(lively music) >> From our studios in the heart of Silicon Valley Palo Alto, California, this is a CUBE Conversation. >> Hi I'm Peter Burris welcome to another CUBE Conversation from our outstanding studios in beautiful Palo Alto, California. As we move forward with digital business and generally the very notion of data better informing human activity, the role that AI is likely to play has become an enormous topic of discussion. Both from a stand point of what it can do, but also from a stand point of what it should do and when it can and should be able to do it. Many enterprises are facing challenges that try to unlock the potential of these technologies, as a consequence of a lot of technological and methodological and other considerations. That's what we're talking about today. What can enterprises do to accelerate the appropriate and proper and successful use of AI within their business. And to do, that we've got Simha Sadasiva who's the CEO of Ushur, with us here on theCUBE. Simha welcome to theCUBE >> Thank you, thanks, good to be here. >> So give us a quick update, what is Ushur? >> Ushur is a broad platform to automate a number of different workflows for enterprise companies. So I started this over five years back with a vision to basically drive automated customer conversations but the more I met with customers and understood the types of problem they were actually looking to solve, it was apparent to me that the more business processes you attach in relation to the conversational automation that you can drive through some of the new technologies that we have available to us, you can actually impact a lot more different types of outcomes for companies. So we went on to create a very broad platform that automates back office processes, as well as customer conversations for a number of different Fortune 1000 and Global 5000 companies. >> Alright, but lets start with this notion of how these enterprises are going to use AI better, because certainly our clients are struggling with a lot of this stuff. They're sometimes successful, they're often not and the nature of the success is sometimes tied to particularly successful development team or successful choice of a tool or something else. What is the problem as you talk to customers, how would generalize the problem, in achieving those outcomes with AI related technologies? >> Yeah, so I always take this approach of understanding business problems that companies are looking to solve rather than just looking at technology and applying it for that specific problem. So as we go about learning about the industry and the transformations that are going on, every C-level executive or stakeholder in a company, is looking at ways and means to transform their business. So you hear this term, digital transformation that's used or in vogue, in every major enterprise company that you talk to. Everyone is worried about how do they, number one, stay incumbent in their line of work without getting disrupted. B, how can they actually run their business and transform their business using technology that is available to them and also consumer behavior has evolved quite a bit over the past generation, past decade I should say. The ways and means that we connect and interact socially has evolved. Businesses want to interact with you in the same ways and means that you are interacting with your friends and family in a social circle. So there are lots of moving parts here, so. >> Let me stop you there- >> Yeah. >> So I as an industry analyst, I use the word digital transformation all the time. But it actually means something, and this is what I want to test with you, so, every business constitutes it's work, it's workflows, it's tasks, it's organization, it's value proposition and how it engages customers around what it regards as most important assets. >> Absolutely >> To us, the very notion of the difference between business and digital business is digital business treats data as an asset which means a digital business transformation is the process of reconstituting work, value, propositions, engagement models, governance models- >> Yeah >> Around the idea of data as an asset and AI seems to me to be an essential feature of that process. Would you agree with that? >> Yeah so, digital transformation is a very broad term but what it actually means is you're moving away from paper based forms, from record keeping- >> You're reconstituting work >> Absolutely, you're redefining how work was done. How do you onboard employees, customers, partners you know, from legacy forms to new forms engagement, new forms of record keeping, and once they become digital then you understand, know and can serve those constituents a lot better. And what happens with AI is the possibilities are that you can not only drive a lot of automated ways to onboard, administer and operate those relationships, but you also learn. You learn from those engagements, all those interactions, and it gets continuously better and better with time. And that's the promise of artificial intelligence and machine learning. >> So let me see if I can, because a though just popped in my mind, that, about kind of the history or the evolution of some of these solutions where we had labor based, physical based activities. We digitized forms, so we digitized the things that people used in those activities, but not necessarily the tasks they performed. And then we ended up with, you know things like RPA, process automation what not, where we took a given set of tasks that happen on a screen 'cause they're now electronic, and we could turn those into robots starting to remove some of the non-discretion work to try to better scale and try to get better productivity. AI seems different though, right? >> Yeah. >> Because AI is not just doing things against a recipe it's also inferencing, it's trying to, I hate to use the word understand, but it's trying to mimic human cognition in doing this. Is that kind of where you are now? >> Yeah, absolutely, absolutely. So these transformations have happened over decades right, so Cloud was one of the first things that came of age, you know Cloud started 20 years back but now in the past 10 years, you've seen every major enterprise talking about Cloud based initiatives. And then if evolve that from an automation perspective now 15 years back you had a lot of companies that started with the RPA type solutions and now we are talking about intelligent automation, or cognitive automation. And what that means is you actually bring the power of the ability to learn, listen, understand information understand, you know, objects, understand images understand language, in ways and means that were not possible previously. Computing, the access to big data, our big databases, big data handling technology, analytics, all of these constitute and enable what's possible today with artificial intelligence and machine learning. And the way we look at it is, we take these cognitive systems and they provide solutions to problems that were previously not possible. For example, we can take a core intake process in an insurance company, something that would take two weeks for an insurance company, to respond back to a core request. Because they have to look and assess the risks involved in that application process. Now if you feed an engine, like Ushur's, with information that were made previously, that a certain, you know, whether this was a adjudicated to be accepted or rejected from a risk perspective. Now we can instantaneously provide a response to a new application that comes in, rather than wait for two weeks. That's