 Live from Las Vegas, it's theCUBE, covering AWS re-invent 2017, presented by AWS, Intel, and our ecosystem of partners. Welcome back, we are live here in Las Vegas, located at the Sands, day three of our coverage here at re-invent, AWS starting to wrap things up, but still I think making a very major statement about the progress they're making in their market. 45,000 plus attendees here, thousands of exhibitors and exhibit space being used here in hundreds of thousands of square footage, certainly reflection of the vibrancy of that market. I'm with James Kobielos, who is the lead analyst at Wikibon and we're joined once again, second appearance on theCUBE in one day. How about that for Naeke Nair, who is the president of Digital Services Management at BMC. Naeke, glad to have you back, we appreciate the time. Thank you, John, thank you, Jim, great to be here and I'm becoming a pro at this, right? You are, I know. Second time of the day. You get to collect your card and you win a prize by being on theCUBE more than once a day. Twice in four hours, that's a pretty good track record. Go pick up your toy, you know? Tell me about, first off, just your thought about the show in general. I mean, you've been in this environment for some time now, but I'm kind of curious what you think about what you're seeing here and the sense of how this thing's really taking off. So first of all, it's just the energy, the vibe, the fun that we're having here is just amazing, but I don't want to draw up to the keynote that Andy did yesterday. It's just phenomenal, the pace at which AWS is innovating. Just to be releasing over 1,300 features in a year, that is just phenomenal. I think he said innovations in a year, which I'd like to hear. It's just a year. Did he say features? Okay. Yeah, I think so, but independent of that, I'm just saying the pace at which and the amount of new stuff that they're bringing to the market is just phenomenal. Customers like us, vendors, it's just phenomenal. We hear a lot about, I mean, it's the buzzword, digital transformation, so what does it really mean to service, what transformation is happening in that? What is that pushing you on that side of the fence? How do we think about now? You know, you said the word digital and sometimes it's very hyperused and what we have done at BMC since our core is service management, we have defined what service management looks like for our customers in this digital age and we have defined it because we were primarily in IT service management for the last 10, 15 years. The future of service management in this digital world is what we call cognitive service management where service management is no longer just reactive, it is proactive, right? And it is also conversational through various agents like chatbots or Alexa or virtual agents, so it's a complete transformation that we are experiencing and we are driving most of that change for our customers right now. And of course, the word cognitive signals the fact that there's some artificial intelligence going on behind the scenes, possibly to drive that conversational UI. With that in mind, I believe that you, BMC, you are one of AWS's partners for Alexa for Business, is that true? And you're bringing it into an IT service management context. That sounds like an innovation and you tell us more about that. Absolutely, so we announced partnership with AWS and multiple fronts, one of them is with Alexa, right, Alexa for Business, where we do integrate with Alexa for providing that end user experience. Alexa was known for consumer world, right? My son uses it all the time, yes, absolutely. But now we are looking at how we could bring it into the enterprise world, especially to provide service to all employees so that you don't have to actually send an email or pick up the phone to call a service agent. Now you can actually interact with Alexa or a chatbot to get any service you need. So that's what we call omnichannel experience for providing that experience for end users, employees, customers, partners, anyone, so. So do you have right now any reference customers? It's so new, or can you give us a sense for how this capability is working in the field in terms of your testing? Do business people understand or are they comfortable with using essentially a consumer appliance as an interface to some serious business infrastructure? Like, you know, being able to report a fault in a server or whatnot. There's a risk there of bringing in a technology, like a consumer technology, before it's really been accepted as a potential business tool. Tell us how that's working. That's very interesting. We are actually seeing a very fast pace at which customers are adopting it. As we speak, I have three customers I'm working with right now who not only wants to use a chatbot or a virtual agent for providing service, not just to the employees, but to the end customers also want to use Alexa inside their company for providing service to their employees. So it is, I would say it's starting the journey as starting. We already have the integration that is working with Alexa. Customers have gotten very excited about it. They're doing POCs, they're starting their journey. I think in the next couple of years we'll see a huge uptake with the customers wanting to do that across the board. Well, I mean, give me an example of if I'm working and I need to go to Alexa business. I mean, how deep can I go? What kind of problems can be solved? And then at what point, where does that shut off? And then we trip over to the human element. Don't forget where the AI fits into the picture. If you could just have a little bit of a plumbing, not too much. So let me give you like two segments. One is the experience through Alexa. The second one is where does deep learning get embedded into the process? Yes. So usually every company has level one, level two service desk agents who are taking the calls or responding to emails for resetting passwords or fixing phone issues, laptop issues. So that level one, level two service desk process is what is being replaced through a chatbot or an Alexa. So now you can take the routine kind of a task away from having a human respond to it. You can have Alexa or a chatbot respond. Do that work. The second piece for high complex scenarios is where it switches. So being able to very automatically switch between an Alexa to a live agent is where the beauty comes in and how we handle the transition. It has all the historical interaction through the whole journey for the customer. But then Alexa forwards any information it has gained from the conversation to a human being who takes it to the next step. So when I- Can a human kick it back to Alexa at some point? No, no, we haven't seen that go back. It's usually level one, level two is where Alexa takes care and then level three is where the human takes care and goes forward. Now the second piece, the AI MLPs. In a service management, there are a lot of processes that are very, I would say routine and very manual. Like every ticket that comes in, customers have millions of tickets