It's going to be a new enabler for those customers are still on premises, to go to the cloud. We the Infor OS is enabler for hybrid process. So some some application can be in the on premises or in the cloud. With the OS they can take the journey and get to the cloud and their own place. >> So architecturally, you don't care. >> We don't care what the application side, >> Okay. But you've certainly done a lot of work to optimize AWS, you know, we're AWS customer, we know it's, it's not trivial, you have to, you know work it. It's simple, developers love it, but to really take advantage of it, integrate it with your processes will take some work. But architectural, you don't care. But it's not. That's not a that's not an offering statement, is it? I mean, today, can I run that multi cloud, run their software anywhere? >> Well >> Doing that? >> Well, today, we have a mix off, we use open source library, but we do utilize AWS, the data lake is built on S3. On AI, we use Laks, or Sagemaker for the training on the models. So we do a lot of AWS, Because it gives you our computing power and any out of the box solution for certain certain pieces. What we do we build interfaces to our application, so that our customers doesn't need to take care of all the plumbing, it's all interconnected and done. So that's, that's one of the power of Infor OS. It brings that application technology layer, between the business application and you know, the basic, you know, technologies >> And the customer doesn't want to think about the plumbing these days, right? >> Right. >> To most customers, infrastructure is irrelevant, you know, again, apologies to my hardware, friends, but they don't care about hardware, right? I mean, >> Yeah. >> It's interesting, Charles said in the keynote yesterday, when we were an onPrem software company, we didn't manage servers for our customers. Customers didn't care really about the server, and any more than they care about the plumbing today, right? >> Right. Yeah. And if I want to relate that to the AI space, all the training, all the science, all the highly computational things that we have to do, customers don't really want to know what that means or how to use that. So what we're actually doing is in conjunction with some of the AI services we're working with, with AWS is we've built a modeling platform to where they're operating in one location. They've got no concept of where this is hosted, what's going on behind the scenes, and then we connect it, we expose an API, and they can do any sort of RPI that they want to. >> So...I mean you are talking about when you talk about your customers, and they don't care about, you know, what's behind the curtain, they just wanted it to handle, maybe something up front, but yet, you have to understand what they can do. Right? You have to understand their potential. So how do you do that, when you're dealing with different companies, different sizes, different priorities, different challenges, they're different technology stages. How do you all address them individually and help them get to that better place? >> Yeah, I think, you know, it's never a one size fits, all right. So we try to give them what we've called citizen developer tool sets in the past. And I've even started to try to say, citizen data science tool set. So how can we make it more consumable by all types of users? So yes, we can provide templates, we can create these things that might work somewhat out of the box. But each one of these customers their data is, is just slightly different than need to make tweaks. So we really want to be able to, you know, provide all that flexibility. And it gets back to we start with our use cases. And then we build from there. So we get all that feedback, and make sure we're making we're hitting those key points. >> So I want to pick up on something you said about citizens, citizen data scientists. I've used that term before in front of data scientists some of them don't like it, right. That denigrates what they do. And it's true, a data scientist is a math whiz, maybe a stats, was there a data hacker they can code, Okay. And that's not every business person, right? Clearly. However, when you think about things like our RPA, I mean, you really want to enable business users. You don't want to repeat the same problem that we had for years with things like decision support, where you had two people in the company that knew how to build a Cube. And you had to have line up with an ask, please can you build my cube, I have a deadline while everybody else does too. Just there wasn't effective. So things like our RPA and low code, citizen data scientists spread that technology throughout. Now, part of that is having a platform that is I vision a studio, whereas a user, I can actually create some kind of process and code that in software, you know, code it. It is something that's repetitive that I don't have to do every day. I do it every day, I do it the same way. Somebody gave the example might have been Soma, I know somebody else, expense report approval? >> Yeah, yeah. Yeah. >> I've never not approved and expense report. I don't crack them open. Look, I don't know, maybe every now and then somebody does. Somebody does, by the way. (laughs) >> (shouts) So don't get any idea here. >> I always press the approval button, right? Why can't a robot do that and look for anomalies and say, Oh, a $300 scotch? That's... >> Yeah Yeah. Absolutely... So is that a capability