 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 standpoint of what it can do but also from a standpoint 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, methodological and other considerations. That's what we're gonna talk about today is 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 Sarasava who's the CEO of Usher with us here in the CUBE. Simha, welcome to the CUBE. Thank you, thanks, good to be here. So, give us a quick update, let's start. What is Usher? Usher is a broad platform to automate a number of different workflows for enterprise companies. So I started this a little 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 problems that they were actually looking to solve, it was apparent to me that the more business processes you attach in addition 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. All right, but let's 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 a particularly successful development team or successful choice of a tool or something else. What is the problem? As you talk to customers, how would you 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 it's in vogue in every major enterprise company that you talk to. Everyone is worried about how do they, number one, stay an 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're interacting with your friends and family in a social circle. So there are lots of moving parts here. Well, let me stop you there because 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 its work, its workflows, its tasks, its organization, its value proposition and how it engages customers around what it regards as its most important assets. To us the very notion of the difference between business and digital business is a 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 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, 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. The reconstituting work. Absolutely, you're redefining how work was done. How do you onboard employees, customers, partners from legacy forms to newer forms of engagement, newer forms of record keeping. And once they become digital, then you understand, know and can serve those, 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, those engagements or 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, cause a thought just popped in my mind 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 that they performed. And then we ended up with things like RPA, process automation, whatnot, where we took a given set of tasks that happened on a screen because 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 greater productivity. AI seems different though, right? Because AI is not just doing things against a recipe. It's also inferencing. It's trying to, I hate the word understand, but it's trying to mimic at least 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. 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 you evolve that from an automation perspective, 15 years back you had a lot of companies that started with 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, discern, understand information, understand objects, understand images, understand language in ways and means that were not possible previously. Computing the access to big databases, big data handling technologies, 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. So for example, we can take a code intake process in an insurance company, something that would take two weeks for an insurance company to respond back to a code request because they have to look and assess the risks involved with that application process. Now, if you feed an engine like ushers with information that were made previously that ascertained whether this was adjudicated to be accepted or rejected from a risk perspective, now we can actually 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. Look, I talked 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. No, nothing wrong with that. Everybody's struggling to try to do this better. You're taking a platform approach. So when I think of a 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's an enormous number of steps in between. 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 of software startups in my career. And one of the things that I've learned, 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 a template approach or a use case approach. While our platform is extremely broad when we are talking to an insurance company versus a healthcare company versus a technology company, you have to show specific applications of how you can actually take this platform and use that platform for, let's say, automating the intake process in an insurance world or the claims process in an insurance world or an IT service management automation for a technology company or a prescription refill for a healthcare company. So these are all specific and definitive use cases that we have templatized. And 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 quick and rapid. But those use cases or those templates have historically been relatively rigid. And that's been one of the challenges that a lot of companies have had is how do I fit these together? The integration work historically has been very difficult. So what I think I hear you say is that, yeah, you need to be able to have artifacts and constructs that make sense in the context of the business problem which also need a simpler way to put those things together because increasingly these processes and activities are not siloed. They become in service to a 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 usher's taking? Yes, and the way we do that is we have an orchestration platform. We call it as 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 systems of records. They could be standard platforms or they could be proprietary homegrown platforms. Irrespective of what you have in your existing back office we can plug usher into any of these platforms rather instantaneously. So you've got templates for integration as well as templates for outcomes. Absolutely, absolutely. And what's exciting about these technologies is the fact that you can actually demonstrate KPIs of 10x or more within the first six months to a year of deploying this. You are not talking about 30% cost optimization or improvements that are like 2x, 3x which was typically what RPA companies have demonstrated. Yeah, those are good numbers. Yeah, so not that they are, but we are interested in transformational KPIs, 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 because I think this is a very important point. I was talking over our CIO clients a couple of weeks ago and he said something very interesting to me. He said everybody talks about shadow IT. The way that his business is now thinking about it, 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 remained mainly focused on cost. How is AI becoming part of that revenue generation side of IT as you get closer to those outcomes? Yeah, so AI again is technology. So when you take an automation approach, you can apply this for a broad set of use cases. All the way from prospecting to servicing your customer, onboarding that customer, servicing that customer, retaining that customer and 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 going after your top line revenues. You're able to service your opportunities a lot faster. So for example, for an insurance company, if you can reduce that quote intake process from two weeks down to an hour, it puts them in a better position to actually 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, shareholder sees value in the efficiency. Absolutely, absolutely, absolutely. All right, so any last thoughts? Where do 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 hot. There's a lot of hype about AI and so part of my job is to educate customers on what is possible and what is not possible. We feel that we're just getting started. Like just like how 20 years back, cloud was a big deal and then we are still hearing companies talk about cloud and transforming into their workflows into the cloud. We believe that automation is an exciting phase and we are on the right side of where the industry is eventually 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 KPIs that we can impact are very, very exciting. I think if I look at this as a three to five year roadmap of where Asher is, I want to put Asher on the global map in terms of being able to take any workflow, take any work that goes on in the back office of an enterprise and how they service all their stakeholders whether they are employees, customers, partners, vendors and impact that through a combination of microservice and micro-engagement which is part of our secret sauce. Excellent. Simha Sarisava is the CEO of Asher. We've been talking about the evolving role of AI and some of the new tooling as businesses try to move from an orientation of understanding, to tooling, to experienced outcomes. Simha, thanks very much for being on the queue. Thanks Peter, thanks for talking to you. And once again, I'm Peter Burris and this has been a CUBE Conversation. Until next time.