(upbeat music beginning) >> From the Cube Studios in Palo Alto and Boston, bringing you data-driven insights from the Cube and ETR, this is "Breaking Analysis" with Dave Vellante. >> Making predictions about the future of enterprise tech is more challenging if you strive to lay down forecasts that are measurable. In other words, if you make a prediction, you should be able to look back a year later and say, with some degree of certainty, whether the prediction came true or not, with evidence to back that up. Hello and welcome to this week's Wikibon Cube Insights, powered by ETR. In this breaking analysis, we aim to do just that, with predictions about the macro IT spending environment, cost optimization, security, lots to talk about there, generative AI, cloud, and of course supercloud, blockchain adoption, data platforms, including commentary on Databricks, snowflake, and other key players, automation, events, and we may even have some bonus predictions around quantum computing, and perhaps some other areas. To make all this happen, we welcome back, for the third year in a row, my colleague and friend Eric Bradley from ETR. Eric, thanks for all you do for the community, and thanks for being part of this program. Again. >> I wouldn't miss it for the world. I always enjoy this one. Dave, good to see you. >> Yeah, so let me bring up this next slide and show you, actually come back to me if you would. I got to show the audience this. These are the inbounds that we got from PR firms starting in October around predictions. They know we do prediction posts. And so they'll send literally thousands and thousands of predictions from hundreds of experts in the industry, technologists, consultants, et cetera. And if you bring up the slide I can show you sort of the pattern that developed here. 40% of these thousands of predictions were from cyber. You had AI and data. If you combine those, it's still not close to cyber. Cost optimization was a big thing. Of course, cloud, some on DevOps, and software. Digital... Digital transformation got, you know, some lip service and SaaS. And then there was other, it's kind of around 2%. So quite remarkable, when you think about the focus on cyber, Eric. >> Yeah, there's two reasons why I think it makes sense, though. One, the cybersecurity companies have a lot of cash, so therefore the PR firms might be working a little bit harder for them than some of their other clients. (laughs) And then secondly, as you know, for multiple years now, when we do our macro survey, we ask, "What's your number one spending priority?" And again, it's security. It just isn't going anywhere. It just stays at the top. So I'm actually not that surprised by that little pie chart there, but I was shocked that SaaS was only 5%. You know, going back 10 years ago, that would've been the only thing anyone was talking about. >> Yeah. So true. All right, let's get into it. First prediction, we always start with kind of tech spending. Number one is tech spending increases between four and 5%. ETR has currently got it at 4.6% coming into 2023. This has been a consistently downward trend all year. We started, you know, much, much higher as we've been reporting. Bottom line is the fed is still in control. They're going to ease up on tightening, is the expectation, they're going to shoot for a soft landing. But you know, my feeling is this slingshot economy is going to continue, and it's going to continue to confound, whether it's supply chains or spending. The, the interesting thing about the ETR data, Eric, and I want you to comment on this, the largest companies are the most aggressive to cut. They're laying off, smaller firms are spending faster. They're actually growing at a much larger, faster rate as are companies in EMEA. And that's a surprise. That's outpacing the US and APAC. Chime in on this, Eric. >> Yeah, I was surprised on all of that. First on the higher level spending, we are definitely seeing it coming down, but the interesting thing here is headlines are making it worse. The huge research shop recently said 0% growth. We're coming in at 4.6%. And just so everyone knows, this is not us guessing, we asked 1,525 IT decision-makers what their budget growth will be, and they came in at 4.6%. Now there's a huge disparity, as you mentioned. The Fortune 500, global 2000, barely at 2% growth, but small, it's at 7%. So we're at a situation right now where the smaller companies are still playing a little bit of catch up on digital transformation, and they're spending money. The largest companies that have the most to lose from a recession are being more trepidatious, obviously. So they're playing a "Wait and see." And I hope we don't talk ourselves into a recession. Certainly the headlines and some of their research shops are helping it along. But another interesting comment here is, you know, energy and utilities used to be called an orphan and widow stock group, right? They are spending more than anyone, more than financials insurance, more than retail consumer. So right now it's being driven by mid, small, and energy and utilities. They're all spending like gangbusters, like nothing's happening. And it's the rest of everyone else that's being very cautious. >> Yeah, so very unpredictable right now. All right, let's go to number two. Cost optimization remains a major theme in 2023. We've been reporting on this. You've, we've shown a chart here. What's the primary method that your organization plans to use? You asked this question of those individuals that cited that they were going to reduce their spend and- >> Mhm. >> consolidating redundant vendors, you know, still leads the way, you know, far behind, cloud optimization is second, but it, but cloud continues to outpace legacy on-prem spending, no doubt. Somebody, it was, the guy's name was Alexander Feiglstorfer from Storyblok, sent in a prediction, said "All in one becomes extinct." Now, generally I would say I disagree with that because, you know, as we know over the years, suites tend to win out over, you know, individual, you know, point products. But I think what's going to happen is all in one is going to remain the norm for these larger companies that are cutting back. They want to consolidate redundant vendors, and the smaller companies are going to stick with that best of breed and be more aggressive and try to compete more effectively. What's your take on that? >> Yeah, I'm seeing much more consolidation in vendors, but also consolidation in functionality. We're seeing people building out new functionality, whether it's, we're going to talk about this later, so I don't want to steal too much of our thunder right now, but data and security also, we're seeing a functionality creep. So I think there's further consolidation happening here. I think niche solutions are going to be less likely, and platform solutions are going to be more likely in a spending environment where you want to reduce your vendors. You want to have one bill to pay, not 10. Another thing on this slide, real quick if I can before I move on, is we had a bunch of people write in and some of the answer options that aren't on this graph but did get cited a lot, unfortunately, is the obvious reduction in staff, hiring freezes, and delaying hardware, were three of the top write-ins. And another one was offshore outsourcing. So in addition to what we're seeing here, there were a lot of write-in options, and I just thought it would be important to state that, but essentially the cost optimization is by and far the highest one, and it's growing. So it's actually increased in our citations over the last year. >> And yeah, specifically consolidating redundant vendors. And so I actually thank you for bringing that other up, 'cause I had asked you, Eric, is there any evidence that repatriation is going on and we don't see it in the numbers, we don't see it even in the other, there was, I think very little or no mention of cloud repatriation, even though it might be happening in this in a smattering. >> Not a single mention, not one single mention. I went through it for you. Yep. Not one write-in. >> All right, let's move on. Number three, security leads M&A in 2023. Now you might say, "Oh, well that's a layup," but let me set this up Eric, because I didn't really do a great job with the slide. I hid the, what you've done, because you basically took, this is from the emerging technology survey with 1,181 responses from November. And what we did is we took Palo Alto and looked at the overlap in Palo Alto Networks accounts with these vendors that were showing on this chart. And Eric, I'm going to ask you to explain why we put a circle around OneTrust, but let me just set it up, and then have you comment on the slide and take, give us more detail. We're seeing private company valuations are off, you know, 10 to 40%. We saw a sneak, do a down round, but pretty good actually only down 12%. We've seen much higher down rounds. Palo Alto Networks we think is going to get busy. Again, they're an inquisitive company, they've been sort of quiet lately, and we think CrowdStrike, Cisco, Microsoft, Zscaler, we're predicting all of those will make some acquisitions and we're thinking that the targets are somewhere in this mess of security taxonomy. Other thing we're predicting AI meets cyber big time in 2023, we're going to probably going to see some acquisitions of those companies that are leaning into AI. We've seen some of that with Palo Alto. And then, you know, your comment to me, Eric, was "The RSA conference is going to be insane, hopping mad, "crazy this April," (Eric laughing) but give us your take on this data, and why the red circle around OneTrust? Take us back to that slide if you would, Alex. >> Sure. There's a few things here. First, let me explain what we're looking at. So because we separate the public companies and the private companies into two separate surveys, this allows us the ability to cross-reference that data. So what we're doing here is in our public survey, the tesis, everyone who cited some spending with Palo Alto, meaning they're a Palo Alto customer, we then cross-reference that with the private tech companies. Who also are they spending with? So what you're seeing here is an overlap. These companies that we have circled are doing the best in Palo Alto's accounts. Now, Palo Alto went and bought Twistlock a few years ago, which this data slide predicted, to be quite honest. And so I don't know if they necessarily are going to go after Snyk. Snyk, sorry. They already have something in that space. What they do need, however, is more on the authentication space. So I'm looking at OneTrust, with a 45% overlap in their overall net sentiment. That is a company that's already existing in their accounts and could be very synergistic to them. BeyondTrust as well, authentication identity. This is something that Palo needs to do to move more down that zero trust path. Now why did I pick Palo first? Because usually they're very inquisitive. They've been a little quiet lately. Secondly, if you look at the backdrop in the markets, the IPO freeze isn't going to last forever. Sooner or later, the IPO markets are going to open up, and some of these private companies are going to tap into public equity. In the meantime, however, cash funding on the private side is drying up. If they need another round, they're not going to get it, and they're certainly not going to get it at the valuations they were getting. So we're seeing valuations maybe come down where they're a touch more attractive, and Palo knows this isn't going to last forever. Cisco knows that, CrowdStrike, Zscaler, all these companies that are trying to make a push to become that vendor that you're consolidating in, around, they have a chance now, they have a window where they need to go make some acquisitions. And that's why I believe leading up to RSA, we're going to see some movement. I think it's going to pretty, a really exciting time in security right now. >> Awesome. Thank you. Great explanation. All right, let's go on the next one. Number four is, it relates to security. Let's stay there. Zero trust moves from hype to reality in 2023. Now again, you might say, "Oh yeah, that's a layup." A lot of these inbounds that we got are very, you know, kind of self-serving, but we always try to put some meat in the bone. So first thing we do is we pull out some commentary from, Eric, your roundtable, your insights roundtable. And we have a CISO from a global hospitality firm says, "For me that's the highest priority." He's talking about zero trust because it's the best ROI, it's the most forward-looking, and it enables a lot of the business transformation activities that we want to do. CISOs tell me that they actually can drive forward transformation projects that have zero trust, and because they can accelerate them, because they don't have to go through the hurdle of, you know, getting, making sure that it's secure. Second comment, zero trust closes that last mile where once you're authenticated, they open up the resource to you in a zero trust way. That's a CISO of a, and a managing director of a cyber risk services enterprise. Your thoughts on this? >> I can be here all day, so I'm going to try to be quick on this one. This is not a fluff piece on this one. There's a couple of other reasons this is happening. One, the board finally gets it. Zero trust at first was just a marketing hype term. Now the board understands it, and that's why CISOs are able to push through it. And what they finally did was redefine what it means. Zero trust simply means moving away from hardware security, moving towards software-defined security, with authentication as its base. The board finally gets that, and now they understand that this is necessary and it's being moved forward. The other reason it's happening now is hybrid work is here to stay. We weren't really sure at first, large companies were still trying to push people back to the office, and it's going to happen. The pendulum will swing back, but hybrid work's not going anywhere. By basically on our own data, we're seeing that 69% of companies expect remote and hybrid to be permanent, with only 30% permanent in office. Zero trust works for a hybrid environment. So all of that is the reason why this is happening right now. And going back to our previous prediction, this is why we're picking Palo, this is why we're picking Zscaler to make these acquisitions. Palo Alto needs to be better on the authentication side, and so does Zscaler. They're both fantastic on zero trust network access, but they need the authentication software defined aspect, and that's why we think this is going to happen. One last thing, in that CISO round table, I also had somebody say, "Listen, Zscaler is incredible. "They're doing incredibly well pervading the enterprise, "but their pricing's getting a little high," and they actually think Palo Alto is well-suited to start taking some of that share, if Palo can make one move. >> Yeah, Palo Alto's consolidation story is very strong. Here's my question and challenge. Do you and me, so I'm always hardcore about, okay, you've got to have evidence. I want to look back at these things a year from now and say, "Did we get it right? Yes or no?" If we got it wrong, we'll tell you we got it wrong. So how are we going to measure this? I'd say a couple things, and you can chime in. One is just the number of vendors talking about it. That's, but the marketing always leads the reality. So the second part of that is we got to get evidence from the buying community. Can you help us with that? >> (laughs) Luckily, that's what I do. I have a data company that asks thousands of IT decision-makers what they're adopting and what they're increasing spend on, as well as what they're decreasing spend on and what they're replacing. So I have snapshots in time over the last 11 years where I can go ahead and compare and contrast whether this adoption is happening or not. So come back to me in 12 months and I'll let you know. >> Now, you know, I will. Okay, let's bring up the next one. Number five, generative AI hits where the Metaverse missed. Of course everybody's talking about ChatGPT, we just wrote last week in a breaking analysis with John Furrier and Sarjeet Joha our take on that. We think 2023 does mark a pivot point as natural language processing really infiltrates enterprise tech just as Amazon turned the data center into an API. We think going forward, you're going to be interacting with technology through natural language, through English commands or other, you know, foreign language commands, and investors are lining up, all the VCs are getting excited about creating something competitive to ChatGPT, according to (indistinct) a hundred million dollars gets you a seat at the table, gets you into the game. (laughing) That's before you have to start doing promotion. But he thinks that's what it takes to actually create a clone or something equivalent. We've seen stuff from, you know, the head of Facebook's, you know, AI saying, "Oh, it's really not that sophisticated, ChatGPT, "it's kind of like IBM Watson, it's great engineering, "but you know, we've got more advanced technology." We know Google's working on some really interesting stuff. But here's the thing. ETR just launched this survey for the February survey. It's in the field now. We circle open AI in this category. They weren't even in the survey, Eric, last quarter. So 52% of the ETR survey respondents indicated a positive sentiment toward open AI. I added up all the sort of different bars, we could double click on that. And then I got this inbound from Scott Stevenson of Deep Graham. He said "AI is recession-proof." I don't know if that's the case, but it's a good quote. So bring this back up and take us through this. Explain this chart for us, if you would. >> First of all, I like Scott's quote better than the Facebook one. I think that's some sour grapes. Meta just spent an insane amount of money on the Metaverse and that's a dud. Microsoft just spent money on open AI and it is hot, undoubtedly hot. We've only been in the field with our current ETS survey for a week. So my caveat is it's preliminary data, but I don't care if it's preliminary data. (laughing) We're getting a sneak peek here at what is the number one net sentiment and mindshare leader in the entire machine-learning AI sector within a week. It's beating Data- >> 600. 600 in. >> It's beating Databricks. And we all know Databricks is a huge established enterprise company, not only in machine-learning AI, but it's in the top 10 in the entire survey. We have over 400 vendors in this survey. It's number eight overall, already. In a week. This is not hype. This is real. And I could go on the NLP stuff for a while. Not only here are we seeing it in open AI and machine-learning and AI, but we're seeing NLP in security. It's huge in email security. It's completely transforming that area. It's one of the reasons I thought Palo might take Abnormal out. They're doing such a great job with NLP in this email side, and also in the data prep tools. NLP is going to take out data prep tools. If we have time, I'll discuss that later. But yeah, this is, to me this is a no-brainer, and we're already seeing it in the data. >> Yeah, John Furrier called, you know, the ChatGPT introduction. He said it reminded him of the Netscape moment, when we all first saw Netscape Navigator and went, "Wow, it really could be transformative." All right, number six, the cloud expands to supercloud as edge computing accelerates and CloudFlare is a big winner in 2023. We've reported obviously on cloud, multi-cloud, supercloud and CloudFlare, basically saying what multi-cloud should have been. We pulled this quote from Atif Kahn, who is the founder and CTO of Alkira, thanks, one of the inbounds, thank you. "In 2023, highly distributed IT environments "will become more the norm "as organizations increasingly deploy hybrid cloud, "multi-cloud and edge settings..." Eric, from one of your round tables, "If my sources from edge computing are coming "from the cloud, that means I have my workloads "running in the cloud. "There is no one better than CloudFlare," That's a senior director of IT architecture at a huge financial firm. And then your analysis shows CloudFlare really growing in pervasion, that sort of market presence in the dataset, dramatically, to near 20%, leading, I think you had told me that they're even ahead of Google Cloud in terms of momentum right now. >> That was probably the biggest shock to me in our January 2023 tesis, which covers the public companies in the cloud computing sector. CloudFlare has now overtaken GCP in overall spending, and I was shocked by that. It's already extremely pervasive in networking, of course, for the edge networking side, and also in security. This is the number one leader in SaaSi, web access firewall, DDoS, bot protection, by your definition of supercloud, which we just did a couple of weeks ago, and I really enjoyed that by the way Dave, I think CloudFlare is the one that fits your definition best, because it's bringing all of these aspects together, and most importantly, it's cloud agnostic. It does not need to rely on Azure or AWS to do this. It has its own cloud. So I just think it's, when we look at your definition of supercloud, CloudFlare is the poster child. >> You know, what's interesting about that too, is a lot of people are poo-pooing CloudFlare, "Ah, it's, you know, really kind of not that sophisticated." "You don't have as many tools," but to your point, you're can have those tools in the cloud, Cloudflare's doing serverless on steroids, trying to keep things really simple, doing a phenomenal job at, you know, various locations around the world. And they're definitely one to watch. Somebody put them on my radar (laughing) a while ago and said, "Dave, you got to do a breaking analysis on CloudFlare." And so I want to thank that person. I can't really name them, 'cause they work inside of a giant hyperscaler. But- (Eric laughing) (Dave chuckling) >> Real quickly, if I can from a competitive perspective too, who else is there? They've already taken share from Akamai, and Fastly is their really only other direct comp, and they're not there. And these guys are in poll position and they're the only game in town right now. I just, I don't see it slowing down. >> I thought one of your comments from your roundtable I was reading, one of the folks said, you know, CloudFlare, if my workloads are in the cloud, they are, you know, dominant, they said not as strong with on-prem. And so Akamai is doing better there. I'm like, "Okay, where would you want to be?" (laughing) >> Yeah, which one of those two would you rather be? >> Right? Anyway, all right, let's move on. Number seven, blockchain continues to look for a home in the enterprise, but devs will slowly begin to adopt in 2023. You know, blockchains have got a lot of buzz, obviously crypto is, you know, the killer app for blockchain. Senior IT architect in financial services from your, one of your insight roundtables said quote, "For enterprises to adopt a new technology, "there have to be proven turnkey solutions. "My experience in talking with my peers are, "blockchain is still an open-source component "where you have to build around it." Now I want to thank Ravi Mayuram, who's the CTO of Couchbase sent in, you know, one of the predictions, he said, "DevOps will adopt blockchain, specifically Ethereum." And he referenced actually in his email to me, Solidity, which is the programming language for Ethereum, "will be in every DevOps pro's playbook, "mirroring the boom in machine-learning. "Newer programming languages like Solidity "will enter the toolkits of devs." His point there, you know, Solidity for those of you don't know, you know, Bitcoin is not programmable. Solidity, you know, came out and that was their whole shtick, and they've been improving that, and so forth. But it, Eric, it's true, it really hasn't found its home despite, you know, the potential for smart contracts. IBM's pushing it, VMware has had announcements, and others, really hasn't found its way in the enterprise yet. >> Yeah, and I got to be honest, I don't think it's going to, either. So when we did our top trends series, this was basically chosen as an anti-prediction, I would guess, that it just continues to not gain hold. And the reason why was that first comment, right? It's very much a niche solution that requires a ton of custom work around it. You can't just plug and play it. And at the end of the day, let's be very real what this technology is, it's a database ledger, and we already have database ledgers in the enterprise. So why is this a priority to move to a different database ledger? It's going to be very niche cases. I like the CTO comment from Couchbase about it being adopted by DevOps. I agree with that, but it has to be a DevOps in a very specific use case, and a very sophisticated use case in financial services, most likely. And that's not across the entire enterprise. So I just think it's still going to struggle to get its foothold for a little bit longer, if ever. >> Great, thanks. Okay, let's move on. Number eight, AWS Databricks, Google Snowflake lead the data charge with Microsoft. Keeping it simple. So let's unpack this a little bit. This is the shared accounts peer position for, I pulled data platforms in for analytics, machine-learning and AI and database. So I could grab all these accounts or these vendors and see how they compare in those three sectors. Analytics, machine-learning and database. Snowflake and Databricks, you know, they're on a crash course, as you and I have talked about. They're battling to be the single source of truth in analytics. They're, there's going to be a big focus. They're already started. It's going to be accelerated in 2023 on open formats. Iceberg, Python, you know, they're all the rage. We heard about Iceberg at Snowflake Summit, last summer or last June. Not a lot of people had heard of it, but of course the Databricks crowd, who knows it well. A lot of other open source tooling. There's a company called DBT Labs, which you're going to talk about in a minute. George Gilbert put them on our radar. We just had Tristan Handy, the CEO of DBT labs, on at supercloud last week. They are a new disruptor in data that's, they're essentially making, they're API-ifying, if you will, KPIs inside the data warehouse and dramatically simplifying that whole data pipeline. So really, you know, the ETL guys should be shaking in their boots with them. Coming back to the slide. Google really remains focused on BigQuery adoption. Customers have complained to me that they would like to use Snowflake with Google's AI tools, but they're being forced to go to BigQuery. I got to ask Google about that. AWS continues to stitch together its bespoke data stores, that's gone down that "Right tool for the right job" path. David Foyer two years ago said, "AWS absolutely is going to have to solve that problem." We saw them start to do it in, at Reinvent, bringing together NoETL between Aurora and Redshift, and really trying to simplify those worlds. There's going to be more of that. And then Microsoft, they're just making it cheap and easy to use their stuff, you know, despite some of the complaints that we hear in the community, you know, about things like Cosmos, but Eric, your take? >> Yeah, my concern here is that Snowflake and Databricks are fighting each other, and it's allowing AWS and Microsoft to kind of catch up against them, and I don't know if that's the right move for either of those two companies individually, Azure and AWS are building out functionality. Are they as good? No they're not. The other thing to remember too is that AWS and Azure get paid anyway, because both Databricks and Snowflake run on top of 'em. So (laughing) they're basically collecting their toll, while these two fight it out with each other, and they build out functionality. I think they need to stop focusing on each other, a little bit, and think about the overall strategy. Now for Databricks, we know they came out first as a machine-learning AI tool. They were known better for that spot, and now they're really trying to play catch-up on that data storage compute spot, and inversely for Snowflake, they were killing it with the compute separation from storage, and now they're trying to get into the MLAI spot. I actually wouldn't be surprised to see them make some sort of acquisition. Frank Slootman has been a little bit quiet, in my opinion there. The other thing to mention is your comment about DBT Labs. If we look at our emerging technology survey, last survey when this came out, DBT labs, number one leader in that data integration space, I'm going to just pull it up real