possible because we can learn and infer from past decisions that were done and it actually drives automation and drives adjudication of that specific workflow accelerates the entire time it takes to make a decision. >> Simha, I get, I talk to a lot of AI companies that make a lot of claims and each one tends to do a small part very well and then they expand the importance of that. Nothing wrong with that, everybody's struggling to try to do this better. You're taking a platform approach. >> Absolutely >> So when I think of platform, I think of starting all the way out from, how do I approach understanding a problem to the actual outcome being executed, but there are an enormous number of steps in between. >> Yeah, absolutely. >> But describe how those steps are being laid out and specifically how your company is providing tooling and automation to facilitate that process. >> I've done a number software startups in my career and one the things I have learnt Peter is that platforms don't make good business models, but applications do. But you have to have a broad vision and when you want to build a platform you have to show customers how to use the platform. So what we do is, we take template approach or a use case approach. While our platform is extremely broad when we are talking to an insurance company versus a health care company versus a technology company, you have to show specific applications of how you can actually take this platform and, you know, use that platform for let's say automating the intake process in an insurance world or a claims process in an insurance world or an IT service management automation for a technology company, right. Or a prescription refill for a health care company. So these are all specific and definitive use cases that we have templatized and you know, we are just getting started and these templates are enormously useful for these companies to start with and they get these companies a starting point to deploy a solution in a quick and rapid- >> But those use cases are those templates have historically been relatively rigid. >> Right >> And that's been one of the challenges that a lot of companies have had how do I fit these together? The integration work historically has been very difficult. What I think I hear you say is that, yeah you need to be able to have artifacts and constructs that make sense in context of the business problem, but you also need a simpler way to put those things together because increasingly these processes and activities are not siloed, they become in service to customer and they have to be integrated so the tooling has to facilitate integration and that's the platform value. Have I got that right, is that kind of the direction that Ushur's taking? >> Yes and the way we do that is, we have orchestration platform, we call it a Zero code builder. It's a flow builder and that flow builder basically enables business teams to very quickly orchestrate their entire process flow. And then you marry this or couple this into your existing systems of records whether they are standard platforms for customer service management or IT service management or HR management or vendor management. You plug this in, into your existing system of records they could be standard platforms or they could be proprietary home grown platforms. Irrespective of what you have in your existing back office we can plug Ushur into any of these platforms rather instantaneously. >> So you're templates for integration as well6 as templates for outcomes? >> Absolutely, absolutely. And what's exciting about these technologies is the fact you can actually demonstrate KPI's of 10x, or more, within the first 6 months to a year of deploying this. We are not talking about, you know, 30 % cost optimization, or improvements that like 2x, 3x, which was typically what RPA companies have demonstrated. >> Those are good numbers. >> Yeah, so not that they are, you know. But we are interested in transformational KPI's transformational experiences for enterprise companies and I don't want to touch any automation opportunity if it does not lead to companies either making a huge saving or making significant improvements in their top line. >> Well, so I want to talk to you about that,6 because I think this is a very important point. I was talking over a CIO client a couple week6s ago and he said something very interesting to me, 6you know, he said everybody talks about Shadow IT, the way that his business is now thinking about what used to be Shadow IT is now becoming IT and that central IT organization is becoming the shadow. And the rationale that they were using is that the function or business unit IT groups were becoming more associated with revenue in digital business, whereas that centralized IT group were main, mainly focused on cost. How is AI becoming part of that revenue generation side via IT as you get closer to those outcomes? >> Yeah so, AI again is technology- >> It can be both. >> Right, so when you take an automation approach you can apply this for a broad set of use cases, right. All the way from prospecting to servicing your customer onboarding the customer, servicing the customer retaining the customer, upselling and cross selling. So when you take sales enablement and you apply these cross selling, upselling opportunities with the platform they naturally give you a significant uptake in terms of, you know, going after your top line revenues. You're able to service your opportunities a lot faster. So for example an insurance company if it can reduce that core intake process from two weeks down to an hour it puts them in a better position to go and win that deal. Just by virtue of the fact that you're getting their work done faster. >> Customer sees value in the speed, share holders see value in the efficiency. >> Absolutely. >> Excellent. So any last thoughts, where you think you're going to be in a year? >> Oh we're just getting started. I've been at this for five years now and I think the space is incredibly hard, there's a lot of hype about AI. So part of my job is to educate customers and what is possible and what is not possible. So we feel like we're just getting started. Like, just like how 20 years back Cloud, you know, was a big deal and we are still hearing companies talk about Cloud and transforming their workflows into the Cloud. We believe that automation is an exciting phase and we are on the right side of where the industries eventually are going. The possibilities of applying transfer learning, supervised learning from what we have done in the computer vision world to linguistics is very promising. The types of problems that we are basically solving are phenomenal. The KPI's that we can impact are very very exciting. So I think if I look at this as a three to five year roadmap of where Ushur is, I want put Ushur on the global map in terms of being able to take any workflow or take any work that goes on in the back office, off an enterprise and how they service their, all their stakeholders. Whether they are employees, customers, partners, vendors and impact that through a combination of micro service and micro engagement which is part of our secret sauce. >> Excellent. Simha Sadasiva is the CEO of Ushur. We've been talking about the evolving role of AI and some of the new tooling as business try to move from an orientation of understanding to tooling, to experienced outcomes. Simha thank you very much for being on theCUBE. >> Thanks Peter, thanks, good talking to you. >> And once again I'm Peter Burris, and this has been CUBE Conversation. Until next time. (lively music)