 Welcome back everyone to theCUBE's coverage here on location at AWS Reinvent. That's their annual conference. I'm John Furrier, your host. 11 years covering Reinvent, seeing the movie many times. But this year, more than ever, it's more on point around generative AI. We've seen the change. All the hype is being matched up with major announcements. Just great energy changing the game. Let's go to the next level. It's totally legit. It's happening with two great guests here. Get Simon and Ryan here from Mission Cloud. Congratulations on being up on stage. Thank you. And getting recognized and your success. And great to see you guys again. CUBE alumnus, welcome back 2014. 2014. Three bars. Two shows that don't run around anymore. But anyway, it's all good. And what's interesting is that last year, I met with Adam and I kind of added this notion of, hey, this is next gen cloud coming. And no, it's ISVs. We're the cloud. I'm like, okay, well, you're starting to see ecosystems form. You're starting to see platforms emerge. And it's been happy for a while. Last year, we saw the beginning of it, the rise of the snowflakes, the rise of the Databrickses, MongoDBs. Companies sitting on top of their infrastructure, building networks and platforms. And they have ecosystems and they're solving bigger problems. It's not just software. It's a service. It's just changing. And obviously, Genevieve AI kicked in in an even more obvious, that the changing of the development environment with Genevieve AI is happening. And you guys are doing that right now and your AI practice has been around for a while. So you're not a stranger to AI. Everyone's on the bandwagon now. We've been doing AI for years. You guys actually have been doing AI for years. So give us- Certainly Ryan has. First of all, give us the update. What's on stage relevance? What's happening on stage? And let's get into the AI practice. Well, Mission Cloud, we started at six years ago. And so we've been growing. We're premier partner now. And we started the practice three years ago when Ryan joined. And of course, he can talk about some of the projects we've been doing over the last few years, but the acceleration just in the last year of demand. And the amazing thing that I find, as the business leader of Mission, is there's just every single use case is totally understandable. You know, document summarization, you know, AI assistant, they're just, they're readily understandable use cases that we can go out there and pitch to our customers. So that's why there's such an acceleration. I mean, the heavy lifting, which is Amazon's kind of thing. We automated way, the undifference of heavy. Well, that's kind of like for infrastructure, I get that, but the AI's, there's a lot of heavy lifting stuff that no one wants to do that you can do with AI and do it better. Right, absolutely. With a human in a loop or not. Absolutely, yeah. Yeah, and I think, you know, for us, you know, we've been doing NLP for a long time, right? And so it's pretty, it was kind of one of those things when Gen AI, right? Gen AI is interesting because ChatGPT is a toy, right? What did ChatGPT do? They made a web interface on top of a model. Well, before you had to go and do a bunch of work to get that model ready, right? But now it's, you know, people see the, have their imaginations awoken. So you're asking about the stage, we're working with a company, Magellan TV. They create documentaries and things you don't think about. They want to do content localization, right? Right now they're US based. They want to, you know, push it out across the world. And so how do you do that, right? You've got to look at, okay, I've got to take and make a transcript of everything. Then I have to translate it. Now, in the US, we suck at English, right? We're just terrible, like we have idioms and slang and everything like just a mess, right? You were talking about it earlier, just, you know, all kinds of jargon. And so you have to sit there and go, okay, I got to first do an English to English translation. So that's one of the spots we use the Titan model is to figure out, take all the slang and all the idioms out, create clean English. And you take that and you translate it. And then when you translate it, because it's documentaries, you have windows, right? You have time windows where you're like, okay, I got to fit in a time window. So we do summarization, right? Because after you translate, if it becomes too long, it's like, okay, I got to summarize that. Like we have pretty heavy prompts that are like, you need to blah, blah, blah within, you know, 10 seconds and you know, every language we look at, there's something new, right? Like we're doing a bunch of German right now and everything has an article in front of it, right? In the English, we don't use articles. I mean, that translation is hard. Translation is extremely difficult. How do you guys, what's the quality in that? How do you get that checked? Because do you, I mean, it's not always the same. Even in English, first of all, put the English aside with the translation in jargon. But the translation to that in foreign language is very difficult. It is, but you know, there's a lot of programs out there, translate from Amazon does a pretty good job. And we also, there's a translator that works for Magellan that, you know, we're doing hand, you know, they're doing hand checks of everything for the first, you know, the first like, let's dig into that example. So let's take that company. So they didn't do films, whatever. What's without mission? What's the process and with mission? What's the, give me the, the foreign after. The business problem that they have is because it's documentary film, it's long tail content. So they can't afford, excuse me, to go out and spend, you know, $4,000, $5,000 per documentary to localize, but they also can't actually go out and test new markets. Yeah. And they would have to spend a lot of money to show this up front cause they didn't know what the market is. They literally just wouldn't do it. They would just gradually and permanently. Because there's too much money up front to figure out the other market for. Exactly. But now, you know, with the system that we've built, they can very cost effectively, order of magnitude, say, look, yes, we want to sign with this new distributor, we want to go into Germany, France, you know, other countries around the world. And so that's the business model just makes a lot more sense. So on the tech promise, is