that come in on a periodic basis. Every ticket that comes in, how you assign the ticket to the right individual. Around the ticket and categorize the ticket, right? Is a very, I would say, labor intensive and expensive process. So we are embedding deep learning capabilities into that so we can automate, customers can automate all of those. Natural language processing, is that- The NLP embedded into it. Now customers can choose to use the NLP of their, NLP engine of their choice like Watson or Amazon or Katona. And then that gets fed back into the service management process. In fact, that's consistent with what AWS is saying about the whole deep learning space. They are agnostic as to the underlying deep learning framework you use to build this logic, whether it be TensorFlow or MXNet or whatever. So what you're saying is very consistent with that sort of open framework for plugging deep learning or AI into the, in this case, a business application. Very good. So developers within your customer base, what are you doing, BMC, to get developers up to speed and what they'll need to do to build the skills to be able to drive this whole, you know, service management workflow? So all this work that we are doing, whether these, what we call these cognitive services, they're all microservices that we have built into our platform that not only we are using in our own applications like in Remedy, like in what we call Digital Workplace, but also we have made it available for all the developers, partners, ecosystem, to consume it in their own application. So these are all micros, just like what Amazon is doing with their microservices strategy. We have microservices for every one of these processes that developers can now consume and build their own special use cases. So use cases that are very unique to their business or to their customers. Yes. So who, I mean, we were talking about this before we started the interview about invent versus innovation. So on the innovation side, what's driving that? I mean, are these interactions that you're having with customers? And so you're trying to absorb whatever that input is, that feedback, or are you innovating, you know, almost in a vacuum or in space a little bit and in providing tools that you think could get traction? Yeah. No, in fact, no, we are not just dreaming in our labs and saying, okay, this is what we should go do. Dreaming in our labs. That's not what the driver is. What's really happening, independent of the industry, you pick any industry like telcos or financial industry, any industry is going through a major, I would say, transformation where they are under competitive pressure to provide a service at the highest efficiency, highest speed at the lowest cost. So if I'm a bank or if I'm a telco, when a customer calls me and they have an issue, the pace at which I provide the service, the speed and the cost at which I provide that service and the accuracy at which I provide that service is my competitive advantage. So that is what is actually driving the innovations that we are bringing to market and all the three things that I talked about and user experience through bots or through virtual agents, how we are automating the processes inside the service management and how we are also providing that for the developers. All these three create a package for our customers in every one of these industries to address the speed, the efficiency and the cost for their service management. Go ahead, James. At this show, AWS, among their many announcements that are building on their AI, they have a new product called, and it's related to this, the accuracy, related, it's called Amazon Comprehend, which is able to build on poly in NLP, their natural language processing, to be able to identify in natural language entities like, hey, my PC doesn't work and I think it's the hard drive. Those are entities, but also identify sentiment, whether the customer is very angry, mildly miffed and so forth and then conceivably you could use or your customers could use that information in building out skills that are more fine-grained in terms of handling off to level two or level three support. Okay, we've identified with a high degree of accuracy or confidence that the problem might reside in this particular component of the system. The customer is really out of joint, you need to put somebody on this right away, and so forth and so on. Any thoughts about possibly using this new functionality within the context of Alexa for Business as you were deploying it at BMC in the future? Your thoughts? Absolutely, in fact, that is what I was very excited about that when they announced that. You know, in an NLP, NLP has been around for many years now, right? And there has been a lot of experiments around NLP. The first patent for NLP was like in the late 50s. Right, so, but the maturity of NLP now and the pace at which, like Amazon, the innovating is just phenomenal. And the real, I would say, beauty of it would be when an NLP engine can really become intelligent where they can understand the sentiment of the customer. When the customer is saying something, it should detect whether the customer is angry, happy, or on the edge, right? So, we are not there yet. I'm really excited to see the announcements from AWS on the comprehensive side. If they really can deliver on that, understand this sentiment, I think it would be phenomenal. It's brand new. Yeah, and I don't want to get this off the tracks, but it's a fascinating point. Because, as you know, words in a static environment could be interpreted one of 50,000 ways. So, how do you get this AI to apply to emotional pitch, tone, agitation? How do you recognize that? That is where NLP, the maturity of NLP at which it's moving is what's going to be game-changing in the long term. It's for it to be able to know what the underlying sentiment is. Anger, excitement, joy, despair, I mean, all those things. Like, I've had enough, can be said many different ways. And that's when we'll switch to a live agent. If it's not, we'll quickly switch to a live agent. The bottom gives up, right? When is that a motion threshold for you? Human being might be the best, immediate. I'm just curious. It's fascinating. Yeah, absolutely. Yeah. Well, thank you for the time. We certainly appreciate that. And we promise this will be it for the day. All right, no more cube duty. But we certainly wish you all the best down the road. And like you, I think we've certainly seen and have a deeper appreciation of what's happening in this marketplace of what we're seeing here this week. Right. It's been extraordinary. Thank you, John. It was a pleasure and really excited to have two cube interviews in a day. How about that? But I think it's a great forum for us to get our message out and get the world to know what we are doing as BMC and Innovations. Talk to real innovators in the business world. So I'll power to you. Thanks for the time. Thank you. Thanks to you. Back with more. We are live here at Reinvent AWS in Las Vegas. Back with more live here on theCUBE right after this break.