 Live from Las Vegas, it's theCUBE, covering the AWS Accenture Executive Summit, brought to you by Accenture. Welcome back everyone to theCUBE's live coverage of the AWS Executive Summit here at the Venetian in Las Vegas, Nevada. I'm your host, Rebecca Knight. We have two guests for this segment. We have Hitoshi Iannaka, the CEO of Arise Analytics and Takuya Kudo, the Chief Sciences Officer at Arise. Thank you both so much for coming on the program. Thank you. Thank you. So I want to start by having you tell our viewers a little bit more about Arise Analytics. Well, Arise Analytics is a joint venture between KDI and Accenture. Well, last year, we established a company. Yeah, the Summit. Right, and that's, you know, kind of, we provide like, talent capabilities and the KDD is kind of number two, the mobile network in Japan has 50 million subscribers, massive data, so that's a lot of room to cook, but they don't have enough capability to support that. So that's why we kind of married together. And it helps companies leverage a wealth of knowledge, resources and data between firms to bring about digital transformation. That's what you're doing. So talk a little bit about what you've seen so far. Well, well, so we have two assets. KDI has a big data and Accenture has a lot of analytics skills. So using these assets, we built an integrated analytics platform hosted on AWS. And our first challenge was to reduce churn out to the other operators. And we scored the churned risk to more than 40 million subscribers and by digging into the data and using machine learning algorithm. And while data includes our tariff plan, contract period and lifestyle service usage. And we optimized customer channels and contact timing and were to target customer efficiently. And while we tried a lot of, well, out of... Out of one, too? Yeah, yeah, out of one, too, marketing. Okay. Yeah. And we can get a good result. And well, as it was not only due to our activities, but only last year, only KDI work could increase the market share among three network operators in Japan. That is our achievement. That's very impressive. So can you talk a little bit about the initial pilot in particular what you saw, Taku, do you want to? Right. So like, as he mentioned, like we have two work stream, gigantic work stream. One is for consumer facing, right? So customer channel and out of under telemarketing or like recommendation engines based upon digital stream data because we have massive like digital consumption data too, not just about like, you know, mobile handset data. And another work stream is B2B, a business domain which sounds like not related to mobile network operators, but they have machine network to sell to B2B customer. So we utilize those gigantic data, combine those. Maybe I can mention about later, but combine those data, creating new service model. So that's quite a new IoT initiatives for B2B layers and the consumer initiatives, you know, to support ongoing current business. And you're using this in a variety of sectors. In particular, I wanted you to ask you about one that you're doing with Toyota and a taxi service. Right. So should I mention? So yeah, that one is like a fabulous example because a, unless otherwise, I don't think that new business model to compete with Uber never happened, right? So KDDI provide like mobile handset, like location data over like a human subscribers creating some, you know, demand side lighters focusing model, right? Overlay on top of that, Toyota's transact log, which is technically like telematics data provide like supply side, which is cars, right? Focusing model and taxi also provide like a meters where customer lighters get in and get off and combine those three completely different capable data set. But also with things like weather and those kinds of other outside. Open data too. And combine those data set and we provide, Accenture provide like talents and creating completely new forecasting model. It's called AI taxi dispatch model. So now if you go to Tokyo, majority of taxi has our algorithm like our eyes analytics and you know KDDI and Accenture provided. So that's very cool. Can you talk a little bit about what you've learned about in terms of when the weather is like this, taxis happen this evening? Yeah, so it's of course weather has massive impact over like it's morning, specifically laying. It's boost like demands and also events. We have also events data. Maybe, I don't know, concerts, some famous singers, celebrities came and it's, you know, boost like lighters demands. So that's actually significant impact over our demand forecasting model. Rather than using pushing like Uber is like, you know, mobile app. We actually, Toyota's invented like taxi actually go because taxi driver and I can see where is a hotspot to pick up riders. And that's what we try to do. So based upon those, you know, people don't even have like maybe like my father's age, like they don't have a smartphone, they can get the benefit, universality, right? So that's the base concepts to provide universal model to those, you know. So even people lacking technology can still reap the benefits of this kind of approach. That's KDDI's philosophy is universality. So that's also our business strategy. Yeah. You're also using this approach in manufacturing environment. Yeah, that's right. We are also working with some manufacturing factory on the factory feed where experienced workers can detect machine-made brake lines before they occur. But how can that knowledge be passed onto less experienced employees? So we created a large predictive maintenance which allows companies ahead of time to play potential breakdowns. Since I've collected data about things like vibrations, temperature, and electric current, the collected data is analyzed by the AI system. So in this way, the prediction of machine failure will be a work can be performed by almost anyone or it used to be addressed by only experienced employees before. Yeah. It not only helps the company know when a machine is going to fail, it also empowers the employee to fix it him or herself. Right. It's a preventive way. And so it's up and running over the AWS. We use Kinesis and Redshift, you know, Lambda functions and over EC2. So that's completely full stack over AWS capability too. So what you're describing sounds like it requires a lot of collaboration, a lot of deep relationship building between not only Accenture and KDDI, but also the clients that you're working with. Can you describe how you all work together? Right. So maybe I'm going to provide that information. So like, of course, like KDDI's employee has specific domain knowledge and we provide like, you know, like data science capabilities and also like maybe through the interview, right? Fund workers or like taxi, they have specific domain knowledge. So combine those, collaboration. It's called two in a box. So we collaborate to be paired each employees and you know, supply the knowledge each other. So that's it's just one is not enough. But as a team integrated over the AWS and creating very strong team. And that's a, you know, we try to cherish in that sculpture and to boost the data science, data-driven companies decision-making process. So I think our viewers are pretty amazed and impressed with what's going on. But in this era of 5G and IoT, what's next? What are you working at? It's a relatively new partnership. What are some of the most exciting things in the pipeline? So the 5G, very strategic. So we are strategizing right now in terms of 5G and IoT. But the definitely one of the pieces could be like deep learning, right? And also virtual realities, which nobody has done before. So that's where we try to collaborate with other sectors, industry to create new and to do. So we need a massive like computation power like GPU servers. And we have to rely on AWS because otherwise we cannot achieve those goals. And specifically 5G maybe change the game. Maybe like, you know, low latency and, you know, wireless connectivity, you know, we don't need connections. So maybe the factory line, assembly lines, you know, completely change the way because we like edge computing no more. Maybe like fog computing, right? In between like cyber and edge because of the 5G. I don't know, but we are strategizing now in a very exciting moment we are doing right now. Indeed it is. Well, Hitoshi, Taku, thank you so much for coming on theCUBE. This was a lot of fun. Thank you. Thank you very much. I'm Rebecca Knight. Stay tuned for more of theCUBE's live coverage of the AWS Executive Summit coming up just after this.