it saving time? Is it, or is it? It's both, right? So it would be about $20 a minute, traditional way. And it's like less than a dollar a minute through the pipeline that we built out for them. And you've got it almost instantaneous versus people doing it essentially by hand. So basically they can get into a market economically, test it, see about it. So you guys took that burden away, the hurdle was high. That's right. All right, so what's the core business right now that you guys have going on here? How did it all get to come together? And what's the relationship with AWS? Why the onstage partner recognition? Well, we really built an overlay business that combines resale, financial operations, managed services and a whole range of consulting but all focused on AWS. And that's kind of unique in the market. A lot of companies are focused on multiple cloud ecosystems and so on. And so what that means is we've got this continuous engagement model across all of our customers. So wherever they are in their lifecycle, they might come to us for a migration, you know, and then it's cloud operations, they might come to us for a data and analytics project. So as a company we've grown now to 500 customers and about 350 team. And it's, you know, we're at that scale now where I think AWS is absolutely realizing that, you know, when we get involved, the customers more secure, they're happier, their projects go faster. And ultimately we actually grow AWS's revenue about two X what, you know, customers would grow without mission being involved. You guys are great partner for Amazon but there's now the AI piece, obviously that's hot. We kind of touched upon it in remars because that was kind of a cool kind of AI kind of vibe show. Talk about the AI because, you know, again, the joke on the cube is me and Dave always say, I've been doing, we've been doing AI for years and that's been everyone kind of has but there's the haves and have not really been doing it. Like, so like, what is AI? I mean, I can say we've been doing AI but not really, it's not really pure NLP. We've got some in the extraction. We do some things, I mean, it's all, I mean, that's all playing around but it's not serious AI. So you guys have been doing some serious AI for a while. Take us through how that started and how it's evolved and what you're looking at today because I'm sure you got to, looking at the JNAI as a huge opportunity. JNAI is absolutely massive. Yeah, I mean, I started basically, you know, grad school, maybe undergrad, doing AI stuff, a lot of computer vision. I worked for a think tank for a long time, built AR devices and then sitting on my couch after the AR company I worked for imploded and started at a different partner and built that practice. So built all the relationships with AWS. We got bought by a company I won't name that destroys every company they buy. I feel like I can think of, I won't be going, let's not go there, pro tip, don't sell. Exactly. So then I joined Mission to build the practice, right? Start from the ground up, you know, we already had a lot of relationships with AWS and I'm known through the AWS community so we were able to build another team at Mission for AI, doing the computer vision, the predictive stuff and a lot of NLP work early on. And then with JNAI, we were there already, right? We had all the use cases. We were doing summarization. We were using the models and so we became more or less for small, medium business and startups as, hey, this is the partner that's done it. They know what they're doing, come in and work with them and it's been crazy. AWS just had kind of a cool funding program where we've lined up for the next six months, like 35 JNAI projects, like it's going to be crazy. And they needed to help. You were hitting the early adopters early, okay? And then as the hype kicked in, that grew and then when the super hype kicked with the ChatGPD, it's funny, ChatGPD, you mentioned the interface, before they launched it was called a chatbot. I mean, basically, I mean, they don't say that anymore. It's now a revolution. But I think it is, it was a browser moment. I mean, to me, I think that was great about that moment, was it educated the masses that this new thing, I mean, the way it streams the results was cool. I mean, that's like... I mean, it reminded me so much of when Google launched. Yes, apparently it was the same sort of thing. It was like, oh, a very simple prompt. Yeah, and so people, I knew like, they don't even know how I speak, like tech Russian, I guess, like other people, what is Kubernetes, what is the jargon? They're like, they're getting it. So that must have a huge impact to your business. What's been that result for you guys? I'm sure that there's been a tsunami of business going to your doorstep, now that the whole world is rushing to try to figure out how to engage with the models, what's the architecture look like, data pipelining. There's a lot of engineering that needs to go on to set up the developer market that's booming, that's going to come on board. We predict that, and our research team's got some data that the developer market will surge in popularity as the bed rocks get better, you're going to have developers feeding on that like a frenzy. And it will, you know, it's, I think it's still very early days. So we're seeing just a lot of experimentation. And so what's interesting is we haven't yet seen like the underlying infrastructure growth really kick in, you know, full tilt yet, but so much experimentation, that's going to continue for a while. But when Adam Slipsky announced like Amazon Q and Q being embedded in Code Whisperer yesterday, you can just see the hyper-efficiencies that, you know, this new AI assistant as well. I mean, we're probably going to embed it into some of our software and so on, that it's, so I think our strategy overall is just lean in, we're hiring a lot of people as well. AWS is actually helping us hire through a strategic collaboration agreement that we signed earlier this year. So a lot of it's about just go, go, go. So your relationship is pretty deep with Amazon. Yes. You're all in on Amazon. We're all in on Amazon. No other cloud just in the US. No other cloud, correct. Okay, so they must love that. Yeah. They do. I mean, we were one of the first partners to get access to Bedrock back in June, so we've been using it for a long time, right? And, you know, it's crazy, like Simon said, you know, we have eight use cases that we've built out for