that you're working on, that you have today. That what I'm envisioning a studio and then I imagine this got some orchestrator... >> Yeah. So yeah, so if you look at throughout all Infor OS, is completely Model Driven. So either you, you build a new integration, or a workflow, or a, an AI model, or a even, we have a platform as a service Mongols, where you build with low code applications. So you can take it to end to end where you you train models in AI, us suppose as an API. You can build your own app on top of it with low code and then, you know, give it to your business users. Very, very simple and in the cloud. You know, in the browser and you can do every customer can do it. So that's very important for us. We work from the beginning with this model to give you know, the tools to everybody, not only an elite of people that can do and then you know, there is the rest of the people that cannot do it. Every new computer science engineer that comes out gets you know, AI out of the box. When I did computer science, Yeah, I got some AI, you know, but it was not really like today. So every everybody can program AI now. And we want to give this tools to every developer and not just went to an elite. >> Yeah. And the workflow prediction model that you've been talking about. If you want to come join us down there, we've actually got a model that we're working on for that exact use case. >> Oh, cool. >> Yeah. So yeah. Giving the ability for those business users, as you say to... it's almost like lowering the barrier to entry to a lot of this AI technology. It's not devaluing or anything, data science, because we've got those advanced tool sets, to where if you want to do something in our studio, bring it over into the Coleman AI platform. You certainly can, we're not devaluing that. But you know, what, if we want to start and take little bites off and you want to give this in the hands of the business users, we've got a great solution for that. >> So this is all the cool stuff. This is stuff that business users care about? I mean, do they... My question is, do people care about what's under the covers? I mean, are they asking you or what's the database? And how does this work? How does that work? Or they just really want to focus on that functionality that they're getting in the business impact? >> Yeah, with the advent of the cloud, you know, people, just those questions like we sh... you know, operating system database, which technology you use? it just went away, right? So people just want to know, the functionality and the value. You know, maybe there are companies that I have more, you know, an IT architects and they want to know, more, you know, that's what they want to go down into the details, then you go into the architecture of the OS, of the application, we integrate with AWS. So we do that as well. We, you know, we talk to customers about it. But most of them, they just want to know, okay, "how can I use this platform to make my business better," right. So it runs the cloud suit, but I now I can connect to other cloud services, I can connect to the other application, I can build my own app and bring it in. So they want that business value immediately. And that's why we built this Infor OS, so that they can run the cloud suite and add business value. >> You guys at last year's analyst meeting, gave a little glimpse of some of the architecture and it was very useful, actually, analysts love that kind of stuff. I didn't get the invite this year, maybe something the some smarmy questions I ask. (laughs) But I found that actually quite impressive in terms of the tech behind it and the RND that you guys are doing there. But ultimately, it comes down to what products you can build and what business impact that has, right? >> Yeah, absolutely. I think where we're heading with this, we really don't have many limitations for what we're seeing right now. We're built in a way to where we can apply to every single industry, every single cloud suite. We have the unique, you know, possibility to where we can go through all these different industries and create these sort of value. So we've got a very unique future ahead of us. >> So. Yeah, So how much better or can you give us an idea of a road map a little bit about what you think Coleman can go? >> Yeah so, we're starting to play in the image recognition space a little bit. Maybe looking at how we can utilize things like drone technology and do inspection reports, those sort of things. It's maybe and at least my opinion, I think others kind of express the same, it's maybe the least developed area and we want to make sure we have something that works for customers the way that they're going to see value immediately. But also we're starting look at edge AI. So how can.... not necessarily just an IoT, but how can we how can we build something in the cloud? How can we create a model, then deploy that for our onprem customers who aren't quite ready, so that they can get that AI experience as well, and that predictive insight. >> It's dvallante@Siliconangle.com Is that right? Your email for the invitation >> David.valante... >> (laughs) to make sure... so what will exchange information later. >> We'll invite you (laughs) >> I'm sure this is not your territory. (laughs) >> Its on me. >> Thanks for joining us. >> Thank you. >> Its been a pleasure. Thank you for the time we appreciate that. Back with more here from Washington DC right after this. You're watching theCUBE.