quickly. It looks like they had a 33% overall net sentiment to lead data analytics integration. So they are clearly growing, it's fourth straight survey consecutively that they've grown. The other name we're seeing there a little bit is Cribl, but DBT labs is by far the number one player in this space. >> All right. Okay, cool. Moving on, let's go to number nine. With Automation mixer resurgence in 2023, we're showing again data. The x axis is overlap or presence in the dataset, and the vertical axis is shared net score. Net score is a measure of spending momentum. As always, you've seen UI path and Microsoft Power Automate up until the right, that red line, that 40% line is generally considered elevated. UI path is really separating, creating some distance from Automation Anywhere, they, you know, previous quarters they were much closer. Microsoft Power Automate came on the scene in a big way, they loom large with this "Good enough" approach. I will say this, I, somebody sent me a results of a (indistinct) survey, which showed UiPath actually had more mentions than Power Automate, which was surprising, but I think that's not been the case in the ETR data set. We're definitely seeing a shift from back office to front soft office kind of workloads. Having said that, software testing is emerging as a mainstream use case, we're seeing ML and AI become embedded in end-to-end automations, and low-code is serving the line of business. And so this, we think, is going to increasingly have appeal to organizations in the coming year, who want to automate as much as possible and not necessarily, we've seen a lot of layoffs in tech, and people... You're going to have to fill the gaps with automation. That's a trend that's going to continue. >> Yep, agreed. At first that comment about Microsoft Power Automate having less citations than UiPath, that's shocking to me. I'm looking at my chart right here where Microsoft Power Automate was cited by over 60% of our entire survey takers, and UiPath at around 38%. Now don't get me wrong, 38% pervasion's fantastic, but you know you're not going to beat an entrenched Microsoft. So I don't really know where that comment came from. So UiPath, looking at it alone, it's doing incredibly well. It had a huge rebound in its net score this last survey. It had dropped going through the back half of 2022, but we saw a big spike in the last one. So it's got a net score of over 55%. A lot of people citing adoption and increasing. So that's really what you want to see for a name like this. The problem is that just Microsoft is doing its playbook. At the end of the day, I'm going to do a POC, why am I going to pay more for UiPath, or even take on another separate bill, when we know everyone's consolidating vendors, if my license already includes Microsoft Power Automate? It might not be perfect, it might not be as good, but what I'm hearing all the time is it's good enough, and I really don't want another invoice. >> Right. So how does UiPath, you know, and Automation Anywhere, how do they compete with that? Well, the way they compete with it is they got to have a better product. They got a product that's 10 times better. You know, they- >> Right. >> they're not going to compete based on where the lowest cost, Microsoft's got that locked up, or where the easiest to, you know, Microsoft basically give it away for free, and that's their playbook. So that's, you know, up to UiPath. UiPath brought on Rob Ensslin, I've interviewed him. Very, very capable individual, is now Co-CEO. So he's kind of bringing that adult supervision in, and really tightening up the go to market. So, you know, we know this company has been a rocket ship, and so getting some control on that and really getting focused like a laser, you know, could be good things ahead there for that company. Okay. >> One of the problems, if I could real quick Dave, is what the use cases are. When we first came out with RPA, everyone was super excited about like, "No, UiPath is going to be great for super powerful "projects, use cases." That's not what RPA is being used for. As you mentioned, it's being used for mundane tasks, so it's not automating complex things, which I think UiPath was built for. So if you were going to get UiPath, and choose that over Microsoft, it's going to be 'cause you're doing it for more powerful use case, where it is better. But the problem is that's not where the enterprise is using it. The enterprise are using this for base rote tasks, and simply, Microsoft Power Automate can do that. >> Yeah, it's interesting. I've had people on theCube that are both Microsoft Power Automate customers and UiPath customers, and I've asked them, "Well you know, "how do you differentiate between the two?" And they've said to me, "Look, our users and personal productivity users, "they like Power Automate, "they can use it themselves, and you know, "it doesn't take a lot of, you know, support on our end." The flip side is you could do that with UiPath, but like you said, there's more of a focus now on end-to-end enterprise automation and building out those capabilities. So it's increasingly a value play, and that's going to be obviously the challenge going forward. Okay, my last one, and then I think you've got some bonus ones. Number 10, hybrid events are the new category. Look it, if I can get a thousand inbounds that are largely self-serving, I can do my own here, 'cause we're in the events business. (Eric chuckling) Here's the prediction though, and this is a trend we're seeing, the number of physical events is going to dramatically increase. That might surprise people, but most of the big giant events are going to get smaller. The exception is AWS with Reinvent, I think Snowflake's going to continue to grow. So there are examples of physical events that are growing, but generally, most of the big ones are getting smaller, and there's going to be many more smaller intimate regional events and road shows. These micro-events, they're going to be stitched together. Digital is becoming a first class citizen, so people really got to get their digital acts together, and brands are prioritizing earned media, and they're beginning to build their own news networks, going direct to their customers. And so that's a trend we see, and I, you know, we're right in the middle of it, Eric, so you know we're going to, you mentioned RSA, I think that's perhaps going to be one of those crazy ones that continues to grow. It's shrunk, and then it, you know, 'cause last year- >> Yeah, it did shrink. >> right, it was the last one before the pandemic, and then they sort of made another run at it last year. It was smaller but it was very vibrant, and I think this year's going to be huge. Global World Congress is another one, we're going to be there end of Feb. That's obviously a big big show, but in general, the brands and the technology vendors, even Oracle is going to scale down. I don't know about Salesforce. We'll see. You had a couple of bonus predictions. Quantum and maybe some others? Bring us home. >> Yeah, sure. I got a few more. I think we touched upon one, but I definitely think the data prep tools are facing extinction, unfortunately, you know, the Talons Informatica is some of those names. The problem there is that the BI tools are kind of including data prep into it already. You know, an example of that is Tableau Prep Builder, and then in addition, Advanced NLP is being worked in as well. ThoughtSpot, Intelius, both often say that as their selling point, Tableau has Ask Data, Click has Insight Bot, so you don't have to really be intelligent on data prep anymore. A regular business user can just self-query, using either the search bar, or even just speaking into what it needs, and these tools are kind of doing the data prep for it. I don't think that's a, you know, an out in left field type of prediction, but it's the time is nigh. The other one I would also state is that I think knowledge graphs are going to break through this year. Neo4j in our survey is growing in pervasion in Mindshare. So more and more people are citing it, AWS Neptune's getting its act together, and we're seeing that spending intentions are growing there. Tiger Graph is also growing in our survey sample. I just think that the time is now for knowledge graphs to break through, and if I had to do one more, I'd say real-time streaming analytics moves from the very, very rich big enterprises to downstream, to more people are actually going to be moving towards real-time streaming, again, because the data prep tools and the data pipelines have gotten easier to use, and I think the ROI on real-time streaming is obviously there. So those are three that didn't make the cut, but I thought deserved an honorable mention. >> Yeah, I'm glad you did. Several weeks ago, we did an analyst prediction roundtable, if you will, a cube session power panel with a number of data analysts and that, you know, streaming, real-time streaming was top of mind. So glad you brought that up. Eric, as always, thank you very much. I appreciate the time you put in beforehand. I know it's been crazy, because you guys are wrapping up, you know, the last quarter survey in- >> Been a nuts three weeks for us. (laughing) >> job. I love the fact that you're doing, you know, the ETS survey now, I think it's quarterly now, right? Is that right? >> Yep. >> Yep. So that's phenomenal. >> Four times a year. I'll be happy to jump on with you when we get that done. I know you were really impressed with that last time. >> It's unbelievable. This is so much data at ETR. Okay. Hey, that's a wrap. Thanks again. >> Take care Dave. Good seeing you. >> All right, many thanks to our team here, Alex Myerson as production, he manages the podcast force. Ken Schiffman as well is a critical component of our East Coast studio. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hoof is our editor-in-chief. He's at siliconangle.com. He's just a great editing for us. Thank you all. Remember all these episodes that are available as podcasts, wherever you listen, podcast is doing great. Just search "Breaking analysis podcast." Really appreciate you guys listening. I publish each week on wikibon.com and siliconangle.com, or you can email me directly if you want to get in touch, david.vellante@siliconangle.com. That's how I got all these. I really appreciate it. I went through every single one with a yellow highlighter. It took some time, (laughing) but I appreciate it. You could DM me at dvellante, or comment on our LinkedIn post and please check out etr.ai. Its data is amazing. Best survey data in the enterprise tech business. This is Dave Vellante for theCube Insights, powered by ETR. Thanks for watching, and we'll see you next time on "Breaking Analysis." (upbeat music beginning) (upbeat music ending)

>>The Cube presents UI Path Forward five. Brought to you by UI Path. >>Hi everybody. Welcome back to Las Vegas. You're watching the Cube's coverage of UI Path Forward. Five. We reach cruising altitude on day two. Christina Seacrest is here. She's the process Artificial intelligence and automation GPS automation leader at ey. And Bob PCIs, executive director for Intelligent Automation for the state of Tennessee. Folks, welcome to the cube. Thank you for Adam. >>Good >>To have you. Okay, I don't know if I messed up that title, Christina, but it's kind of interesting. You got process, you got ai, you got automation, you got gps. What's your role? >>I have a lot of rules, so thank you for that. Yeah, so my focus is first and foremost automation. So how do you get things like UI path into our clients, but also I focus specifically in our government and public sector clients. So sled specifically. So state local education. So that's why I'm here with the state of Tennessee. And then we also like to take it beyond automation. So how do you bring an artificial intelligence and all the technologies that come with that. So really full end to end spectrum of >>Automation. So Bob, when you think about the sort of the, the factors that are driving your organization of, how did you describe that, Those sort of external factors that inform your strategy. What, what's, what are the catalysts for how you determine to deploy technology? >>Well, it was primarily that we know tendency has a tendency to provide good customer service, but we want to get to a great status best in class, if you will. And we had an external advisory review where it said, Hey, you know, we could make automation to improve our customer experience. And so that was like a directive of the, the state leaders to go across the board and automate all processes statewide, starting with the 23 executive agencies. >>So where's the focus from that standpoint? Is it on just providing better interfaces to your constituents, your customers? Is it cutting costs or you actually have more budget to invest? Kind of a combination of >>Those? Yeah, so it's, it's really both qualitative and quantitative, right? So quantitative is where we're able to reduce hours and therefore we can redirect people to more less mundane work, if you will. And then qualitative is where we're able to reduce the errors, improve data quality, reduce cycle time for our citizens, you know, when they're making requests, et cetera. So it's, I think it's a combination of both of those quantitative and qualitative metrics that we are mandated in, in micromanaged, quite frankly to, to bring, make those >>Numbers. So I'm from Massachusetts, when I go to a a mass.gov website, I say, all this was done in the 1990s and you could just see where the different stovepipes were, were. But then every now and then you'll hit one and you'll say, Wow, okay, this is up to, it's such a great experience. And then the flip side of that is you want your employees to be happy and not have to do all this mundane work so you can retain the best people. You don't have to. So you're living that in, in state and, and local. So where did you start your automation journey? What role did EY play? Let's go. Yeah, >>Sure. So I, I, I think the thought for process automation was probably three or four years ago, but then we started the program about 18 months ago and there was a lot of, let's say behind the scenes work before we could bring EY in, you know, like what resources was I gonna have in, in the state that were gonna help me address all of the agency simultaneously, right? Cuz normally you'll see a project that'll do be more siloed across the state and say, we're gonna do this agency, we're gonna do this division. Well, you have 40 other agencies that are, you know, the momentum is it's just gonna fall, it wayside. So how we looked at it was let's blanket it and go across all 23 agencies at the same time, you know, identify common processes that are used across 40 divisions, for example, right? >>So, so what we basically did is we procured the software, you know, did the contracts, and then it was really about, I designed, I'm gonna say a multistream approach where they were, we could run multiple work streams, independent define all the architectures, required dev tests, production, the disaster recovery at the same time in parallel developed the center of excellence, the operation model, the processes, methodologies. And the third one was, let's go out to a few divisions, business administration, health, you know, health, human resources, and be able to do a process inventory to see what was there. And then based on that, there's all this theory of well let's do a proof of concept. Let's do a proof of technology, let's do apply. Well, the bottom line is rpa technology's been around for a long time. It's proven there's nothing to prove. But really what was important to prove before we decided to go, you know, full tilt was, you know, develop a proof of perceived business value. >>Are we gonna bring in the, the business value, the hours and the qu qualitative metrics that is expected by our ex executive team, The leadership, we were able to do that, you know, with the help of help of ey, we built out the prototypes and we got the green light to go forward, got ey to start, and then we just basically went pedal to the metal. We had our foundation already defined. We built up the architecture in less than one to two months. Now, in, in a public sector or private sector, it's just not heard of, right? But we have a tendency with EYs technical team, myself, we look around the, the road around the rock instead, the rock in the road, right? So we ended up coming up with a very unique, very easy to easy to handle architecture that was very scalable. And then were able to hit the ground running and deploy in production by December where head of >>Was EY involved in the whole, you know, dev test production, dr. Center of excellence, the, the process inventory or did you bring them in? Did you kind of do that internally then bring EY in for the proof of >>Value? EY was actually awarded the contract for soup to nuts, basically the first phase, which was those four work streams I told you about. And they worked with myself and the state of Tennessee infrastructure architecture teams. We needed to get these things defined and signed off the architecture so we could expedite getting them built out. And then they, and they basically ran all four work streams, you know, the process, inventory, the prototype, the, the proof of perceived business value, the building out the center of excellence, working with myself. And, and this wasn't just us in a, a vacuum, we ended up having to, I mean, I could do the strategy, I could do the technology and I could said the roadmap and all the good stuff, but we had to actually meet with a lot of the state or tendency organizations on change management. How do we end up putting this process or an automation in the middle of the, the normal traditional process, right? So there was a lot of interaction there and getting their feedback and then tweaking our operational model based on feedback from the state of Tennessee. So it was all very collective collaborative. I think that would be the keyword is collaborative and then building out everything. So then, and then we ended up going to the next way where they knew so much and we were, we had such a tight timeframe that we continued with ey. >>So Christina, Bob mentioned center of excellence a couple of times in the state of Tennessee, but then beyond state of Tennessee, other organizations you've worked with in this space, what's the relationship between center of excellence and this thing we've been hearing about over the last couple of days, the citizen developer has that been, has, has, has that been leveraged in the state of Tennessee? Bob, have you seen that leveraged in other places? Christina? What's that relationship look like? >>Yeah, so we don't leverage that, that model yet we have centralized model and there's reasons for that. So we don't end up having maverick's, runoff runoffs have one off, have, you know, have a a UI path version or down this division or have another RPA tool in another division, right? So then all of a sudden we're, we have a maintenance nightmare. Manageability nightmare. So we basically, you know, I I I negotiate an ELA with UI path, so therefore if anyone wants to go do another automation on another division, or they would basically follow our model, our design, our coe, our quality gates. We we're the gatekeepers to bring into production. >>Got it. Now, yeah. Now Christina, what's your perspective? Because I can imagine Nashville and Memphis might have very different ideas about a lot of things. Yeah. Little Tennessee reference there, but what, what, what about what, what about other places are you, are you seeing the citizen developer leveraged in, in some kinds of places more than others or >>What? Yeah. Yeah. And that's part of, because of the foundation we're building. Yeah. So we laid, you know, when, when Bob talks about the first phase of eight weeks, that was amazingly fast, even in that's ridiculous. Spoke about it to say you're gonna lay these four foundations. I was excited, like, I was like, wow, this, this is a very serious client. They wanna go fast and they wanna get that momentum, but the AUM was laid out so we could propel ourselves. So we are at 40 automations right now. We're in the works of creating 80 more automations in this next year. We'll be at 120 really quickly. The AUM is critical. And I will say at a client, I've, I've worked with over 50 clients on automation programs. The way state of Tennessee treats the aom and they abide by it, it is the living document of how you go and go fast. Got it. And the one thing I would say is it's also allowed us to have such immense quality. So I always talk about you put in forward, you put in another 80, we're at 98% uptime on all our automations, meaning they don't go down. And that's because of the AOM we set up. And the natural progression is going to be how do you take it to citizen developer? How do you take it to, we call, you know, process automation plus, >>But methodically, methodically, not just throwing it out at the beginning and, and hoping the chaos >>Works. Exactly. Exactly. And >>The ratio of of bots to automations, is that one to one or you have automation? Oh no, the single bot is doing multiple. So how many bots are you talking about? >>We're doing, Bob, you're gonna answer this better than I will, but the efficiency is amazing. We've been pushing that. >>So our ratio now, cause we have a high density architecture we put in is four bots, excuse me, four processes. The one bot and four bots, The one virtual machine EC two server. Right? So it's four to one, four to one. Now what we're going to get by next summer, we'll do more analysis. We'll probably get the six to one, six to one that's made serious shrinkage of our footprint from a machine, you know, management perspective from 60 down to seven right now we're gonna add the next chunk. We add another 80 automations in FIS gear 24. We're only gonna add two more bot, two more servers. Right? So that's only 10 running like close to 200 bucks. >>And, and is doing this on prem in the cloud? >>No, our, the architecture's fully >>Oh, cloud based >>Ct. Yeah. So we use UiPath SAS model. Yeah. Right. So that handles the orchestrator, the attended bots, all the other tooling you need automation hub, process minor et etc. Etc. Cetera. And then on the state side in aws we have, we use unattended bots, cert bots that have to go down into the legacy systems, et cetera. And they're sitting on EC two instances. >>Was there, was there a security not hole that you had to get through internally? What was that like? >>No, actually we, we, we were lock and step with the security team on this. I mean, there are some standards and templates and you know, what we had to follow, you know, but they're doing an assessment every single release, they do assessments on little bots, what systems it's activating or are accessing, et cetera. The data, because you have fedra data of FTI data, you know, in the public sector to make sure we're not touching it. >>Do you guys golf? >>I do, yeah. Not Well, yes, >>If you mean I I like golf but not don't golf well, but so you know what, what a mulligan is. If you had a Mulligan right, for the state of Tennessee, what'd you learn? What would you do differently? You know, what are some of the gotchas you see maybe Christina in, in other customers and then maybe specifically state of Tennessee, >>Right? I would say, you know, it is the intangibles. So when we talk about our clients that go fast and go big, like state of Tennessee, it's because that, that we call it phase zero that gets done that Bob did. It's about making sure you've got the sponsorship. So we've got executive sponsorship all the way up. You've got amazing stakeholder engagement. So you're communicating the value of what we're trying to do. And you're, you're showing them the value. We have been really focused on the return on investment and we'll talk a little bit about that, but it's how do you make sure that when you do, you know, states are different with those agencies, you have such an opportunity to maximize return on investment if you do it right, because you're not talking about automation in one agency, you're talking it across multiple agencies. We call that the multiplier effect. And that's huge. And if you understand that and how to actually apply that, the value you get is amazing. So I, I don't, I can't say there's a mulligan here, Bob, you may think of some, I know on other clients, if you don't line up your stakeholders and you don't set the expectations early on, you meander and you may get five, six automations in over the year. You know, when I go to clients and say, we're doing 40, we're doing 80, they're like, >>Wow, that's the, but that's the bottom line. Gotcha. Is if you, if you want to have an operational impact and have multiple zeros, you gotta go through that process that you said up front. >>Exactly. A >>Anything you do differently, Bob? >>Well, I I what I do differently, I mean, I think, I mean we, we did get executive sponsorship, you know, and in one area, but we still have to go out to all the 23 agencies and get, and bring awareness and kind of like set the hook to bring 'em in, right? Bring 'em to the, to the, to the lake. Right. And, and I think if, if it was more of a blanket top down, getting every agency to agree to, you know, in investigate automation, it would've been a lot easier. So we're, we're, we're getting it done. We've gone through 13 agencies already and less than a year, all of our releases are sprinkling across multiple agencies. So it's not like a silo. I'll look at that. Everyone at every agency is being impacted. So I think that's great. But I, I think our, our Mueller now is just trying to make sure we have enough backlog to do the next sprints. >>Is it, you know, the ROI on these initiatives is, is, is so clear and so fast. Is it self-funding? Is there gain sharing or do you just give business, give money back to the state and have to scramble for more? Do you get to, you know, get a lick off that cone? >>Unfortunately we don't, but I, I, I try to see if we could get some property like, nah, we don't do that. It's all cost, cost based. But, but our ROI is very attractive, I think for, for doing a whole state, you know, transformation. I think our ROI is three and a half to four years. Right. And that's pretty mind blowing. Even if you look at private sector or, I, I think some of the, the key things which people are noticing, even though we're in public sector, we're we are very nimble. This project is extremely nimble. We've had people come in, exactly, we need this, so we're gonna get penalized. Okay, knock it out in four hours, four days. Right? So it's that nimbleness that you just don't hear of even in private sector or public sector. And we're just able to do that for all the collaboration we do across ey, across myself and across all the other organizations that I, that I kind of drag along or what have, >>What do you, what do you, do you see any limits to the opportunities here? I mean, is this a decade long opportunity? Is you have that much runway >>Or that's just not my dna, so we're gonna, we're gonna probably do it like in four years, but Well, when >>You say do it, I mean, will you be done at that point? Or do you see the weight, >>Look at, you know, we could boil the ocean and I think this is one of the reasons why we're successful is we could boil the ocean and and be, it will be 10 attended 20 year program. Yeah. Okay. Or we looked at it, we had some of EY guys look at it and say, I said, what's the 25 80 rule? Meaning, you know, give me, So if we had 500 processes, tell me how many processes will gimme 80% of the hours. And it was 125, it was a 25 80 rule. I said, that's what we're doing it, we're doing, we're gonna do the 80% of the hours quantifiably. Now when we're done with that pass, then we'll have those other ones that are bringing 20% of the hours, that's when we might be bringing citizens in. That's what we're bringing state workers in. But at that same time, we will be going back in the wave and doing advanced ai. Right. Or advance ia, in other words. So right now we do rpa, ocr, icr, but you know, there's NL ml nps, there's virtual agents and stuff. So that's like the wave we're gonna do through the ones we've already gone through. Got it. Right. So it'll probably be a two or three wave or iterations. >>Cool. Guys, thanks so much for coming into the cube. Great story. Really appreciate you taking us through it. Thank you so much for having us. You're very welcome. All right, keep it right there. Dave Nicholson. The Dave ante. We back at UI path forward five from the Venetian in Las Vegas. Keep it right there.