customers over the last, you know, year and even more now as foundation models become easier to use. And it's crazy we've built, you know, our own architecture pattern that we call Ragnarok, you know, we love some good Marvel, you know, but instead of just ending in the scene, we added the extra K, but, you know, obviously it's rag and then the N.A. is for agents and then on Bedrock. A little clever hack there, beautiful. That's sort of the party rock that they launched you. That was kind of clever. What's the end game now for you guys on this next leg of the journey? I'm saying, not end game, next step, better way to put it. As you're now set up, you know, it's like you said, you got to get lean in, get inside the tornado as that book would say, you don't want to be, you don't want to get too, you don't want to get thrown around, you don't want to get inside the action. You're already there. What's the next step for mission? Well, this is maybe a little contrarian, but we're not going to change out domain name to missioncloud.ai. Because someone else got it. Because, no, because like, you know, we built the company from the start. We really want to be like the largest independent cloud services platform company in the world, you know, with AWS and we're already well on our way in the US. And I think, look, AI is this new mega trend. It's going to drive so many use cases, it's going to drive a lot of our business. But at the same time, there's still so much else that we're doing for customers, like, you know, the cloud operations, the, you know, a lot of the typical stuff. We don't want to push that aside and just be like. But your business is not just services. You're a manager's cloud. Correct. So you're front-ending AWS. Yes. We're simplifying the experience for SMBs with mission control. Building use case template kind of model where people can just have solutions on top of. Exactly. So you're at the top of the stack for Amazon, basically. Yeah. And I think the big thing for us on AI is like, we're not doing the simple stuff, right? Like, Swamy just announced, right? Okay, you can now integrate it to make RAG easier. Okay, whatever, right? We're doing stuff with like- Give it an example of some hard stuff. Yeah, we're working with a company that's like, that do those printed books, photo books, right? And so right now you come in, it's a pain, right? It's terrible, pick a template, all that, right? And so they've seen with their business, hey, a lot of people stop because they're just tired, right? Like, what am I doing here? A lot of people mix and match templates until they're like, how do we make this total gen AI, right? How do I come in? No longer have to build templates. No longer have to have all the embellishments, stickers and all that. How can I give the customer, hey, build some pages and then have an autocomplete button, right? So we're working on, okay, you uploaded some pictures. Let me caption the pictures, then take the captions and build a story out of it and then create the full book out of that. So, you know, that's well past any chat box. Yeah, and then you get to computer vision background as we talked about in our last QB interview. You bring up a good point and this comes back down to inertia and people stuck in the old ways and there's a theme that I'm seeing where there's some companies that's just so established with these data warehouses that they literally are stuck. They don't even know, they're like paralyzed from an agility standpoint. They can't even move. Do you guys see some of that? And for the folks that recognize that, hey, I got to either blow this up or put a wrapper around it or do something. How do they get from that antiquated paralysis to movement forward? Yeah, so I'll talk about this a lot. So it's kind of interesting, right? Like you have Gen AI and then you have Gen BI, right? With QuickSci and everything trying to push Gen BI. So I've told people like next year is going to be the year where everyone's like, my schema really sucks and everyone's going to be redoing all their database schemas to make it so that these Gen BI tools can work, right? So they can gather that information. AWS is using data zone and things like that to kind of help with that. But that's going to be a lot of that. So you're clear. You see this as like, there's going to be a reset of schemas and databases. Also the other thing about the keynote that I want to bring up is that, I don't got to end quickly, but you mentioned the demo on the queue. The whole thousand Java apps in two days and then dropping the little hint of .NET to Linux. I mean, to your point about things changing. I mean, that blew me away. I really fell out of my chair. I'm like, that's huge value. I mean, can you imagine the impact on cost? License cost on .NET alone. Alone, I mean, that's going to be like push a button, sign me up if I'm a big company. I mean, that's the radical nature of what's coming out of this. Yeah, and a lot of the systems do that coding difference. Like we have a couple of projects that are there they often have just templates, right? Where they need to redo SQL or other templates and they want their customers to just be able to write a quick sentence, right? And have, here it all is. Well, Ryan, let's get together again soon. Simon, let's do a deep dive on all the stuff on business and the tech. I know we got to go. Last minute we have left, put a plug in for what you guys are working on. You're on stage, got an award, saw that. What are you guys doing? What's next? You're hiring, what's on your goals? Give a plug for Mission Cloud. The big thing is we launched Mission Control in the AWS Marketplace. So it's a really easy on-ramp for customers, particularly in the SMB realm, to be able to bring all of our services together. And so it's our first ISV play, the fourth leg of the stool. So that's the plug I'll make. What did you say, Ryan? My plug is one of the only one-stop shops out there, right? You can come to Mission, do your resell, do your 24-7 MSP and professional services. There's no one else out there that can do everything for a company. Ryan, congratulations on all the hard work you guys put in to it. Great to see you guys again. 2014 OpenStack, world's changed. I know, I'm not gonna ask. It turns over, turns over. It's good fun. Thanks for this way, I appreciate it. We back with more Cube coverage back to the studio for On Location here. We'll be right back with our next guest after this short break.