(intro upbeat music) >> TheCUBE presents UiPath Forward5, Brought to you by UiPath. >> Welcome to day two of Forward5 UiPath Customer Conference. You're watching theCUBE. My name is Dave Vellante. My co-host is David Nicholson. Yesterday, Dave, we heard about the extension into an enterprise platform. We heard about, from the two CEOs, a new go-to-market strategy. We heard from a lot of customers how they're implementing UiPath generally and automation, specifically, scaling, hyper-automation, and all the buzzwords you hear. Todd Foley is the CDO and CSO of Lydonia Technologies and Devika Saharya is the director of ERP and RPA at MongoDB. Folks, welcome to theCUBE. Thanks for taking time out of your busy day and coming on. >> Thank you Dave. >> Thank you so much. >> So let's start with the roles. So Devika, ERP and RPA. >> Yes. >> It's like peanut butter and jelly, or how do those things relate? What's your, what's your role? >> Absolutely. So I started at Mongo as an ERP manager, and you know, as we were growing, the one thing that came out of, you know, the every year goals for the company, one big goal that came out was how we have to scale. There are so many barriers to scale. How can we become a billion dollar company? What do we need to do? And when we started drilling down into, you know, different areas, we figured it out that people do a lot of stuff manually. It's like comparing sheets, you know, copying data from one place to the other, and so on and so forth. So one thing that we realized was we definitely need some kind of automation. At that time, we didn't know about automation, but we did our own market research and here we are. >> Let's automate. Yeah, right. (Devika laughs) Sounds easy. All right, thank you. Todd, CDO, Chief Data or Chief Dig, and CSO, I'm assuming Chief Data? >> Chief Data. >> And the Chief Information Security Officer. Tell us about Lydonia and also your role. >> Sure, Lydonia, we started just over three years ago. We looked at the RPA market. We saw great opportunity, but we also saw a challenge. We saw that a lot of people had deployed RPA but weren't getting the promised, you know, immediate ROI, rapid deployment that was out there. And when we looked at it, we saw that it really wasn't a technical challenge. Sometimes it was how technology was applied, but there were a lot of things that people were doing in their process and how they were treating RPA, often as if it were traditional technology that slowed them down. So we built our practice, our company, around the idea of being able to help people scale very quickly and drive that faster. And we're finding now with the RPA being pretty ubiquitous, that it's the one thing that's in the greatest demand among our clients. >> Okay, so you're the implementation partner for Mongo, is that right? >> We are. >> Okay, so relatively new. Very new actually, but a specialist. Why'd you choose Lydonia? >> So, that's an interesting question. When we came last year to UiPath Forward, we were looking for, you know, the right kind of people who can, you know, put us on track. We had the technology, we had everything in place, we did the POC, everybody liked it, but we didn't know how to, you know, basically go in that direction. We were missing that direction. And then we, you know, we were doing our homework here, we found, we accidentally stumbled with Lydonia, and I had follow up conversations with Todd, and they were just so tapered. I knew exactly what Todd was explaining me, and we knew we are, we are in safe hands. >> So, where did you start? >> So we, the first thing that we did was a POC for the finance side of business. And right after that POC, we realized that, you know, how much time people were actually investing manually, like things that were done in three to four days was turning into a 30 minute process. And that gave us, you know, the idea that we should start drilling down into different departments and try to find where there are, you know, areas where we can improve. And we did all of that. And then we met with Todd, and Todd explained that how his Reignite process works. So we took Reignite as our first step and, you know, took it from there. We chose one department, we worked with them. We had about 10 processes highlighted, thanks to Todd, he worked with them, and he literally drilled and nailed it down that what we need to do. And as of today, all those 10 are automated. >> Wow. Okay. >> Todd, does this interaction between Lydonia and MongoDB, as a customer, apply equally in the field when you're going out and talking to clients that might be running MongoDB, they might be customers of MongoDB, they may have financial applications that are backended with MongoDB, is there a synergy there that you've been able to gain? >> I think there is. I think there's one thing that's kind of unique about RPA, and that the traditional questions around integration and applicability aren't as important when you have a platform that can work with anything that people can use. I think also, you know, when we look at what we typically do with people, some of the things we see at Mongo are very common use cases you know, across all of our clients. So I, there's definitely the ability for us to take things we've done and have clients get leverage out of them. At the same time, the platform itself is, makes it different than a traditional model where, you know if somebody has worked in a particular area or built an automation for a particular application, there's some kind of utility to do it faster for another client. What we find is that that's not really the case. And that oftentimes we'll compete with people who use different tool sets than UiPath who have that kind of value story around having done it before, we come in and we do it twice as fast as they could. >> So you've, you're a veteran of complex integrations. >> Oh yeah. (Todd laughs) >> I know that from our paths have crossed in the past. So you're saying that in this world of RPA, that this tool set like UiPath as a platform, we've been talking a lot about the difference between being a tool set and being a platform. >> Right. >> That this platform can sort of hover above things without that same layer of complexity, or level of complexity, that you've experienced in the past. Because that speaks to the idea that UiPath, as a platform, is going to work moving forward in a big way. >> Exactly, right. I think we've seen for years and years that regardless of the type of development environment you're using, a developer's value sometimes is based on what reusable libraries they've created, what they have to cut and paste from their old code to be able to do things faster. The challenge with that is it has to be maintained, when things change, they've got to update those libraries. It's a value prop that's very high touch. With UiPath, they've created the ultimate in reusability. The platform, especially since they acquired cloud elements and built all of those API integrations into their platform. The platform maintains the reusability and the libraries in such a way where they're drag and drop from a development standpoint and you don't have to maintain them. It's the ultimate expression of reusability as a platform. >> Yeah, cloud elements, API automation, obviously a key pick by UiPath. Devika, what's the scale of your operation today? Like how many bots and where do you see it going? >> Yes. So we, we started with one bot. Last year we experimented a lot that, you know, we were just trying to make our footprint in the company, trying to understand that, you know, people understand what RPA is, what UiPath is. Initially we got a lot of pushback. We got a pushback from our security team as well, because they could not understand, you know, that what UiPath is and how secure it is. And we had to explain them that how we would host it over AWS, how we will work, how we will not save passwords, et cetera. When we did all of that and they got comfort, we started picking, you know, very small processes around to show, you know, people the capability of RPA and UiPath per se. When we did that, people started just coming with bigger processes, and one specific team that I can think of came that we do, you know, fuzzy logic in Excel, and we do it twice a week, but it takes a lot of time. We automated it, they run it daily, every single day, two times now. And the exponential growth that we saw just with that one automation was mind boggling. I couldn't believe that, you know. We were tracking our insights and we were like, oh my God, what happened? It just blew out of proportion. >> Okay. So then did you need more bots? Are you still running one bot, or? >> Nope. Now at the moment we have nine. >> Okay. >> And we are still looking to grow. >> Okay. So the initial friction, you said there was some, you know, concern, it was primarily security or were there others, people afraid they're going to lose their jobs? Was there any of that? >> There was no risk of losing the job. The major, you know, pushback was, one was from security, the other one was from different system owners because a lot of people were not sure why we want UI access, or why we want API access, and why are we accessing their systems? What type of information we are trying to gather out of their systems. Are we writing into their system? Because a lot of people have issues when we start saying that we will write or override data. So most of the processes that we are working around are either writing, comparing, and reading and comparing, and if it is writing, we take special permission that this is what we are going to do. >> So what did you have to do to get through the security mottle, a AWS SOC 2 report, did you have to show them the UiPath pen test? >> Absolutely. >> Did you have to change any of your processes? What was that sort of punch list like? >> Everything. >> Yeah. >> So we had to start from pen test. We had to start, we had to explain that UiPath is in the process of, you know, acquiring SOC. We also explained that how things are hosted on AWS. We had to, you know, bring our consultants in who explained that how on, on AWS, this will be a very secured way of doing things. And when we did our first process, which was actually for the auditors, which is, you know, interesting. >> Yeah. >> What we did was we did segregation of duties, which I think is very important in every field and every sphere we work in. So for example, the the writeup that we were building for auditors, we made sure that it is approved by a physical or a human, you know, and not everything is done by the bot. The biggest piece of the puzzle was writing, you know, because it was taking a lot of time. People were going into different systems, gathering information, putting it on Excel, and then you know, comparing and submitting it to PWC. >> When you say write, you mean any update to a system of record? >> Correct. >> Required some scrutiny? >> Some scrutiny, yes, yes. >> Okay, initially by a human until there was comfort level and then it's like these bots know what they're doing. >> Correct, correct. >> Okay. And now you're a NetSuite customer, correct? >> Yes. >> That's your ERP? >> That's right. >> Now we were talking about Oracle is going to acquire OCR capabilities. Will that, and we've been talking, Dave and I, a week about, okay well ServiceNow has, you know, RPA, and Salesforce, and SAP, et cetera. How will that affect your thinking about adopting UiPath? >> I don't think it should matter because I think all these systems kind of coexist in a bigger ecosystem, you know, and I also feel that all these systems have their own plus points and minus points. Not one system in, per se, can do everything within a company. So it could be that, for example, NetSuite might be very strong for financials in the space we are in, but not extremely good around sales and marketing. So for that company chose Salesforce. So you know, you have those smaller smaller multiple systems that build into a bigger ecosystem, right. And I think the other piece of the puzzle is that UiPath helps bridge that gap between these systems. You know, it could happen that certain things can get integrated, certain things cannot because of the nature of business, the nature of work that the teams are trying to do. And I think UiPath is leveraging that gap, you know, and putting, you know, those strings together. >> As you scale - >> Mm hmm. >> How will, and Todd I presume you're going to assist in this process, but how will you decide what processes to prioritize, and is that a process driven decision? Is it data led? Both? If so, what kind of data? Can you describe how you guys are going to approach that? >> Yep. Todd, would you like to take that first before I start? >> Sure, yeah. >> Maybe some best practices and then we can maybe get specific to Mongo. >> Absolutely. Our guidance is always that it should be a business decision, right? And it should be data driven, based on a business defined metric around the business case for that particular automation. Our guidance to customers is don't automate it unless you know why you're automating it, and what the value is. We see sometimes there are challenges with people being able to articulate the business case for an automation, and it can almost always be resolved by having that business case be the first step, and qualifying and identifying an automation candidate. >> And how does that apply to Mongo? Do you, where are you thinking about scaling, in your opinion? >> It's interesting because, you know, initially we thought that we will, you know, explore one area in MongoDB. And the other thing that we did was we did road shows. So because we had to create some awareness in the company that we have UiPath there's something called bots. There's something called, you know, automation that we can do, so we created a presentation with small demos inside it and, you know, circulated it within the company. Different departments tried to explain what we can achieve. And based off of that, you know, we came up with a laundry list of all the automations that different departments needed. And out of that, you know, we started doing the business case, the value, you know, trying to come up with complexity, effort. We did a full estimation matrix and based off of that we came, okay, these are the top 20 that we should build first. And as soon as we built those top 20, we saw a skyrocket, you know, growth and - >> And you're looking for hard dollars, right? >> Yes, yes. Absolutely. >> Okay, just to be clear. >> Devika, I think Mongo also is great at taking a data driven approach to looking at their program. Do you want to share how you do that? >> Yes, absolutely. So one thing that we were very sure was we have to talk in terms of numbers because that's the only solid way to see growth. And what we did was, you know, we got insights, we started doing full metrics in terms of dollar saved, hour saved, and we are trying to track how every process is impacting, you know, in the grand scheme of things. Like say for example, for finance, are we shortening the close cycle in any shape or form by doing these two or three automations that we are doing? And I'm happy to report that we have really shortened our close cycle from where we started. >> Your quarter end or month end close. >> Correct, yes. >> Daily? You at the daily close yet, (all laugh) or the "John Chambers"? >> Drive everyone nuts. First I have to say, I could feel the audience sort of smiling as they see, as they hear from MongoDB, disruptor of legacy databases being cautious in their internal approach to change. As everyone else is. >> Exactly, yeah. >> But Todd, just sort of, double clicking on this idea of kind of stove pipes of capabilities in the RPA space. I mean OCR, being added to NetSuite, I'm not sure if that's the greatest example, but the point is Lydonia will work with all of those technologies to synthesize something. Is that correct? Or are you a UiPath only? >> Both. So we exclusively use UiPath with our customers. We don't use other RPA platforms. >> Okay. >> And we don't because, not because we can't, but because we don't believe that anything else is going to be as quick or as effective. Also, it's the only platform that is as broad and comprehensive as it needs to be to deliver outcomes to our customers. We have partnerships with other companies that have gaps where UiPath isn't currently playing, but the number of companies and the number of gaps has shrunk down to almost nothing these days. And we're well placed as UiPath continues to grow their platform to take advantage of that and leverage that to deliver outcomes to customers. >> It was a great story of starting small, being careful. >> Yes. >> And prudent, from a security standpoint, especially as a public company. And then it sounds like there's virtually unlimited opportunity. >> Yes, absolutely, absolutely. >> For you guys. Great story, thank you very much for sharing it. Appreciate it. >> Thank you. >> All right, good luck. All right, thank you for watching. Keep it right there. Dave Nicholson and Dave Vellante will be back from UiPath Forward5 from the Venetian in Las Vegas. Be right back. (upbeat music playing)

>> TheCUBE presents UI Path Forward Five brought to you by UI Path. >> Welcome back to UI Path Forward Five. You're watching The Cubes, Walter Wall coverage. This is day one, Dave Vellante, with my co-host Dave Nicholson. We're taking RPA to intelligence automation. We're going from point tools to platforms. Neeraj Mathur is here. He's the director of Intelligent Automation at VMware. Yes, VMware. We're not going to talk about vSphere or Aria, or maybe we are, (Neeraj chuckles) but he's joined by Thomas Stocker who's a principal product manager at UI Path. And we're going to talk about testing automation, automating the testing process. It's a new sort of big vector in the whole RPA automation space. Gentleman, welcome to theCUBE. Good to see you. >> Neeraj: Thank you very much. >> Thomas: Thank you. >> So Neeraj, as we were saying, Dave and I, you know, really like VMware was half our lives for a long time but we're going to flip it a little bit. >> Neeraj: Absolutely. >> And talk about sort of some of the inside baseball. Talk about your role and how you're applying automation at VMware. >> Absolutely. So, so as part of us really running the intelligent automation program at VMware, we have a quite matured COE for last, you know four to five years, we've been doing this automation across the enterprise. So what we have really done is, you know over 45 different business functions where we really automated quite a lot different processes and tasks on that. So as part of my role, I'm really responsible for making sure that we are, you know, bringing in the best practices, making sure that we are ready to scale across the enterprise but at the same time, how, you know, quickly we are able to deliver the value of this automation to our businesses as well. >> Thomas, as a product manager, you know the product, and the market inside and out, you know the competition, you know the pricing, you know how customers are using it, you know all the features. What's your area of - main area of focus? >> The main area of the UiPathT suite... >> For your role, I mean? >> For my role is the RPA testing. So meaning testing RPA workflows themselves. And the reason is RPA has matured over the last few years. We see that, and it has adopted a lot of best practices from the software development area. So what we see is RPA now becomes business critical. It's part of the main core business processes in corporation and testing it just makes sense. You have to continuously monitor and continuously test your automation to make sure it does not break in production. >> Okay. And you have a specific product for this? Is it a feature or it's a module? >> So RPA testing or the UiPath T Suite, as the name suggests it's a suite of products. It's actually part of the existing platform. So we use Orchestrator, which is the distribution engine. We use Studio, which is our idea to create automation. And on top of that, we build a new component, which is called the UiPath Test Manager. And this is a kind of analytics and management platform where you have an oversight on what happened, what went wrong, and what is the reason for automation to **bring. >> Okay. And so Neeraj, you're testing your robot code? >> Neeraj: Correct. >> Right. And you're looking for what? Governance, security, quality, efficiency, what are the things you're looking for? >> It's actually all of all of those but our main goal to really start this was two-front, right? So we were really looking at how do we, you know, deliver at a speed with the quality which we can really maintain and sustain for a longer period, right? So to improve our quality of delivery at a speed of delivery, which we can do it. So the way we look at testing automation is not just as an independent entity. We look at this as a pipeline of a continuous improvement for us, right? So how it is called industry as a CICD pipeline. So testing automation is one of the key component of that. But the way we were able to deliver on the speed is to really have that end to end automation done for us to also from developers to production and using that pipeline and our testing is one piece of that. And the way we were able to also improve on the quality of our delivery is to really have automated way of doing the code reviews, automated way of doing the testing using this platform as well. and then, you know, how you go through end to end for that purpose. >> Thomas, when I hear testing robots, (Thomas chuckles) I don't care if it's code or actual robots, it's terrifying. >> It's terrify, yeah. >> It's terrifying. Okay, great. You, you have some test suite that says look, Yeah, we've looked at >> The, why is that terrifying? >> What's, It's terrifying because if you have to let it interact with actual live systems in some way. Yeah. The only way to know if it's going to break something is either you let it loose or you have some sort of sandbox where, I mean, what do you do? Are you taking clones of environments and running actual tests against them? I mean, think it's >> Like testing disaster recovery in the old days. Imagine. >> So we are actually not running any testing in the production live environment, right? The way we build this actually to do a testing in the separate test environment on that as well by using very specific test data from business, which you know, we call that as a golden copy of that test data because we want to use that data for months and years to come. Okay. Right? Yeah. So not touching any production environmental Facebook. >> Yeah. All right. Cause you, you can imagine >> Absolutely >> It's like, oh yeah we've created a robotic changes baby diapers let's go ahead and test it on these babies. [Collective Laughter] Yeah >> I don't think so. No, no, But, but what's the, does it does it matter if there's a delta between the test data and the, the, the production data? How, how big is that delta? How do you manage that? >> It does matter. And that's where actually that whole, you know, angle of how much you can, can in real, in real life can test right? So there are cases where you would have, even in our cases where, you know, the production data might be slightly different than the test data itself. So the whole effort goes into making sure that the test data, which we are preparing here, is as close to the products and data itself, right? It may not be a hundred percent close but that's the sort of you know, boundary or risk you may have to take. >> Okay. So you're snapshotting, that moving it over, a little V motion? >> Neeraj: Yeah. >> Okay. So do you do this for citizen developers as well? Or is you guys pretty much center of excellence writing all the bots? >> No, right now we are doing only for the unattended, the COE driven bots only at this point of time, >> What are you, what are your thoughts on the future? Because I can see I can see some really sloppy citizen coders. >> Yeah. Yeah. So as part of our governance, which we are trying to build for our citizen developers as well, there there is a really similar consideration for that as well. But for us, we have really not gone that far to build that sort of automation right >> Now, narrowly, just if we talk about testing what's the business impact been on the testing? And I'm interested in overall, but the overall platform but specifically for the testing, when did that when did you start implementing that and, and what what has been the business benefit? >> So the benefit is really on the on the speed of the delivery, which means that we are able to actually deliver more projects and more automation as well. So since we adopted that, we have seen our you know, improvement, our speed is around 15%, right? So, so, you know, 15% better speed than previously. What we have also seen is, is that our success rate of our transactions in production environment has gone to 96% success rate, which is, again there is a direct implication on business, on, on that point of view that, you know, there's no more manual exception or manual interaction is required for those failure scenarios. >> So 15% better speed at what? At, at implementing the bots? At actually writing code? Or... >> End to end, Yes. So from building the code to test that code able to approve that and then deploy that into the production environment after testing it this is really has improved by 15%. >> Okay. And, and what, what what business processes outside of sort of testing have you sort of attacked with the platform? Can you talk to that? >> The business processes outside of testing? >> Dave: Yeah. You mean the one which we are not testing ourself? >> Yeah, no. So just the UI path platform, is it exclusively for, for testing? >> This testing is exclusively for the UI path bots which we have built, right? So we have some 400 plus automations of UI bots. So it's meant exclusively >> But are you using UI path in any other ways? >> No, not at this time. >> Okay, okay. Interesting. So you started with testing? >> No, we started by building the bots. So we already had roughly 400 bots in production. When we came with the testing automation, that's when we started looking at it. >> Dave: Okay. And then now building that whole testing-- >> Dave: What are those other bots doing? Let me ask it that way. >> Oh, there's quite a lot. I mean, we have many bots. >> Dave: Paint a picture if you want. Yeah. In, in finance, in auto management, HR, legal, IT, there's a lot of automations which are there. As I'm saying, there's more than 400 automations out there. Yeah. So so it's across the, you know, enterprise on that. >> Thomas. So, and you know, both of you have a have a view on this, but Thomas's views probably wider across other, other instances. What are the most common things that are revealed in tests that indicate something needs to be fixed? Yeah, so think of, think of a test, a test failure, an error. What are the, what are the most common things that happen? >> So when we started with building our product we conducted a, a survey among our customers. And without a surprise the main reason why automation breaks is change. >> David: Sure. >> And the problem here is RPA is a controlled process a controlled workflow but it runs in an uncontrollable environment. So typically RPA is developed by a C.O.E. Those are business and automation experts, but they operate in an environment that's driven by new patches new application changes ruled out by IT. And that's the main challenge here. You cannot control that. And so far, if you, if you do not proactively test what happens is you catch an issue in production when it already breaks, right? That's reactive, that's leads to maintenance to un-claim maintenance actually. And that was the goal right from the start from the taste suite to support our customers here and go over to proactive maintenance meaning testing before and finding those issues before the heat production. >> Yeah. Yeah, yeah. So I'm, I'm still not clear on, so you just gave a perfect example, changes in the environment. >> Yeah. >> So those changes are happening in the production environment. >> Thomas: Yeah. The robot that was happily doing its automation stuff before? >> Thomas: Yeah. Everyone was happy with it. Change happens. Robot breaks. >> Thomas: Yeah. >> Okay. You're saying you test before changes are implemented? To see if those changes will break the robot? >> Thomas: Yeah. >> Okay. How do you, how do you expose those changes that are in the, in a, that are going to be in a production environment to the robot? You must have a, Is is that part of the test environment? Does that mean that you have to have what fully running instances of like an ERP system? >> Thomas: Yeah. You know, a clone of an environment. How do you, how do you test that without having the live robot against the production environment? >> I think there's no big difference to standard software testing. Okay. The interesting thing is, the change actually happens earlier. You are affected on production side with it but the change happens on it side or on DevOps side. So you typically will test in a test environment that's similar to your production environment or probably in it in a pre-product environment. And the test itself is simply running your workflow that you want to test, but mark away any dependencies you don't want to invoke. You don't want to send a, a letter to a customer in a test environment, right? And then you verify that the result is what you actually expect, right? And as soon as this is not the case, you will be notified you will have a result, the fail result, and you can act before it breaks. So you can fix it, redeploy to production and you should be good now. >> But the, the main emphasis at VMware is testing your bots, correct? >> Neeraj: Testing your bots. Yes. Can I apply this to testing other software code? >> Yeah, yeah. You, you can, you can technically actually and Thomas can speak better than me on that to any software for that matter, but we have really not explored that aspect of it. >> David: You guys have pretty good coders, good engineers at VMware, but no, seriously Thomas what's that market looking like? Is that taking off? Are you, are you are you applying this capability or customers applying it for just more broadly testing software? >> Absolutely. So our goal was we want to test RPA and the application it relies on so that includes RPA testing as well as application testing. The main difference is typical functional application testing is a black box testing. So you don't know the inner implementation of of that application. And it works out pretty well. The big, the big opportunity that we have is not isolated Not isolated testing, isolated RPA but we talk about convergence of automation. So what we offer our customers is one automation platform. You create one, you create automation, not redundantly in different departments, but you create once probably for testing and then you reuse it for RPA. So that suddenly helps your, your test engineers to to move from a pure cost center to a value center. >> How, how unique is this capability in the industry relative to your competition and and what capabilities do you have that, that or, or or differentiators from the folks that we all know you're competing with? >> So the big advantage is the power of the entire platform that we have with UiPath. So we didn't start from scratch. We have that great automation layer. We have that great distribution layer. We have all that AI capabilities that so far were used for RPA. We can reuse them, repurpose them for testing. And that really differentiates us from the competition. >> Thomas, I I, I detect a hint of an accent. Is it, is it, is it German or >> It's actually Austrian. >> Austrian. Well, >> You know. Don't compare us with Germans. >> I understand. High German. Is that the proper, is that what's spoken in Austria? >> Yes, it is. >> So, so >> Point being? >> Point being exactly as I drift off point being generally German is considered to be a very very precise language with very specific words. It's very easy to be confused about between the difference the difference between two things automation testing and automating testing. >> Thomas: Yes. >> Because in this case, what you are testing are automations. >> Thomas: Yes. >> That's what you're talking about. >> Thomas: Yes. >> You're not talking about the automation of testing. Correct? >> Well, we talk about >> And that's got to be confusing when you go to translate that into >> Dave: But isn't it both? >> 50 other languages? >> Dave: It's both. >> Is it both? >> Thomas: It actually is both. >> Okay. >> And there's something we are exploring right now which is even, even the next step, the next layer which is autonomous testing. So, so far you had an expert an automation expert creating the automation once and it would be rerun over and over again. What we are now exploring is together with university to autonomously test, meaning a bot explores your application on the test and finds issues completely autonomously. >> Dave: So autonomous testing of automation? >> It's getting more and more complicated. >> It's more clear, it's getting clearer by the minute. >> Sorry for that. >> All right Neeraj, last question is: Where do you want to take this? What's your vision for, for VMware in the context of automation? >> Sure. So, so I think the first and the foremost thing for us is to really make it more mainstream for for our automation developer Excel, right? What I mean by that is, is to really, so so there is a shift now how we engage with our business users and SMEs. And I said previously they used to actually test it manually. Now the conversation changes that, hey can you tell us what test cases you want what you want us to test in an automated measure? Can you give us the test data for that so that we can keep on testing in a continuous manner for the months and years to come down? Right? The other part of the test it changes is that, hey it used to take eight weeks for us to build but now it's going to take nine weeks because we're going to spend an extra week just to automate that as well. But it's going to help you in the long run and that's the conversation. So to really make it as much more mainstream and then say that out of all these kinds of automation and bots which we are building, So we are not looking to have a test automation for every single bot which we are building. So we need to have a way to choose where their value is. Is it the quarter end processing one? Is it the most business critical one, or is it the one where we are expecting of frequent changes, right? That's where the value of the testing is. So really bring that as a part of our whole process and then, you know >> We're still fine too. That great. Guys, thanks so much. This has been really interesting conversation. I've been waiting to talk to a real life customer about testing and automation testing. Appreciate your time. >> Thank you very much. >> Thanks for everything. >> All right. Thank you for watching, keep it right there. Dave Nicholson and I will be back right after this short break. This is day one of theCUBE coverage of UI Path Forward Five. Be right back after this short break.

>>The Cube presents UI Path Forward five. Brought to you by UI Path. >>Hi everybody. We're back at UI path forward to five. This is Dave Ante with Dave Nicholson. Derek Mu is here. He's automation product line lead for Merck. Thank you, by the way, for, you know, all you guys do, and thank you Dave for having in the, in the, in the vaccine area, saving our butts. And Bill Engel is back on the cube. He's the director at cgi. Guys, good to see you again. >>Good to see you. Thank >>You. So Merrick, Wow, it's been quite a few years for you guys. Take us through Derek, what's happening in sort of your world that's informing your automation strategy? >>Well, Dave, I mean as you know, we just came out of the pandemic. We actually have quite a few products like Gabriel Antiviral Pill. Obviously we worked, you know, continue to drive our products through a difficult time. But, you know, is during these can last few years that, you know, we've accelerated our journey in automation. We're about four years plus in our journey, you know, so just like the theme of this conference we're we're trying to move towards, you know, bigger automations, transformational change, continue to drive digital transformation in our company. >>Now Bill, you've been on before, but CGI tell people about the firm. It's not computer graphics imaging. >>Sure. No, it's, it's definitely not. So cgi, we're a global consultancy about 90,000 folks across the world. We're a, we're both a product company and a services company. So we have a lot of different, you know, software products that we deliver to our clients, such as CGI Advantage, which is a state local government EER P platform. And so outside of that, we, my team does automation and so we wrap automation around R IP and deliver that to our clients. >>So you guys are automation pros, implementation partners, right? So, so let's go back. Yep. Derek said four years I think. Yep. Right, You're in. So take us through what was the catalyst, how did you get started? Obviously it was pre pandemic, so it's interesting, a lot of companies pre pandemic gave lip service to digital transformation. Sounds like you guys already started your journey, but I'll come back to that. But take us back to the Catalyst four years ago. Why automation? We'll get into why UI path, >>Right. So I, I would say it started pretty niche in our company. Started first in our finance area. Of course, you know, we were looking in technology evaluating different companies, Blue Prism, ui P. Ultimately we chose UI p did it on-prem to start to use automation in sort of our invoice processing, sort of our financial processes, right? And then from there, after it was really when the pandemic hit, that's when sort of we all went to remote work. That's when the team, the COE continued to scale up, especially during pandemic. We were trying to automate more and more processes given the fact that more and more of our workers are remote, they reprocesses. How, how do you do events? You know, part of our livelihood is, is meeting with engaging with customers. Customers in this case is, are doctors and physicians, right? How do you engage with them digitally? How do you, you know, you know, a lot of the face to face contact now have to kind of shift to more digital, digital way. And so automation was a way to kind of help accelerate that, help facilitate that. >>You, you, I think you mentioned COE as in center of excellence. Yep. So, so describe your approach to implementing automation. It's, that sounds like when you say center, it sounds like something is centralized as, as opposed to a bunch of what we've been hearing a lot about citizen developers. What does that interaction >>Look like? We do have both. I would say in the beginning was more decentralized, but over time we, over the few years as, as we built more and more bots, we're now at maybe somewhere between four to 500 bots. We now have sort of internal to the company functional verticals, right? So there's an animal health, we have an animal health function. So there's, there's a team building engaging with the animal health business to build animal health box. There's human health, which is what I work on as well as hr, finance, manufacturing, research. And so internally there's engagement leads, one of the engagement leads that interact with the business. Then when there's an engineering squads that help build and design, develop and support and maintain those as well as sort of a DevOps team that supports the platform and maintains all the bot infrastructure. >>So you started in finance common story, right? I'm sure you hear this a lot Belt, How did you decide what to target? Was it, was it process driven decision? Was it, was it data oriented? Like some kind of combination? How did you decide, Do you remember? Or do you, could you take >>Us back to Oh yeah. So for, for cgi how we started to engage with MER is, you know, we, we do a lot of other business with Merck. We work on all their different business lines and we, we understand the business process. So we, we knew where there was potential for automation. So we brought those ideas to Merck and, and really kind of landed there and helped them realize the value from automation from that standpoint. And then from there the journey just continued to expand, you know, looking for those use cases that, that, you know, fit the mold for, for, for RPA to start. And now the evolution is to go to broader hyper automation. >>And, and was it CFO led into the finance department and then, or was it sort of more bottoms >>Up? Yeah, so, so I think it started in, in finance and, and, but we actually really started out in the business line. So out in regulatory clinical, that's, that's where we, we have the life science expertise that are embedded. And so I partnered with them to come up with, hey, here's a real solution we could do to help streamline, say submission archiving. So when, when submissions come back from the fda, they need to be archived into, you know, the, their system of record. So that's, those are the types of use cases that, that we helped automate. >>Okay. Cause you're saying a human had to sort physically archive that and you were able to sort of replicate that. Okay. And you started with software robots, obviously rpa and now you're expanding into, we we're hearing from UI this the platform message. How does that coincide Derek, with what you guys are doing? Are you sort of adding platform? What aspects of the platform are, are you adding? >>Yeah, no, I mean we are, we are on-premise, right? So we have the platform, but some of the cool things we just had, another colleague of mine presented earlier today. Some of the cool things we're, we're doing ephemeral infrastructure. So infrastructure as code, which essentially means instead of having all these dedicated bot machines, that that, you know, cuz these bots only in some cases run 10 minutes and they're done. So we're, we're soon of doing all on demand, you know, start up a server, run the bot when it's finished, you know, kill the server. So we only pay for the servers that we use, which allows us to save a whole >>Lot of money. Serverless bots. So you, but you're doing that OnPrem, so you >>No, >>No, but >>That's >>Cloud. We, >>We, we we're doing it OnPrem, but our, our bot machines that actually run the, let's say SAP process, right? We spin that machine up, it's on the cloud, it runs it finish, Let's say it's processed in one hour and then when it's done, we kill that machine. So we only play for that one hour usage of that bot machine. >>Okay. So you mentioned SAP earlier you mentioned Blue Prism when you probably looked at other competitors too. You pull the Gartner Magic quadrant, blah, blah, you know, with the way people, you know, evaluate technology, but SAP's got a product. Why UI path mean? Is it that a company like SAP two narrow for their only sap you wanted to apply it other ways? Maybe they weren't even in the business that back then four years ago they probably weren't. Right? But I'm curious as to how the decision was made for UiPath. >>Well, I think you hit it right on the nail. You know, SAP sort of came on a little later and they're specific to sort of their function, right? So UiPath for us is the most flexible tool can interact by UI to our sales and marketing systems, to, to workday, to service Now. It's, it cuts across every function that we have in the company as well as you're the most mature. I mean, you're the market leader, right? So Right. Definitely you, you continue to build upon those capabilities and we are exploring the new capabilities, especially being announced today. >>And what do you see Bill in the marketplace? Are you, are you kind of automation tool agnostic? Are you more sort of all in on? I >>Would say we are, we are agnostic as a company, but obviously as part of a, as an automation practice lead, you know, I want to deliver solutions to my clients that are gonna benefit them as a whole. So looking at UI path, you know, that this platform is, it covers the end to end spectrum of, of automation. So I can go really into any use case and be able to provide a solution that, that delivers value. And so that's, that's where I see the value in UI path and that's why CGI is, is a customer as well. We automate our internal processes. We actually have, we just launched probably SALT in the, in the market last week, expanded partnership with UiPath. We launched CGI, Excel 360. That's our fully managed service around automation. We host our clients whole UI path infrastructure and bots. It's completely hands off to them and they just get the value outta >>Automation. Nice, nice. Love >>It. Derek, you mentioned, you mentioned this ephemeral infrastructure. Yeah. Sounds like it's also ethereal possibility possibly you're saying, you, you're saying you have processes that are running on premises, right? But then you reach out to have an automation process run that's happening off pre and you're, and you're sort of, >>It's on the cloud, so, so yeah, so we have a in-house orchestrator, so we don't, we're not using your sort of on the cloud orchestrator. So, so we brought it in-house for security reasons. Okay. But we use, you know, so inside the vpn, you know, we have these cloud machines that run these automations. So, so that's, that's the ephemeral side of the, of the >>Infrastructure. But is there a financial angle to that in terms of when you're spinning these things up, are you, is it a, is it a pay by the drink or by the, by the CPU >>Hours, if you can imagine like we, you know, like I mentioned where somewhere between four to 500 bots and every bot has a time slot to run and takes a certain amount of time. And so that's hundreds and hundreds of bot machines that we in the old days have to have to buy and procure and, you know, staff and support and maintain. So in this new model, and we're just beginning to kind of move from pilot into implementation, we're moving all, all of bots this in ephemeral infrastructure, right? So these, okay, these machines, these bot machines are, you know, spun up. They run the, they, they run their automation and then they spin >>Down. But just to be clear, they're being spun up on physical infrastructure that is in your >>Purview and they spun up on aws. Yeah. Okay. And then they spin down. Okay, got >>It. Got it. Interesting. Four >>To 500 bots. You know, Daniel one point play out this vision of a bot chicken in every pot, I called it a bot for every employee. Is that where you're headed or is that kind of in this new ephemeral world, not necessary, it's like maybe every employee has access to an ephemeral bot. How, how are you thinking about that? >>That's a good question. So obviously the, the four to 500 is a mix of unattended bonds versus attended bonds, right? That, that we also have a citizen developer, sort of a group team. We support that as well from a coe. So, you know, we see the future as a mix. There's, there's a spectrum of, we are the professional development team. There's also, we support and nurture the personal automation and we provide the resources to help them build smaller scale automations that help, you know, reduce the, you know, the mundaneness and the hours of their own tasks. But you know, for us, we want to focus more and more on building bigger and bigger transfer transformational automations that really drive process efficiencies and, and savings. >>And what's the, what's the business impact been? You mentioned savings and maybe there's other sort of productivity. How do you measure the benefit, the ROI and, and >>Quantify that we, you know, I, I don't, I don't profess I don't think we have all the right answers, but yeah, simple metrics like number of hours saved or other sort of excitement sort of in like an nps, internal NPS between the different groups that we engage. But we definitely see automation demand coming from our, our functional teams going up, driving up. So it's, it's continued to be a hot area and hopefully we, we can, you know, like, like what the key message and theme of this, of this conference. Essentially we want to take and build upon the, the good work that we've done in terms of rpa and we want to drive it more towards digital transformation. >>So Bill, what are you seeing across the, your customer base in terms of, of, of roi? I'm not looking for percentages there. I'm sure they're off the charts, but in terms of, you know, you can optimize for fast payback, you know, maybe lower the denominator, you know, or you can optimize for, you know, net benefit over time, right? You know, what are you seeing? What are customers after they want fast payback and little quick hits? Or are they looking for sort of a bigger enterprise wide impact? >>Yeah, I think it's, it's the latter. It's that larger impact, right? Obviously they, you know, they want an roi and just depending upon the use case, that's gonna vary in terms of the, the benefits delivered. And a lot of our clients, depending on the industry, so in in life sciences it may be around, you know, compliance like GXP compliance is huge. And so that may may not be much of a time saver, but it ensures that they're, they're running their processes and they're being compliant with, you know, federal standards. So that's, that's one aspect to it. But you know, to, you know, a bank, they're looking to reduce their overall costs and and so on. But yeah, I think, I think the other, the other part of it is, you know, impacting broader business processes. So taking that top down approach versus kind of bottom up, you know, doing ta you know, the ones you choose the tasks is not as impactful as looking at broader across the entire business process and seeing how we can impact >>It. Now, Derek, when you guys support a citizen developer, how does that work? So, hey, I got this task I want to automate, I'm gonna go write a, you know, software robot. I'm gonna go do an automation. Do I just do it and then throw her to the defense? You guys, you guys send me a video on how to do it. Hold my hand. How's that work? >>Yeah, I mean, good question. So, so we obviously direct them to the UI path Academy, get some training. We also have some internal training materials to how to build a bot sort of internal inside Merck. We, we go through, we have writeups and SOPs on using the right framework for automations, using the right documentation, PDD kind of materials, and then ultimately how do we deploy bot inside the MER ecosystem. But I, I, maybe I'll just add, I think you asked the point about ROI before. Yeah. I'll also say because we're, we're a pharmaceutical company. I think one of the other key metrics is actually time saved, right? So if, if, if we have a bot that helps us get through the clinical process or even the getting a, a label approved faster, even if it's eight days saved, that's eight days of a product that can get out to the market faster to, to our patients and, and healthcare professionals. And that's, that, that's immeasurable benefit. >>Yeah, I bet if you compress that ELAP time of, of getting approval and so forth. All right guys, we've gotta go. Thanks so much. Congratulations on all the success and appreciate you sharing your story. Thank >>You so much. Appreciate it. You're welcome. >>Appreciate it. All right. Thank you for watching this Dave Ante for Dave Nicholson, The cubes coverage, two day coverage. We're here in day one, UI path forward, five. We'll be right back right after the short break. Awesome. >>Great.

(cheerful music) >> Hello everyone, welcome to today's session of theCUBE's presentation of AWS Startup Showcase, New Breakthroughs in DevOps, Data Analytics, Cloud Management Tools, featuring Okera from the cloud management migration track. I'm John Furrier, your host. We've got two great special guests today, Nong Li, founder and CTO of Okera, and Sanjeev Mohan, principal @SanjMo, and former research vice president of big data and advanced analytics at Gartner. He's a legend, been around the industry for a long time, seen the big data trends from the past, present, and knows the future. Got a great lineup here. Gentlemen, thank you for this, so, life in the trenches, lessons learned across compliance, cloud migration, analytics, and use cases for Fortune 1000s. Thanks for joining us. >> Thanks for having us. >> So Sanjeev, great to see you, I know you've seen this movie, I was saying that in the open, you've at Gartner seen all the visionaries, the leaders, you know everything about this space. It's changing extremely fast, and one of the big topics right out of the gate is not just innovation, we'll get to that, that's the fun part, but it's the regulatory compliance and audit piece of it. It's keeping people up at night, and frankly if not done right, slows things down. This is a big part of the showcase here, is to solve these problems. Share us your thoughts, what's your take on this wide-ranging issue? >> So, thank you, John, for bringing this up, and I'm so happy you mentioned the fact that, there's this notion that it can slow things down. Well I have to say that the old way of doing governance slowed things down, because it was very much about control and command. But the new approach to data governance is actually in my opinion, it's liberating data. If you want to democratize or monetize, whatever you want to call it, you cannot do it 'til you know you can trust said data and it's governed in some ways, so data governance has actually become very interesting, and today if you want to talk about three different areas within compliance regulatory, for example, we all know about the EU GDPR, we know California has CCPA, and in fact California is now getting even a more stringent version called CPRA in a couple of years, which is more aligned to GDPR. That is a first area we know we need to comply to that, we don't have any way out. But then, there are other areas, there is insider trading, there is how you secure the data that comes from third parties, you know, vendors, partners, suppliers, so Nong, I'd love to hand it over to you, and see if you can maybe throw some light into how our customers are handling these use cases. >> Yeah, absolutely, and I love what you said about balancing agility and liberating, in the face of what may be seen as things that slow you down. So we work with customers across verticals with old and new regulations, so you know, you brought up GDPR. One of our clients is using this to great effect to power their ecosystem. They are a very large retail company that has operations and customers across the world, obviously the importance of GDPR, and the regulations that imposes on them are very top of mind, and at the same time, being able to do effective targeting analytics on customer information is equally critical, right? So they're exactly at that spot where they need this customer insight for powering their business, and then the regulatory concerns are extremely prevalent for them. So in the context of GDPR, you'll hear about things like consent management and right to be forgotten, right? I, as a customer of that retailer should say "I don't want my information used for this purpose," right? "Use it for this, but not this." And you can imagine at a very, very large scale, when you have a billion customers, managing that, all the data you've collected over time through all of your devices, all of your telemetry, really, really challenging. And they're leveraging Okera embedded into their analytics platform so they can do both, right? Their data scientists and analysts who need to do everything they're doing to power the business, not have to think about these kind of very granular customer filtering requirements that need to happen, and then they leverage us to do that. So that's kind of new, right, GDPR, relatively new stuff at this point, but we obviously also work with customers that have regulations from a long long time ago, right? So I think you also mentioned insider trading and that supply chain, so we'll talk to customers, and they want really data-driven decisions on their supply chain, everything about their production pipeline, right? They want to understand all of that, and of course that makes sense, whether you're the CFO, if you're going to make business decisions, you need that information readily available, and supply chains as we know get more and more and more complex, we have more and more integrated into manufacturing and other verticals. So that's your, you're a little bit stuck, right? You want to be data-driven on those supply chain analytics, but at the same time, knowing the details of all the supply chain across all of your dependencies exposes your internal team to very high blackout periods or insider trading concerns, right? For example, if you knew Apple was buying a bunch of something, that's maybe information that only a select few people can have, and the way that manifests into data policies, 'cause you need the ability to have very, very scalable, per employee kind of scalable data restriction policies, so they can do their job easier, right? If we talk about speeding things up, instead of a very complex process for them to get approved, and approved on SEC regulations, all that kind of stuff, you can now go give them access to the part of the supply chain that they need, and no more, and limit their exposure and the company's exposure and all of that kind of stuff. So one of our customers able to do this, getting two orders of magnitude, a 100x reduction in the policies to manage the system like that. >> When I hear you talking like that, I think the old days of "Oh yeah, regulatory, it kind of slows down innovation, got to go faster," pretty basic variables, not a lot of combination of things to check. Now with cloud, there seems to be combinations, Sanjeev, because how complicated has the regulatory compliance and audit environment gotten in the past few years, because I hear security in a supply chain, I hear insider threats, I mean these are security channels, not just compliance department G&A kind of functions. You're talking about large-scale, potentially combinations of access, distribution, I mean it seems complicated. How much more complicated is it now, just than it was a few years ago? >> So, you know the way I look at it is, I'm just mentioning these companies just as an example, when PayPal or Ebay, all these companies started, they started in California. Anybody who ever did business on Ebay or PayPal, guess where that data was? In the US in some data center. Today you cannot do it. Today, data residency laws are really tough, and so now these organizations have to really understand what data needs to remain where. On top of that, we now have so many regulations. You know, earlier on if you were healthcare, you needed to be HIPAA compliant, or banking PCI DSS, but today, in the cloud, you really need to know, what data I have, what sensitive data I have, how do I discover it? So that data discovery becomes really important. What roles I have, so for example, let's say I work for a bank in the US, and I decide to move to Germany. Now, the old school is that a new rule will be created for me, because of German... >> John: New email address, all these new things happen, right? >> Right, exactly. So you end up with this really, a mass of rules and... And these are all static. >> Rules and tools, oh my god. >> Yeah. So Okera actually makes a lot of this dynamic, which reduces your cloud migration overhead, and Nong used some great examples, in fact, sorry if I take just a second, without mentioning any names, there's one of the largest banks in the world is going global in the digital space for the first time, and they're taking Okera with them. So... >> But what's the point? This is my next topic in cloud migration, I want to bring this up because, complexity, when you're in that old school kind of data center, waterfall, these old rules and tools, you have to roll this out, and it's a pain in the butt for everybody, it's a hassle, huge hassle. Cloud gives the agility, we know that, and cloud's becoming more secure, and I think now people see the on-premise, certainly things that'd be on-premises for secure things, I get that, but when you start getting into agility, and you now have cloud regions, you can start being more programmatic, so I want to get you guys' thoughts on the cloud migration, how companies who are now lifting and shifting, replatforming, what's the refactoring beyond that, because you can replatform in the cloud, and still some are kind of holding back on that. Then when you're in the cloud, the ones that are winning, the companies that are winning are the ones that are refactoring in the cloud. Doing things different with new services. Sanjeev, you start. >> Yeah, so you know, in fact lot of people tell me, "You know, we are just going to lift and shift into the cloud." But you're literally using cloud as a data center. You still have all the, if I may say, junk you had on-prem, you just moved it into the cloud, and now you're paying for it. In cloud, nothing is free. Every storage, every processing, you're going to pay for it. The most successful companies are the ones that are replatforming, they are taking advantage of the platform as a service or software as a service, so that includes things like, you pay as you go, you pay for exactly the amount you use, so you scale up and scale down or scale out and scale in, pretty quickly, you know? So you're handling that demand, so without replatforming, you are not really utilizing your- >> John: It's just hosting. >> Yeah, you're just hosting. >> It's basically hosting if you're not doing anything right there. >> Right. The reason why people sometimes resist to replatform, is because there's a hidden cost that we don't really talk about, PaaS adds 3x to IaaS cost. So, some organizations that are very mature, and they have a few thousand people in the IT department, for them, they're like "No, we just want to run it in the cloud, we have the expertise, and it's cheaper for us." But in the long run, to get the most benefit, people should think of using cloud as a service. >> Nong what's your take, because you see examples of companies, I'll just call one out, Snowflake for instance, they're essentially a data warehouse in the cloud, they refactored and they replatformed, they have a competitive advantage with the scale, so they have things that others don't have, that just hosting. Or even on-premise. The new model developing where there's real advantages, and how should companies think about this when they have to manage these data lakes, and they have to manage all these new access methods, but they want to maintain that operational stability and control and growth? >> Yeah, so. No? Yeah. >> There's a few topics that are all (indistinct) this topic. (indistinct) enterprises moving to the cloud, they do this maybe for some cost savings, but a ton of it is agility, right? The motor that the business can run at is just so much faster. So we'll work with companies in the context of cloud migration for data, where they might have a data warehouse they've been using for 20 years, and building policies over that time, right? And it's taking a long time to go proof of access and those kind of things, made more sense, right? If it took you months to procure a physical infrastructure, get machines shipped to your data center, then this data access taking so long feels okay, right? That's kind of the same rate that everything is moving. In the cloud, you can spin up new infrastructure instantly, so you don't want approvals for getting policies, creating rules, all that stuff that Sanjeev was talking about, that being slow is a huge, huge problem. So this is a very common environment that we see where they're trying to do that kind of thing. And then, for replatforming, again, they've been building these roles and processes and policies for 20 years. What they don't want to do is take 20 years to go migrate all that stuff into the cloud, right? That's probably an experience nobody wants to repeat, and frankly for many of them, people who did it originally may or may not be involved in this kind of effort. So we work with a lot of companies like that, they have their, they want stability, they got to have the business running as normal, they got to get moving into the new infrastructure, doing it in a new way that, you know, with all the kind of lessons learned, so, as Sanjeev said, one of these big banks that we work with, that classical story of on-premise data warehousing, maybe a little bit of Hadoop, moved onto AWS, S3, Snowflake, that kind of setup, extremely intricate policies, but let's go reimagine how we can do this faster, right? What we like to talk about is, you're an organization, you need a design that, if you onboarded 1000 more data users, that's got to be way, way easier than the first 10 you onboarded, right? You got to get it to be easier over time, in a really, really significant way. >> Talk about the data authorization safety factor, because I can almost imagine all the intricacies of these different tools creates specialism amongst people who operate them. And each one might have their own little authorization nuance. Trend is not to have that siloed mentality. What's your take on clients that want to just "Hey, you know what? I want to have the maximum agility, but I don't want to get caught in the weeds on some of these tripwires around access and authorization." >> Yeah, absolutely, I think it's real important to get the balance of it, right? Because if you are an enterprise, or if you have diversive teams, you want them to have the ability to use tools as best of breed for their purpose, right? But you don't want to have it be so that every tool has its own access and provisioning and whatever, that's definitely going to be a security, or at least, a lot of friction for you to get things going. So we think about that really hard, I think we've seen great success with things like SSO and Okta, right? Unifying authentication. We think there's a very, very similar thing about to happen with authorization. You want that single control plane that can integrate with all the tools, and still get the best of what you need, but it's much, much easier (indistinct). >> Okta's a great example, if people don't want to build their own thing and just go with that, same with what you guys are doing. That seems to be the dots that are connecting you, Sanjeev. The ease of use, but yet the stability factor. >> Right. Yeah, because John, today I may want to bring up a SQL editor to go into Snowflake, just as an example. Tomorrow, I may want to use the Azure Bot, you know? I may not even want to go to Snowflake, I may want to go to an underlying piece of data, or I may use Power BI, you know, for some reason, and come from Azure side, so the point is that, unless we are able to control, in some sort of a centralized manner, we will not get that consistency. And security you know is all or nothing. You cannot say "Well, I secured my Snowflake, but if you come through HTFS, Hadoop, or some, you know, that is outside of my realm, or my scope," what's the point? So that is why it is really important to have a watertight way, in fact I'm using just a few examples, maybe tomorrow I decide to use a data catalog, or I use Denodo as my data virtualization and I run a query. I'm the same identity, but I'm using different tools. I may use it from home, over VPN, or I may use it from the office, so you want this kind of flexibility, all encompassed in a policy, rather than a separate rule if you do this and this, if you do that, because then you end up with literally thousands of rules. >> And it's never going to stop, either, it's like fashion, the next tool's going to come out, it's going to be cool, and people are going to want to use it, again, you don't want to have to then move the train from the compliance side this way or that way, it's a lot of hassle, right? So we have that one capability, you can bring on new things pretty quickly. Nong, am I getting it right, this is kind of like the trend, that you're going to see more and more tools and/or things that are relevant or, certain use cases that might justify it, but yet, AppSec review, compliance review, I mean, good luck with that, right? >> Yeah, absolutely, I mean we certainly expect tools to continue to get more and more diverse, and better, right? Most innovation in the data space, and I think we... This is a great time for that, a lot of things that need to happen, and so on and so forth. So I think one of the early goals of the company, when we were just brainstorming, is we don't want data teams to not be able to use the tools because it doesn't have the right security (indistinct), right? Often those tools may not be focused on that particular area. They're great at what they do, but we want to make sure they're enabled, they do some enterprise investments, they see broader adoption much easier. A lot of those things. >> And I can hear the sirens in the background, that's someone who's not using your platform, they need some help there. But that's the case, I mean if you don't get this right, there are some consequences, and I think one of the things I would like to bring up on next track is, to talk through with you guys is, the persona pigeonhole role, "Oh yeah, a data person, the developer, the DevOps, the SRE," you start to see now, developers and with cloud developers, and data folks, people, however they get pigeonholed, kind of blending in, okay? You got data services, you got analytics, you got data scientists, you got more democratization, all these things are being kicked around, but the notion of a developer now is a data developer, because cloud is about DevOps, data is now a big part of it, it's not just some department, it's actually blending in. Just a cultural shift, can you guys share your thoughts on this trend of data people versus developers now becoming kind of one, do you guys see this happening, and if so, how? >> So when, John, I started my career, I was a DBA, and then a data architect. Today, I think you cannot have a DBA who's not a developer. That's just my opinion. Because there is so much of CICD, DevOps, that happens today, and you know, you write your code in Python, you put it in version control, you deploy using Jenkins, you roll back if there's a problem. And then, you are interacting, you're building your data to be consumed as a service. People in the past, you would have a thick client that would connect to the database over TCP/IP. Today, people don't want to connect over TCP/IP necessarily, they want to go by HTTP. And they want an API gateway in the middle. So, if you're a data architect or DBA, now you have to worry about, "I have a REST API call that's coming in, how am I going to secure that, and make sure that people are allowed to see that?" And that was just yesterday. >> Exactly. Got to build an abstraction layer. You got to build an abstraction layer. The old days, you have to worry about schema, and do all that, it was hard work back then, but now, it's much different. You got serverless, functions are going to show way... It's happening. >> Correct, GraphQL, and semantic layer, that just blows me away because, it used to be, it was all in database, then we took it out of database and we put it in a BI tool. So we said, like BusinessObjects started this whole trend. So we're like "Let's put the semantic layer there," well okay, great, but that was when everything was surrounding BusinessObjects and Oracle Database, or some other database, but today what if somebody brings Power BI or Tableau or Qlik, you know? Now you don't have a semantic layer access. So you cannot have it in the BI layer, so you move it down to its own layer. So now you've got a semantic layer, then where do you store your metrics? Same story repeats, you have a metrics layer, then the data centers want to do feature engineering, where do you store your features? You have a feature store. And before you know, this stack has disaggregated over and over and over, and then you've got layers and layers of specialization that are happening, there's query accelerators like Dremio or Trino, so you've got your data here, which Nong is trying really hard to protect, and then you've got layers and layers and layers of abstraction, and networks are fast, so the end user gets great service, but it's a nightmare for architects to bring all these things together. >> How do you tame the complexity? What's the bottom line? >> Nong? >> Yeah, so, I think... So there's a few things you need to do, right? So, we need to re-think how we express security permanence, right? I think you guys have just maybe in passing (indistinct) talked about creating all these rules and all that kind of stuff, that's been the way we've done things forever. We get to think about policies and mechanisms that are much more dynamic, right? You need to really think about not having to do any additional work, for the new things you add to the system. That's really, really core to solving the complexity problem, right? 'Cause that gets you those orders of magnitude reduction, system's got to be more expressive and map to those policies. That's one. And then second, it's got to be implemented at the right layer, right, to Sanjeev's point, close to the data, and it can service all of those applications and use cases at the same time, and have that uniformity and breadth of support. So those two things have to happen. >> Love this universal data authorization vision that you guys have. Super impressive, we had a CUBE Conversation earlier with Nick Halsey, who's a veteran in the industry, and he likes it. That's a good sign, 'cause he's seen a lot of stuff, too, Sanjeev, like yourself. This is a new thing, you're seeing compliance being addressed, and with programmatic, I'm imagining there's going to be bots someday, very quickly with AI that's going to scale that up, so they kind of don't get in the innovation way, they can still get what they need, and enable innovation. You've got cloud migration, which is only going faster and faster. Nong, you mentioned speed, that's what CloudOps is all about, developers want speed, not things in days or hours, they want it in minutes and seconds. And then finally, ultimately, how's it scale up, how does it scale up for the people operating and/or programming? These are three major pieces. What happens next? Where do we go from here, what's, the customer's sitting there saying "I need help, I need trust, I need scale, I need security." >> So, I just wrote a blog, if I may diverge a bit, on data observability. And you know, so there are a lot of these little topics that are critical, DataOps is one of them, so to me data observability is really having a transparent view of, what is the state of your data in the pipeline, anywhere in the pipeline? So you know, when we talk to these large banks, these banks have like 1000, over 1000 data pipelines working every night, because they've got that hundred, 200 data sources from which they're bringing data in. Then they're doing all kinds of data integration, they have, you know, we talked about Python or Informatica, or whatever data integration, data transformation product you're using, so you're combining this data, writing it into an analytical data store, something's going to break. So, to me, data observability becomes a very critical thing, because it shows me something broke, walk me down the pipeline, so I know where it broke. Maybe the data drifted. And I know Okera does a lot of work in data drift, you know? So this is... Nong, jump in any time, because I know we have use cases for that. >> Nong, before you get in there, I just want to highlight a quick point. I think you're onto something there, Sanjeev, because we've been reporting, and we believe, that data workflows is intellectual property. And has to be protected. Nong, go ahead, your thoughts, go ahead. >> Yeah, I mean, the observability thing is critically important. I would say when you want to think about what's next, I think it's really effectively bridging tools and processes and systems and teams that are focused on data production, with the data analysts, data scientists, that are focused on data consumption, right? I think bridging those two, which cover a lot of the topics we talked about, that's kind of where security almost meets, that's kind of where you got to draw it. I think for observability and pipelines and data movement, understanding that is essential. And I think broadly, on all of these topics, where all of us can be better, is if we're able to close the loop, get the feedback loop of success. So data drift is an example of the loop rarely being closed. It drifts upstream, and downstream users can take forever to figure out what's going on. And we'll have similar examples related to buy-ins, or data quality, all those kind of things, so I think that's really a problem that a lot of us should think about. How do we make sure that loop is closed as quickly as possible? >> Great insight. Quick aside, as the founder CTO, how's life going for you, you feel good? I mean, you started a company, doing great, it's not drifting, it's right in the stream, mainstream, right in the wheelhouse of where the trends are, you guys have a really crosshairs on the real issues, how you feeling, tell us a little bit about how you see the vision. >> Yeah, I obviously feel really good, I mean we started the company a little over five years ago, there are kind of a few things that we bet would happen, and I think those things were out of our control, I don't think we would've predicted GDPR security and those kind of things being as prominent as they are. Those things have really matured, probably as best as we could've hoped, so that feels awesome. Yeah, (indistinct) really expanded in these years, and it feels good. Feels like we're in the right spot. >> Yeah, it's great, data's competitive advantage, and certainly has a lot of issues. It could be a blocker if not done properly, and you're doing great work. Congratulations on your company. Sanjeev, thanks for kind of being my cohost in this segment, great to have you on, been following your work, and you continue to unpack it at your new place that you started. SanjMo, good to see your Twitter handle taking on the name of your new firm, congratulations. Thanks for coming on. >> Thank you so much, such a pleasure. >> Appreciate it. Okay, I'm John Furrier with theCUBE, you're watching today's session presentation of AWS Startup Showcase, featuring Okera, a hot startup, check 'em out, great solution, with a really great concept. Thanks for watching. (calm music)

>>Hold on. Welcome to this special cube conversation. I'm John ferry, host of the queue here in Palo Alto, California. Got a great deep dive conversation with multicloud, who we were featuring on our AWS showcase of cloud startups. Uh, Venkat Krista who's the CEO. And co-founder great to see you again and Candace Hendrix delivery architect at green pages, a partner customer. Great to see you. Thanks for coming on as always cube conversations are fun to get the deep dive. Good to see you. >>Oh, great to have, uh, have this opportunity, John. Thank you so much. Uh, Candace, thank you for joining us. It's been a pleasure work in pages, John, we're looking forward to this conversation today. >>Yeah. One of the things I'm really excited about that came out of our coupon cloud startups showcase was you guys talking about day two operations, which has been kicked around, but you guys drilled into it and put some quantification around the value proposition, but this is every company has a day to problem an opportunity and then usually our problems and most people see, but they're really opportunities to create this value proposition around something that's now going to be an operational, um, standard table-stakes. So let's get into it, take us through, uh, what you guys have with day two offers that, do a deep dive on this. Take, take it away. >>Thanks, John. Uh, John, we'll do a little bit of an involved conversation today. We'll switch between a little bit of a slide and, um, we are actually happy to show a quick demo as well. So our customers can, uh, what they see is what they get kind of demo. Um, so, uh, to give a quick background on context a day, two operations in the cloud are important for customers who are trying to get, uh, self-service provisioning, going standardization going, uh, have a way to help their developers move fast on the innovation. What we are experiencing now is developers are increasingly having a seat at the table and they would like their infrastructure architects and infrastructure solution providers to enable them to do things that they want to do with fewer friction points. What day two platform that we built does is it upskills our it teams so that they can deli work, uh, what the developers need so that the sandbox environments that they want comes to life quickly. >>And on top of that, developers can move fast with the innovation with guard rails that are in place, the guard rails that are it, administrators, it leaders are able to set for developers, include cost guard, rails, governance, guard, rails, security, and compliance guard rails, a, you know, bot based approach to getting out of the way of the developers so they can move fast while the, uh, technology provides them the Alcoa to go innovate without running into the common cloud problems, such as cost overruns or security or compliance challenges today, I'll go show and tell a little bit of all of this, and then we'll bring in partners or partner, canvas as well, so that she can talk about how we help the fortune 200, uh, innovate, uh, faster with our platform. >>Awesome. Well, let's get into it. I, you know, as you know, I, I think that day two operations is really a cloud, uh, lingua. Frank was going to be part of everyone's, uh, operational standard. And it's not just for making sure you've got cost-effectiveness, but innovation strategies that rely on cloud, they need to have new things in place. So take us through the show and tell. >>Great, well, let's switch to the slide deck here. So I'm going to give a quick background and then go from there. Great. So, um, uh, you know, Montclair is an intelligent cloud man and platform company. We help customers of all sizes. Uh, we are an AWS partner that is a cloud management tool, competency partner, super happy to be in a wedding on the AWS platform for AWS customers. Our platform is an autonomous cloud operations platform. What our mission is, we empower ID teams to go deliver to their developers and become cloud powerhouses. Uh, I'm going to go through a quick three sections of the Manticore platform that delivers value to our customers first with our platform without needing additional skillsets or hiring, uh, needing to hire, uh, you know, hard to find talent or having to use third party tools. Our customers can use AWS native solutions to achieve full visibility into their cloud environments. >>They can enable consistent self-service deployments and simplify them. They can also reduce the total cost of cloud operations, all in just a few clicks. Uh, I'm going to show and tell, uh, what customers get quickly moving into the slide where customers can get visibility into the footprint, a comprehensive security posture management and compliance posture management, click away and solve these problems. They can enable their innovation teams with operations ready environments that can provision anything from server-based workloads to serverless workloads, to containerized environments. All of that are available readily in the platform. And of course, uh, all of this can be done with a few clicks and no code. That's our platform. And a nutshell I'm happy to switch to a demo from here on John. How does that sound >>Great. Sounds awesome. Let's get the demo. Thanks for the overview. By the way, we cover that in a great video too, and a high level, um, in our new show startup showcase, people can check that out online, um, check it out, but let's get into the demo. >>Sounds good. So I'm going to switch to my laptop again here to show the browser window and go into the demo environment. Great. So this is Monte cloud.com. Uh, customers can go to app.monica.com. I'm going to move fast in a demo environment show and tell here, uh, customers split login, assuming they have signed up for the platform. It's free to sign up. Uh, the platform activates immediately. This is their full first run experience. Uh, customers can get started in about a couple of clicks. There's a welcome screen here. They can walk through this. What this provides is a way a guard had experience for customers to be able to gain visibility, security, compliance, and set up the cloud operations, uh, environment in just a couple of clicks. So in this case, customers can get continuous resource visibility. They click next from a security point of view, we'll assess about 2,220 plus security best practices and customers can select saying they would like to remediate the issues. >>We'll help do that. That's a bot based approach that does it click next compliance, a similar situation. We do compliance assessments in the platform. Customers can remediate it. Uh, click next. We have provisioning templates, John. We had a really good conversation yesterday about this, a whole set of, uh, well-architected, uh, templates that customers can click and provision anything from, uh, basic core networking, all the way up to high performance computing and minds that all is available in the platform. Again, click next to go select that customers can manage servers, windows, or Linux servers running on any cloud could be hybrid cloud, uh, Azure, AWS GCP. Again, we can manage them in a single interface and last but not the least application management, our ID operators and leaders want to have a position on how their cloud applications are performing. They want to react quickly to it best possible platform. Uh, that's it they've selected all the features. All the, which is free in the platform. Some features are available in the free trial. Customers can click and say they would like to try for 14 days. That's all. So click next platform sets itself up. This is how quick we can get to helping customers understanding what they need to do. I'm going to try and show you if I can go to the next screen here and say, this is my company name. >>So I'm going to enter some details here that, uh, helps, um, capture some basic information about, uh, our customers, uh, departments. Uh, let's say this is a demo account, or I'm going to say, um, HR, um, uh, account, let's say there's a human resources department that I'm trying to connect and manage their cloud environment, but click next >>And that's it. They connect to the AWS account. We now take our customers back to an AWS console where they're familiar interface. They're going to click next on this cloud formation stack here, which automatically starts creating what we need on the customer's account. And click, click a button here. It's going to run in the background, what my platform in this case, my view, the other view does is, uh, it instantly receives notification back from the customer's account. As you can see now, day two has recognized that, Hey, the customer is trying to connect the cloud account. It's a question. Do you want to manage these regions? We can manage 15 plus regions click next. Uh, that is pretty much it. Uh, I'm going to skip this one so that we can get to the dashboard. I'm going to skip this as well, because you can invite your team members. Uh, you can get weekly reports, uh, long story short, that's it about 10 clicks. We are already in, in a cloud environment where customers can begin to manage, operate and start taking control of the cloud footprint. >>Got it. And physical you, you skipped over the collaboration feature that's for what team members do. Kind of see the same dashboard. >>The great question. Uh, our customers can invite additional team members could be an educator who wants to look at the total cost of cloud operations. Uh, they could invite another team member who wants to be enabled only for certain parts of the platform. Very simple. We have SSO integration as well in the platform. So, uh, invite additional users start using day two in less than 10 minutes, no additional, uh, you know, configuration required. >>You know, Amazon's got that slogan always day one. You guys are always day to always go to >>About all about ensuring data was taken care of. >>Awesome. Great stuff. Candace, what's your take on this? How do you fit in here? Talk about what it's like to work with these guys. What's the, what's your perspective on this? A new multicloud day two operations dashboard. >>Hi, thank you, John. Hi, Ben Kat. Thank you very much for the introduction. Um, basically our interaction is collaborative and we're great team partners, and we work well with, with multicloud often and, and have been partners working together for quite some time and solutioning products for our clients. >>Great. Vinca you want to chime in as well and share some color commentary on, um, your partners value? >>Sure. Thanks Justin. So, uh, so green pages, uh, they offer cloud services and a whole suite of solutions to their customers. Some of the customers are ranging from fortune a hundred enterprises, uh, to a wide variety of customers. Perhaps we can actually switch over to a slide deck here, but Candace, if you're up for it, maybe we can walk through a liberal green pages and solutions that you've implemented. We can talk from the customer point of view, which we think would be more beneficial to our audience as well. >>Yes. Thank you. That's very helpful. Um, again, my name is Candice Hendrix and I'm a delivery architect here at green pages technology solutions. And what I'd like to do is share a few examples of collaboration that we have achieved through our partnership with Moni cloud first to give a better history of green pages we've been in business since 1992, we maintain a wide range of customer base, um, approximately 500 different, uh, customers and all different workflows from insurance to government to, um, um, manufacturing and the such. We've also made the CRN tech elite two 50 less for, uh, sense its inception in 2011. And basically what that is, is it's all of the companies and, or the top 250 companies in the U S and Canada, having the highest level of experience top of their game, maintaining the highest levels of training and certifications. We also offer managed services, support, professional services, cloud readiness assessments, and migrations, as well as growing a CSP or cloud service provider today, I would like to highlight a few innovative projects that we've executed with multicloud is our partner for AWS compliance needs as well as, um, AWS Dr. >>So this slide first outlines a business scenario that we dealt with with one of our clients to address cost security compliance standardization across a global AWS environment. And the challenge with this was that we experienced was the complexity of the cloud environment and the size of the environment and how can they stay compliant, optimize costs and scale the outcome with the teamwork of Mani cloud and green pages, we were able to achieve all the facets of the challenge, also enabling and, and creating what we coined it, the compliance bot and what that provided was a platform to easily parameterize some of the, um, options such as configurable schedules, configurable target servers, departments, um, options to choose between automated and manual remediation processes in compliance ability to choose whether that remediation process also, uh, auto reboots versus approval based reboots on, um, infrastructure or resources integrations into a Slack channel for manual remediation approval process, as well as daily noncompliance reporting the compliance bot also can ensure proper patching necessary agents required software versions and resources, um, that they maintain compliance through the use of tagging Lambda functions, AWS fleet manager, AWS config, and AWS CloudWatch. >>Uh, another, um, opportunity we've had to work with, um, Moni cloud in this use case, the scenario that the green pages customer needed to solve was the automation of Dr to address the requirement of an entire AWS regional failure within requirements was a RTO of four hours and an RPO of less than one minute uncertain ESE, two instances. So the challenge that we had was to develop this solution with only the use of AWS native services meeting the required RTO and RPO with no custom tooling integration. So with mighty clouds assistance and teamwork, what we were able to achieve is what we now refer to as the Dr. Bot, we solution the automation to replicate everything from their production, uh, environment in AWS to the Dr. Region in AWS, such as subnets, um, IP cider ranges, LAN IP addresses, security groups, load balancers, and all associated configuration settings. >>So with the pilot light scripting that runs daily through a Lambda function, we can manage those Delta copies into the Dr production or the Dr. Region from production and address any changes that may occur in the production environment to meet the RPO. What we used is cloud door, which is also a native AWS service. And we used AWS backup for the more static instances, we then created an integration to send any health alerts in the event of an AWS outage to their Slack channel. Then upon approval, um, they could kick off through a manual approval process. They could kick off and execute an end to end fail over from production to an AWS region and to their Dr. Region in AWS, both the compliance spot and the Dr. Bot automations can be ported and variabilize for any AWS environment. We welcome the opportunity to discuss this further and assist you in your cloud journey. I hope this explain some of the great innovation that we've been able to work with money cloud on. Thanks, Ben Capra, allowing me to speak and back to you. >>Thank you, Candace. This is fantastic. John Lassie Seesaw, right? The challenge with cloud operations is there's a lot of moving parts and, uh, visibility, compliance, security, uh, you know, all of that. Typically customers have to write custom code or integrate ten-plus tools, suddenly what, you know, customers we're seeing they're spinning up their own cloud operating teams. They're spinning up their own homegrown cloud operations model, which in invariably results in more attacks, symptoms of maintenance tasks, our platform can do all of this abstract, the complexity, and put this kind of automation within the reach of customers who are trying to transform their it departments by clicking away. That's the attack that we built on top. >>Yeah, I think that's a great example. I think Candace highlights some of the things we were talking about last time around intelligent applications, meeting, intelligent infrastructure, and to your point about operations, this comes up huge all the time in every conversation we're in and we're seeing it in the marketplace where there's a new operational model developing in real time. You're seeing people, um, homegrown ops, transforming ops. I mean, there's new roles and responsibilities are emerging and that's just the nature of the beast right now. This is kind of the new normal that it's not your traditional ops model. It's transitioning to a new, new way. This is a great example. Um, you see that the same way? >>Well, that's a, that's a great description, John you're right. That is the model that is evolving that, uh, once, um, that demands more from it teams and on the runway that is shrinking to transform and the cloud surface, it has grown how that's exactly where the becoming to help. And, uh, uh, we did do a little bit of a deep dive into what the platform does today to talk to our audience so that they can get this value. Thank you for that. Uh, you know, uh, depth in diving, happy to chat a little bit more if you'd like about, uh, where customers could go and that they can get started. >>Yeah. Looking forward to it. Vanco. Thanks for coming on, Candace. Thank you very much for sharing. Um, green pages. Congratulations. Love the Dr. Bot. That's phenomenal. I mean, I w I want a cube bottom. You're just doing these interviews is boss, but I'm looking forward to having a follow on conversation vanco. We're going to certainly see you out on the internet on Twitter. Um, maybe get you on our clubhouse, uh, chats, a lot of action out there. A lot of people talking about this, and you're seeing things from observability to new kinds of monitoring, to modern application development techniques that are just evolving in real time. So day two is here. Thanks for sharing. >>Looking forward, John, and, uh, where customers could go to is they could go to montclair.com today. They could get started in just a few place. We have a free version on the platform. They can activate this account in 10 months. They now have the power of the automation that we've built, and they can start taking control of the cloud operations in about 10 minutes. So we encourage persons to go find some free monitor.com and thank you candidates for taking the time, uh, uh, does it's fantastic that we'll be able to go solve some problems together. >>Mazi cloud turning teams into cloud powerhouses. That's their slogan. Check them out. I'm John Farrar with the cube. Thanks for watching.

(upbeat music) >> Hi, and welcome to theCUBE, the leading source for insights into the world of technology and innovation. I'm your host, Donald Klein and today's topic is the exploding software segment of Robotic Process Automation, where Automation Anywhere is one of the leading providers. To have that conversation today, I'm joined by Riadh Dridi, CMO of Automation Anywhere. Welcome to the show, Riadh. >> Thank you for having me. >> Great, okay so, look, you're relatively new to Automation Anywhere, is that correct? >> Yes, I've been there for about six months now. >> Excellent, so why don't you talk a little bit about your background and how you came to the world of RPA. >> Yes, so I've been in the IT industry for about 20 years, been in the hardware space and the software space and the cloud space more recently, so when I heard about Automation Anywhere in the RPA space, did my due diligence and find out how fast this technology was catching on in enterprises, I got really, really excited and then met the management team and then get even more excited and ended up, you know, taking the job. >> Well, congratulations. >> Thank you. >> It's an exploding segment, for sure. Why don't you talk to us a little bit about what you see happening in this market and how fast it's growing. >> Yeah, so there are many studies out there, and of course we have our own internal data, but the market right now, according to Gartner is growing about 63% year over year, is the fastest growing enterprise software market in the industry right now and is projected to continue to grow at that pace for the foreseeable future. >> Okay, and let's talk about, sort of for people who are not that familiar with RPA. It's obviously an acronym that's being, you know, tossed around a lot but, you know, talk to us about Robotic Process Automation and how you define that category. >> Right, so that was one of the challenges early on is to try to put the label on this segment, which is really about automating processes end-to-end as much as possible, and so the RPA category is where, you know, some of the analysts decided to focus on, and so what it does is really allow businesses to deploy software robots to business processes so that process can be handled by bots instead of humans. The mundane, repetitive tasks that humans do as part of the end-to-end process, whether it's a order to cash process or procure to pay process, any, frankly, business process that things, that humans should not be doing, should be better suited to do more creative work. That's when, you know, bots came into play and the whole category was named, Robotic Process Automation because the robots are taking the place of the humans, in that terms of process automation. >> Got it, okay, so (mumbles) of the bots, so creating bots, right, and what's kind of fascinating about this world is that, you know, for customers that deploy this type of solution, right, they're growing a whole library of bots, right (mumbles). Maybe just walk us through an example bot and what a bot does and why this technology is so unique. >> Right, so think about, first of all, the problem that those bots are solving, right? So today you have ERP applications, CRM applications, any sort of applications in businesses to really automate a process, like I said an order to cash process, procure to pay process. That's why people have bought the technology, but what the industry has realized is after twenty years or more of using the same technology, humans were still doing part of the process that should have been automated by the software. So when you look at the average enterprises, only 20% of the steps that should be automated are automated, 80% of it is done by humans, whether it's opening files, reading documents, cutting and pasting, filling out forms, you know, playing with excel and kind of loading data into systems, data entry, a lot of it is still done by humans. So what the bots do is go in and take that work away from the humans so they can really focus on better tasks. That's really what it is. >> And so, just so everybody's kind of clear, so what's really so intelligent about these capabilities, right, take something sort of like invoices, right? Any company, you know, receiving lots and lots of invoices, all these invoices are going to be formatted in different ways. >> Right. >> Correct? >> Right. >> And historically it's been up to a human to kind of look through that invoice, pull out the relevant pieces of information, right, and enter that into the system so that the system can then issue the PO or pay the PO, et cetera, right? >> Exactly. >> But what your bots can do, or what the space as a whole, right, is they can intelligently scan these documents, and look for the kind of pieces of information, and actually load those into the system, correct? >> That's exactly right. So what the bots are doing now with computer vision, they're able to look into applications, they're able to assess the data, they're able to assess the information from that data and then process it like humans would do. So they're able to, again, get in, look at invoices or any type of, frankly, unstructured data or semi-structured data, and take that data, analyze it, and then manipulate it like a human would do. >> Excellent. >> An exception is that they are, obviously, doing it 24/7, much faster, with less errors. >> Got it, right. So you're turning people who, previously may have been focused on kind of a data entry task, right, into kind of managing a process, right? >> Exactly. So basically, what we like to say is we are taking the robot out of humans and then giving it to the robots, who are supposed to be doing the work. >> Excellent. >> And that's kind of phase one, and then phase two is obviously making those robots more intelligent, so that they're not able to do the simplest of simplest tasks, but start to be a little bit more intelligent and use AI to do things that are a little bit more advanced and more complicated. >> Okay, excellent. So look, you guys have got some news, right? >> Yup. >> You've kind of just come out with a big new release of your platform. Why don't you just kind of talk us through what the news is and what you guys have released? >> Yeah, so if you think about what the space has done so far, is taking a process, that's usually a known process, like I said, an order to cash, or even a simpler process, right? And taking look at the different steps and tasks that people have to do, and say, let's now automate those tasks and that particular process. A lot of the time is spent on trying to figure out their process. I don't know about your company, but I know in a lot of companies that I've been at, a lot of processes are not documented. So what we've announced yesterday is a bot, we call this Discovery Bot, that allows us to discover the processes that people work with. So if you're, again, an agent or a knowledge worker in an organization, you're going through a certain number of steps. The bot is going to basically analyze all those different steps, map the process, allows you to understand the flow that you're going through, and let you know that if you automate those repetitive tasks within your process, you're going to be able to save a certain amount of time and energy and have a better process in place. And then the cool thing about what we announced yesterday, and this is unique in the industry today, is the ability to create bots automatically from analyzing that process. So again, the industry has matured into analyzing processes manually, or using certain tools, but then the work had to be done by a different platform to basically create the bots from these processes. We're the only provider today that can analyze processes with the tool, and then create the bots automatically, shrinking the time for process automation end-to-end. >> Fantastic. >> Okay, and now, but also part of this release, too, right, is your kind of cloud capabilities. You've really kind of ramped up your ability to scale for the kind of largest customers. Talk a little to us about how the application functions in the cloud, how it functions on-prem. How does that all work end-to-end? >> Right, so back in November we announced the new platform called Enterprise A2019. This was the first cloud native web-based platform in the industry. And the reason why cloud native is important is because it's what gives you the benefits, in terms of scaling, in terms of TCO, in terms of easy to use, and that platform is now the core platform for the company, and so the product announcement we had yesterday allows our customers to use the same platform, except now we add this Discovery Bot at the front-end to discover the process, prioritize them, and then use the platform we've announced to automate these processes. What's very interesting about the platform is that customers can use it on-prem, can use it in the cloud. The customers, obviously, that decide to use it in the cloud will have the ability to learn more from the platform because, you know, it's going to tackle a lot more data in the cloud. Then we're going to be able to use lots of data analysis tools to be able to get the customers to extract knowledge from it and then innovate a much faster way. The people who are going to be using it on-prem, typically, are regulated industries or customers who have systems of records that are, typically, on-prem and they would like the bots to run where the systems are. So the platform is available in the cloud. It's available on-prem. It's the customer's choice to decide how to use it, but the innovation that's backed into it is what's really exciting. >> So this is kind of, I think, a fundamental point, maybe people should understand, right? So what you're, this is kind of a brave new world, right? You're saying kind of cloud native app, right, which is now ready to be used on-prem, right? >> Right >> As opposed to maybe the older world where people develop applications that were primarily based for kind of a server architecture within the firewall, right? >> Exactly. >> And then they tried to migrate it to the cloud? >> Exactly. >> So in some sense, you've done the reverse. >> Exactly. So if you were to build an application today knowing, you know, microservices architecture, knowing Java, knowing web-based, that's how you would build it. And so the fact that you've built the architecture for a modern application and then offer the options to customers to use it, either on-prem or in the cloud, is what we've done. >> Got it, great. Okay, so then what's the advantage of being able to use, so you've got this application that can scale with microservices, right? It can handle the volume that a Fortune 500 company might need. What's the advantage for them being able to do it on-prem? What does that help? >> So for some customers, it's really about regulating industries. For example, if you're a bank, or if you're a healthcare institution, the data cannot travel through the cloud. So systems of records, whether it's a CRM, whether it's HRM with some other systems of records, an ERP, usually will be on-prem and the data can travel through the cloud. So for these customers, we're saying, use the product on-prem, you have the same benefit. It's still the cloud architecture, microservices-based. It's still web-based as far as the client interface is concerned. It's the lowest TCO you can get, but you don't have to worry about getting to the cloud if that's what you decide to do. >> So, in terms of enabling digital transformation, really the requirement here is to be able to enable that both in the cloud and on-prem and do it simultaneously. >> Correct, and again, some customers will do a hybrid of both and then say, for these workflows we'll have them in the cloud, for these we'll keep them on-prem. Some customers in regulated industries will say, we don't want to do anything in the cloud, we want everything on-prem. They'll have the choice to do that. >> Understood, okay, well look, final question here. Let's talk about kind of some of the upcoming events that Automation Anywhere has going on, right? You do events all across the globe, you're now a global company. Tell us what's happening on that front. >> Yeah, so we do lots of events, you know, cause our customers are global, where we have customers in 90 countries, we have offices in 45 countries, and so we have to go where our customers are. So we have four large conferences throughout the year, one upcoming in London, we have it in Vegas, in Tokyo, and in Bangalore, as well. And it's the largest gathering of RPA minds and experts in the industry today. So what's exciting about the one that's coming up is, obviously, Discovery Bot is going to be featured at that conference. People will be able to play with the product, they'll be able to understand, you know, the latest innovations from Automation Anywhere. We have sessions that are called Build a Bots where people will be able to build their bots on-site, and that's always a popular thing for people to do. And then we're going to have some amazing speakers and top leaders who will help customers understand, you know, what's happening in digital transformation, and how intelligent automation can accelerate that transformation. >> Okay, great, and so just to understand the timing of it, so you've got a show coming up in London in the very near future here, is that right? >> Yes, I believe it's in April and then we have another one in May in Las Vegas. >> Okay, so then the big one in North America is going to be Vegas this year? >> Correct, correct, it's in May. >> Okay, great. And then, what about the, so then you also talked about Bangalore, talk about -- >> Yeah, Bangalore, I don't have all the dates in my head, so I apologize, but I think Bangalore is, I believe, in August or September, and then Tokyo, I believe, it's in June, so I'll have to confirm all those dates -- >> But one of the unique things, right, is that Bangalore show has actually been one of your largest shows of the year. >> It's been amazing. So I literally missed that show by one week. When I joined the company, I was super excited about having the ability to go visit the customers and the partners within the show. I think last year they had 6000 people, so it's an amazing opportunity this year to go see it first-hand. I don't know what the audience is going to be like, I'm assuming it's going to be more than 6000, but feeling the energy and the excitement from attendees is what I'm really looking forward to. >> Well, that just shows, right, that the software industry, particularly cloud-enabled software industry, is now a global industry, right? >> It is, it is, absolutely, because again, cloud allows those barriers to entry for companies, wherever they are, to be lowered, and customers in different regions can have the latest, greatest directly from the cloud and they both use the product, you know, when it comes out, and so that's, obviously, a super big advantage. The other thing I should be (mumbles) if I didn't say, you know, because it's also available in the cloud, and it's web-based, it's easy to use, easy to access, a lot of our first-time customers are business users. They're not even IT people, so they just go in, start playing with the product, you know, automating a few processes, and then start to scale end-to-end, and then of course they build the COE, IT gets involved. So being able to start your automation journey as small, and then grow as you scale from any parts of the world is really what this opportunity gives us. >> Okay, well thank you for your time today, Riadh. I'm fascinated, everything you guys are doing. Super hot category for those folks out there that want to touch base with Automation Anywhere, shows in London, Vegas, Bangalore, and then where was the fourth one? >> I think Tokyo -- >> Tokyo. >> And then Bangalore after that, yes. >> Okay, fantastic. >> Yes. >> Thanks for joining us today. This is Donald Klein, I'm the host of theCUBE. I'll see you next time. (upbeat music)

(upbeat music) >> Hi, and welcome to theCUBE, the leading source for insights into the world of technology and innovation. I'm your host, Donald Klein and today's topic is the exploding software segment of Robotic Process Automation, where Automation Anywhere is one of the leading providers. To have that conversation today, I'm joined by Riadh Dridi, CMO of Automation Anywhere. Welcome to the show, Riadh. >> Thank you for having me. >> Great, okay so, look, you're relatively new to Automation Anywhere, is that correct? >> Yes, I've been there for about six months now. >> Excellent, so why don't you talk a little bit about your background and how you came to the world of RPA. >> Yes, so I've been in the IT industry for about 20 years, been in the hardware space and the software space and the cloud space more recently, so when I heard about Automation Anywhere in the RPA space, did my due diligence and find out how fast this technology was catching on in enterprises, I got really, really excited and then met the management team and then get even more excited and ended up, you know, taking the job. >> Well, congratulations. >> Thank you. >> It's an exploding segment, for sure. Why don't you talk to us a little bit about what you see happening in this market and how fast it's growing. >> Yeah, so there are many studies out there, and of course we have our own internal data, but the market right now, according to Gartner is growing about 63% year over year, is the fastest growing enterprise software market in the industry right now and is projected to continue to grow at that pace for the foreseeable future. >> Okay, and let's talk about, sort of for people who are not that familiar with RPA. It's obviously an acronym that's being, you know, tossed around a lot but, you know, talk to us about Robotic Process Automation and how you define that category. >> Right, so that was one of the challenges early on is to try to put the label on this segment, which is really about automating processes end-to-end as much as possible, and so the RPA category is where, you know, some of the analysts decided to focus on, and so what it does is really allow businesses to deploy software robots to business processes so that process can be handled by bots instead of humans. The mundane, repetitive tasks that humans do as part of the end-to-end process, whether it's a order to cash process or procure to pay process, any, frankly, business process that things, that humans should not be doing, should be better suited to do more creative work. That's when, you know, bots came into play and the whole category was named, Robotic Process Automation because the robots are taking the place of the humans, in that terms of process automation. >> Got it, okay, so everybody talked about the addition of the bots, so creating bots, right, and what's kind of fascinating about this world is that, you know, for customers that deploy this type of solution, right, they're growing a whole library of bots, right you're doing things. Maybe just walk us through an example bot and what a bot does and why this technology is so unique. >> Right, so think about, first of all, the problem that those bots are solving, right? So today you have ERP applications, CRM applications, any sort of applications in businesses to really automate a process, like I said an order to cash process, procure to pay process. That's why people have bought the technology, but what the industry has realized is after twenty years or more of using the same technology, humans were still doing part of the process that should have been automated by the software. So when you look at the average enterprises, only 20% of the steps that should be automated are automated, 80% of it is done by humans, whether it's opening files, reading documents, cutting and pasting, filling out forms, you know, playing with excel and kind of loading data into systems, data entry, a lot of it is still done by humans. So what the bots do is go in and take that work away from the humans so they can really focus on better tasks. That's really what it is. >> And so, just so everybody's kind of clear, so what's really so intelligent about these capabilities, right, take something sort of like invoices, right? Any company, you know, receiving lots and lots of invoices, all these invoices are going to be formatted in different ways. >> Right. >> Correct? >> Right. >> And historically it's been up to a human to kind of look through that invoice, pull out the relevant pieces of information, right, and enter that into the system so that the system can then issue the PO or pay the PO, et cetera, right? >> Exactly. >> But what your bots can do, or what the space as a whole, right, is they can intelligently scan these documents, and look for the kind of pieces of information, and actually load those into the system, correct? >> That's exactly right. So what the bots are doing now with computer vision, they're able to look into applications, they're able to assess the data, they're able to assess the information from that data and then process it like humans would do. So they're able to, again, get in, look at invoices or any type of, frankly, unstructured data or semi-structured data, and take that data, analyze it, and then manipulate it like a human would do. >> Excellent. >> An exception is that they are, obviously, doing it 24/7, much faster, with less errors. >> Got it, right. So you're turning people who, previously may have been focused on kind of a data entry task, right, into kind of managing a process, right? >> Exactly. So basically, what we like to say is we are taking the robot out of humans and then giving it to the robots, who are supposed to be doing the work. >> Excellent. >> And that's kind of phase one, and then phase two is obviously making those robots more intelligent, so that they're not able to do the simplest of simplest tasks, but start to be a little bit more intelligent and use AI to do things that are a little bit more advanced and more complicated. >> Okay, excellent. So look, you guys have got some news, right? >> Yup. >> You've kind of just come out with a big new release of your platform. Why don't you just kind of talk us through what the news is and what you guys have released? >> Yeah, so if you think about what the space has done so far, is taking a process, that's usually a known process, like I said, an order to cash, or even a simpler process, right? And taking look at the different steps and tasks that people have to do, and say, let's now automate those tasks and that particular process. A lot of the time is spent on trying to figure out their process. I don't know about your company, but I know in a lot of companies that I've been at, a lot of processes are not documented. So what we've announced yesterday is a bot, we call this Discovery Bot, that allows us to discover the processes that people work with. So if you're, again, an agent or a knowledge worker in an organization, you're going through a certain number of steps. The bot is going to basically analyze all those different steps, map the process, allows you to understand the flow that you're going through, and let you know that if you automate those repetitive tasks within your process, you're going to be able to save a certain amount of time and energy and have a better process in place. And then the cool thing about what we announced yesterday, and this is unique in the industry today, is the ability to create bots automatically from analyzing that process. So again, the industry has matured into analyzing processes manually, or using certain tools, but then the work had to be done by a different platform to basically create the bots from these processes. We're the only provider today that can analyze processes with the tool, and then create the bots automatically, shrinking the time for process automation end-to-end. >> Fantastic. >> Okay, and now, but also part of this release, too, right, is your kind of cloud capabilities. You've really kind of ramped up your ability to scale for the kind of largest customers. Talk a little to us about how the application functions in the cloud, how it functions on-prem. How does that all work end-to-end? >> Right, so back in November we announced the new platform called Enterprise A2019. This was the first cloud native web-based platform in the industry. And the reason why cloud native is important is because it's what gives you the benefits, in terms of scaling, in terms of TCO, in terms of easy to use, and that platform is now the core platform for the company, and so the product announcement we had yesterday allows our customers to use the same platform, except now we add this Discovery Bot at the front-end to discover the process, prioritize them, and then use the platform we've announced to automate these processes. What's very interesting about the platform is that customers can use it on-prem, can use it in the cloud. The customers, obviously, that decide to use it in the cloud will have the ability to learn more from the platform because, you know, it's going to tackle a lot more data in the cloud. Then we're going to be able to use lots of data analysis tools to be able to get the customers to extract knowledge from it and then innovate a much faster way. The people who are going to be using it on-prem, typically, are regulated industries or customers who have systems of records that are, typically, on-prem and they would like the bots to run where the systems are. So the platform is available in the cloud. It's available on-prem. It's the customer's choice to decide how to use it, but the innovation that's backed into it is what's really exciting. >> So this is kind of, I think, a fundamental point, maybe people should understand, right? So what you're, this is kind of a brave new world, right? You're saying kind of cloud native app, right, which is now ready to be used on-prem, right? >> Right >> As opposed to maybe the older world where people develop applications that were primarily based for kind of a server architecture within the firewall, right? >> Exactly. >> And then they tried to migrate it to the cloud? >> Exactly. >> So in some sense, you've done the reverse. >> Exactly. So if you were to build an application today knowing, you know, microservices architecture, knowing Java, knowing web-based, that's how you would build it. And so the fact that you've built the architecture for a modern application and then offer the options to customers to use it, either on-prem or in the cloud, is what we've done. >> Got it, great. Okay, so then what's the advantage of being able to use, so you've got this application that can scale with microservices, right? It can handle the volume that a Fortune 500 company might need. What's the advantage for them being able to do it on-prem? What does that help? >> So for some customers, it's really about regulating industries. For example, if you're a bank, or if you're a healthcare institution, the data cannot travel through the cloud. So systems of records, whether it's a CRM, whether it's HRM with some other systems of records, an ERP, usually will be on-prem and the data can travel through the cloud. So for these customers, we're saying, use the product on-prem, you have the same benefit. It's still the cloud architecture, microservices-based. It's still web-based as far as the client interface is concerned. It's the lowest TCO you can get, but you don't have to worry about getting to the cloud if that's what you decide to do. >> So, in terms of enabling digital transformation, really the requirement here is to be able to enable that both in the cloud and on-prem and do it simultaneously. >> Correct, and again, some customers will do a hybrid of both and then say, for these workflows we'll have them in the cloud, for these we'll keep them on-prem. Some customers in regulated industries will say, we don't want to do anything in the cloud, we want everything on-prem. They'll have the choice to do that. >> Understood, okay, well look, final question here. Let's talk about kind of some of the upcoming events that Automation Anywhere has going on, right? You do events all across the globe, you're now a global company. Tell us what's happening on that front. >> Yeah, so we do lots of events, you know, cause our customers are global, where we have customers in 90 countries, we have offices in 45 countries, and so we have to go where our customers are. So we have four large conferences throughout the year, one upcoming in London, we have it in Vegas, in Tokyo, and in Bangalore, as well. And it's the largest gathering of RPA minds and experts in the industry today. So what's exciting about the one that's coming up is, obviously, Discovery Bot is going to be featured at that conference. People will be able to play with the product, they'll be able to understand, you know, the latest innovations from Automation Anywhere. We have sessions that are called Build a Bots where people will be able to build their bots on-site, and that's always a popular thing for people to do. And then we're going to have some amazing speakers and top leaders who will help customers understand, you know, what's happening in digital transformation, and how intelligent automation can accelerate that transformation. >> Okay, great, and so just to understand the timing of it, so you've got a show coming up in London in the very near future here, is that right? >> Yes, I believe it's in April and then we have another one in May in Las Vegas. >> Okay, so then the big one in North America is going to be Vegas this year? >> Correct, correct, it's in May. >> Okay, great. And then, what about the, so then you also talked about Bangalore, talk about -- >> Yeah, Bangalore, I don't have all the dates in my head, so I apologize, but I think Bangalore is, I believe, in August or September, and then Tokyo, I believe, it's in June, so I'll have to confirm all those dates -- >> But one of the unique things, right, is that Bangalore show has actually been one of your largest shows of the year. >> It's been amazing. So I literally missed that show by one week. When I joined the company, I was super excited about having the ability to go visit the customers and the partners within the show. I think last year they had 6000 people, so it's an amazing opportunity this year to go see it first-hand. I don't know what the audience is going to be like, I'm assuming it's going to be more than 6000, but feeling the energy and the excitement from attendees is what I'm really looking forward to. >> Well, that just shows, right, that the software industry, particularly cloud-enabled software industry, is now a global industry, right? >> It is, it is, absolutely, because again, cloud allows those barriers to entry for companies, wherever they are, to be lowered, and customers in different regions can have the latest, greatest directly from the cloud and they both use the product, you know, when it comes out, and so that's, obviously, a super big advantage. The other thing I should be remiss if I didn't say, you know, because it's also available in the cloud, and it's web-based, it's easy to use, easy to access, a lot of our first-time customers are business users. They're not even IT people, so they just go in, start playing with the product, you know, automating a few processes, and then start to scale end-to-end, and then of course they build the COE, IT gets involved. So being able to start your automation journey as small, and then grow as you scale from any parts of the world is really what this opportunity gives us. >> Okay, well thank you for your time today, Riadh. I'm fascinated, everything you guys are doing. Super hot category for those folks out there that want to touch base with Automation Anywhere, shows in London, Vegas, Bangalore, and then where was the fourth one? >> I think Tokyo -- >> Tokyo. >> And then Bangalore after that, yes. >> Okay, fantastic. >> Yes. >> Thanks for joining us today. This is Donald Klein, I'm the host of theCUBE. I'll see you next time. (upbeat music)

>> Live, from Las Vegas, it's theCUBE covering UiPath Forward Americas 2019. Brought to you by UiPath. >> Welcome back to the Bellagio in Las Vegas, everybody. You're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante. Day one of UiPath Forward III, hashtag UiPathForward. Elena Christopher is here. She's the senior vice president at HFS Research, and Elena, I'm going to recruit you to be my co-host here. >> Co-host! >> On this power panel. Jean Youngers here, CUBE alum, VP, a Six Sigma Leader at Security Benefit. Great to see you again. >> Thank you. >> Dave: And Amy Chandler, who is the Assistant Vice President and Director of Internal Controls, also from Security Benefit. >> Hello. >> Dave: Thanks for coming on theCUBE. >> Thank you. >> Alright Elena, let's start off with you. You follow this market, you have for some time, you know HFS is sort of anointed as formulating this market place, right? >> Elena: We like to think of ourselves as the voice-- >> You guys were early on. >> The voice of the automation industry. >> So, what are you seeing? I mean, process automation has been around forever, RPA is a hot recent trend, but what are you seeing the last year or two? What are the big trends and rip currents that you see in the market place? >> I mean, I think one of the big trends that's out there, I mean, RPA's come on to the scene. I like how you phrase it Dave, because you refer to it as, rightly so, automation is not new, and so we sort of say the big question out there is, "Is RPA just flavor of the month?" RPA is definitely not, and I come from a firm, we put out a blog earlier this year called "RPA is dead. Long live automation." And that's because, when we look at RPA, and when we think about what it's impact is in the market place, to us the whole point of automation in any form, regardless of whether it's RPA, whether it be good old old school BPM, whatever it may be, it's mission is to drive transformation, and so the HFS perspective, and what all of our research shows and sort of justifies that the goal is, what everyone is striving towards, is to get to that transformation. And so, the reason we put out that piece, the "RPA is dead. Long live integrated automation platforms" is to make the point that if you're not- 'cause what does RPA allow? It affords an opportunity for change to drive transformation so, if you're not actually looking at your processes within your company and taking this opportunity to say, "What can I change, what processes are just bad, "and we've been doing them, I'm not even sure why, "for so long. What can we transform, "what can we optimize, what can we invent?" If you're not taking that opportunity as an enterprise to truly embrace the change and move towards transformation, that's a missed opportunity. So I always say, RPA, you can kind of couch it as one of many technologies, but what RPA has really done for the market place today, it's given business users and business leaders the realization that they can have a role in their own transformation. And that's one of the reasons why it's actually become very important, but a single tool in it's own right will never be the holistic answer. >> So Jean, Elena's bringing up a point about transformation. We, Stew Bennett and I interviewed you last year and we've played those clips a number of times, where you sort of were explaining to us that it didn't make sense before RPA to try to drive Six Sigma into business processes; you couldn't get the return. >> Jean: Right. >> Now you can do it very cheaply. And for Six Sigma or better, is what you use for airplane engines, right? >> Right. >> So, now you're bringing up the business process. So, you're a year in, how's it going? What kind of results are you seeing? Is it meeting your expectations? >> It's been wonderful. It has been the best, it's been probably the most fun I've had in the last fifteen years of work. I have enjoyed, partly because I get to work with this great person here, and she's my COE, and helps stand up the whole RPA solution, but you know, we have gone from finance into investment operations, into operations, you know we've got one sitting right now that we're going to be looking at statements that it's going to be fourteen thousand hours out of both time out as well as staff hours saved, and it's going to touch our customer directly, that they're not going to get a bad statement anymore. And so, you know, it has just been an incredible journey for us over the past year, it really has. >> And so okay Amy, your role is, you're the hardcore practitioner here right? >> Amy: That's right. >> You run the COE. Tell us more about your role, and I'm really interested in how you're bringing it out, RPA to the organization. Is that led by your team, or is it kind of this top-down approach? >> Yeah, this last year, we spent a lot of time trying to educate the lower levels and go from a bottom-up perspective. Pretty much, we implemented our infrastructure, we had a nice solid change management process, we built in logical access, we built in good processes around that so that we'd be able to scale easily over this last year, which kind of sets us up for next year, and everything that we want to accomplish then. >> So Elena, we were talking earlier on theCUBE about you know, RPA, in many ways, I called it cleaning up the crime scene, where stuff is kind of really sort of a mass and huge opportunities to improve. So, my question to you is, it seems like RPA is, in some regards, successful because you can drop it into existing processes, you're not changing things, but in a way, this concerns that, oh well, I'm just kind of paving the cow path. So how much process reinvention should have to occur in order to take advantage of RPA? >> I love that you use that phrase, "paving the cow path." As a New Englander, as you know the roads in Boston are in fact paved cow paths, so we know that can lead to some dodgy roads, and that's part of, and I say it because that's part of what the answer is, because the reinvention, and honestly the optimization has to be part of what the answer is. I said it just a little bit earlier in my comments, you're missing an opportunity with RPA and broader automation if you don't take that step to actually look at your processes and figure out if there's just essentially deadwood that you need to get rid of, things that need to be improved. One of the sort of guidelines, because not all processes are created equal, because you don't want to spend the time and effort, and you guys should chime in on this, you don't want to spend the time and effort to optimize a process if it's not critical to your business, if you're not going to get lift from it, or from some ROI. It's a bit of a continuum, so one of the things that I always encourage enterprises to think about, is this idea of, well what's the, obviously, what business problem are you trying to solve? But as you're going through the process optimization, what kind of user experience do you want out of this? And your users, by the way, you tend to think of your user as, it could be your end customer, it could be your employee, it could even be your partner, but trying to figure out what the experience is that you actually want to have, and then you can actually then look at the process and figure out, do we need to do something different? Do we need to do something completely new to actually optimize that? And then again, line it with what you're trying to solve and what kind of lift you want to get from it. But I'd love to, I mean, hopping over to you guys, you live and breathe this, right? And so I think you have a slightly different opinion than me, but-- >> We do live and breathe it, and every process we look at, we take into consideration. But you've also got to, you have a continuum right? If it's a simple process and we can put it up very quickly, we do, but we've also got ones where one process'll come into us, and a perfect example is our rate changes. >> Amy: Rate changes. >> It came in and there was one process at the very end and they ended up, we did a wing to wing of the whole thing, followed the data all the way back through the process, and I think it hit, what, seven or eight-- >> Yeah. >> Different areas-- >> Areas. >> Of the business, and once we got done with that whole wing to wing to see what we could optimize, it turned into what, sixty? >> Amy: Yeah, sixty plus. Yeah. >> Dave: Sixty plus what? >> Bot processes from one entry. >> Yeah. >> And so, right now, we've got 189 to 200 processes in the back log. And so if you take that, and exponentially increase it, we know that there's probably actually 1,000 to 2,000 more processes, at minimum, that we can hit for the company, and we need to look at those. >> Yeah, and I will say, the wing to wing approach is very important because you're following the data as it's moving along. So if you don't do that, if you only focus on a small little piece of it, you don't what's happening to the data before it gets to you and you don't know what's going to happen to it when it leaves you, so you really do have to take that wing to wing approach. >> So, internal controls is in your title, so talking about scale, it's a big theme here at UiPath, and these days, things scale really fast, and boo-boos can happen really fast. So how are you ensuring, you know that the edicts of the organization are met, whether it's security, compliance, governance? Is that part of your role? >> Yeah, we've actually kept internal audit and internal controls, and in fact, our external auditors, EY. We've kept them all at the table when we've gone through processes, when we've built out our change management process, our logical access. When we built our whole process from beginning to end they kind of sat at the table with us and kind of went over everything to make sure that we were hitting all the controls that we needed to do. >> And actually, I'd like to piggyback on that comment, because just that inclusion of the various roles, that's what we found as an emerging best practice, and in all of our research and all of the qualitative conversations that we have with enterprises and service providers, is because if you do things, I mean it applies on multiple levels, because if you do things in a silo, you'll have siloed impact. If you bring the appropriate constituents to the table, you're going to understand their perspective, but it's going to have broader reach. So it helps alleviate the silos but it also supports the point that you just made Amy, about looking at the processes end to end, because you've got the necessary constituents involved so you know the context, and then, I believe, I mean I think you guys shared this with me, that particularly when audit's involved, you're perhaps helping cultivate an understanding of how even their processes can improve as well. >> Right. >> That is true, and from an overall standpoint with controls, I think a lot of people don't realize that a huge benefit is your controls, cause if you're automating your controls, from an internal standpoint, you're not going to have to test as much, just from an associate process owner paying attention to their process to the internal auditors, they're not going to have to test as much either, and then your external auditors, which that's revenue. I mean, that's savings. >> You lower your auditing bill? >> Yeah. Yeah. >> Well we'll see right? >> Yeah. (laughter) >> That's always the hope. >> Don't tell EY. (laughter) So I got to ask you, so you're in a little over a year So I don't know if you golf, but you know a mulligan in golf. If you had a mulligan, a do over, what would you do over? >> The first process we put in place. At least for me, it breaks a lot, and we did it because at the time, we were going through decoupling and trying to just get something up to make sure that what we stood up was going to work and everything, and so we kind of slammed it in, and we pay for that every quarter, and so actually it's on our list to redo. >> Yeah, we automated a bad process. >> Yeah, we automated a bad process. >> That's a really good point. >> So we pay for it in maintenance every quarter, we pay for it, cause it breaks inevitably. >> Yes. >> Okay so what has to happen? You have to reinvent the process, to Elena's? >> Yes, you know, we relied on a process that somebody else had put in place, and in looking at it, it was kind of a up and down and through the hoop and around this way to get what they needed, and you know there's much easier ways to get the data now. And that's what we're doing. In fact, we've built our own, we call it a bot mart. That's where all our data goes, they won't let us touch the other data marts and so forth so they created us a bot mart, and anything that we need data for, they dump in there for us and then that's where our bot can hit, and our bot can hit it at anytime of the day or night when we need the data, and so it's worked out really well for us, and so the bot mart kind of came out of that project of there's got to be a better way. How can we do this better instead of relying on these systems that change and upgrade and then we run the bot and its working one day and the next day, somebody has gone in and tweaked something, and when all's I really need out of that system is data, that's all I need. I don't need, you know, a report. I don't need anything like that, cause the reports change and they get messed up. I just want the raw data, and so that's what we're starting to do. >> How do you ensure that the data is synchronized with your other marts and warehouses, is that a problem? >> Not yet. >> No not yet! (laughter) >> I'm wondering cause I was thinking the exact same question Dave, because on one hand its a nice I think step from a governance standpoint. You have what you need, perhaps IT or whomever your data curators are, they're not going to have a heart attack that you're touching stuff that they don't want you to, but then there is that potential for synchronization issues, cause that whole concept of golden source implies one copy if you will. >> Well, and it is. It's all coming through, we have a central data repository that the data's going to come through, and it's all sitting there, and then it'll move over, and to me, what I most worry about, like I mentioned on the statement once, okay, I get my data in, is it the same data that got used to create those statements? And as we're doing the testing and as we're looking at going live, that's one of our huge test cases. We need to understand what time that data comes in, when will it be into our bot mart, so when can I run those bots? You know, cause they're all going to be unattended on those, so you know, the timing is critical, and so that's why I said not yet. >> Dave: (chuckle) >> But you want to know what, we can build the bot to do that compare of the data for us. >> Haha all right. I love that. >> I saw a stat the other day. I don't know where it was, on Twitter or maybe it was your data, that more money by whatever, 2023 is going to be spent on chat bots than mobile development. >> Jean: I can imagine, yes. >> What are you doing with chat bots? And how are you using them? >> Do you want to answer that one or do you want me to? >> Go ahead. >> Okay so, part of the reason I'm so enthralled by the chat bot or personal assistant or anything, is because the unattended robots that we have, we have problems making sure that people are doing what they're supposed to be doing in prep. We have some in finance, and you know, finance you have a very fine line of what you can automate and what you need the user to still understand what they're doing, right? And so we felt like we had a really good, you know, combination of that, but in some instances, they forget to do things, so things aren't there and we get the phone call the bot broke, right? So part of the thing I'd like to do is I'd like to move that back to an unattended bot, and I'm going to put a chat bot in front of it, and then all's they have to do is type in "run my bot" and it'll come up if they have more than one bot, it'll say "which one do you want to run?" They'll click it and it'll go. Instead of having to go out on their machine, figure out where to go, figure out which button to do, and in the chat I can also send them a little message, "Did you run your other reports? Did you do this?" You know, so, I can use it for the end user, to make that experience for them better. And plus, we've got a lot of IT, we've got a lot of HR stuff that can fold into that, and then RPA all in behind it, kind of the engine on a lot of it. >> I mean you've child proofed the bot. >> Exactly! There you go. There you go. >> Exactly. Exactly. And it also provides a means to be able to answer those commonly asked questions for HR for example. You know, how much vacation time do I have? When can I change my benefits? Examples of those that they answer frequently every day. So that provides another avenue for utilization of the chat bot. >> And if I may, Dave, it supports a concept that I know we were talking about yesterday. At HFS it's our "Triple-A Trifecta", but it's taking the baseline of automation, it intersects with components of AI, and then potentially with analytics. This is starting to touch on some of the opportunities to look at other technologies. You say chat bots. At HFS we don't use the term chat bot, just because we like to focus and emphasize the cognitive capability if you will. But in any case, you guys essentially are saying, well RPA is doing great for what we're using RPA for, but we need a little bit of extension of functionality, so we're layering in the chat bot or cognitive assistant. So it's a nice example of some of that extension of really seeing how it's, I always call it the power of and if you will. Are you going to layer these things in to get what you need out of it? What best solves your business problems? Just a very practical approach I think. >> So Elena, Guy has a session tomorrow on predictions. So we're going to end with some predictions. So our RPA is dead, (chuckle) will it be resuscitated? What's the future of RPA look like? Will it live up to the hype? I mean so many initiatives in our industry haven't. I always criticize enterprise data warehousing and ETL and big data is not living up to the hype. Will RPA? >> It's got a hell of a lot of hype to live up to, I'll tell you that. So, back to some of our causality about why we even said it's dead. As a discrete software category, RPA is clearly not dead at all. But unless it's helping to drive forward with transformation, and even some of the strategies that these fine ladies from Security Benefit are utilizing, which is layering in additional technology. That's part of the path there. But honestly, the biggest challenge that you have to go through to get there and cannot be underestimated, is the change that your organization has to go through. Cause think about it, if we look at the grand big vision of where RPA and broader intelligent automation takes us, the concept of creating a hybrid workforce, right? So what's a hybrid workforce? It's literally our humans complemented by digital workers. So it still sounds like science fiction. To think that any enterprise could try and achieve some version of that and that it would be A, fast or B, not take a lot of change management, is absolutely ludicrous. So it's just a very practical approach to be eyes wide open, recognize that you're solving problems but you have to want to drive change. So to me, and sort of the HFS perspective, continues to be that if RPA is not going to die a terrible death, it needs to really support that vision of transformation. And I mean honestly, we're here at a UiPath event, they had many announcements today that they're doing a couple of things. Supporting core functionality of RPA, literally adding in process discovery and mining capabilities, adding in analytics to help enterprises actually track what your benefit is. >> Jean: Yes. >> These are very practical cases that help RPA live another day. But they're also extending functionality, adding in their whole announcement around AI fabric, adding in some of the cognitive capability to extend the functionality. And so prediction-wise, RPA as we know it three years from now is not going to look like RPA at all. I'm not going to call it AI, but it's going to become a hybrid, and it's honestly going to look a lot like that Triple-A Trifecta I mentioned. >> Well, and UiPath, and I presume other suppliers as well, are expanding their markets. They're reaching, you hear about citizens developers and 100% of the workforce. Obviously you guys are excited and you see a long-run way for RPA. >> Jean: Yeah, we do. >> I'll give you the last word. >> It's been a wonderful journey thus far. After this morning's event where they showed us everything, I saw a sneak peek yesterday during the CAB, and I had a list of things I wanted to talk to her about already when I came out of there. And then she saw more of 'em today, and I've got a pocketful of notes of stuff that we're going to take back and do. I really, truly believe this is the future and we can do so much. Six Sigma has kind of gotten a rebirth. You go in and look at your processes and we can get those to perfect. I mean, that's what's so cool. It is so cool that you can actually tell somebody, I can do something perfect for you. And how many people get to do that? >> It's back to the user experience, right? We can make this wildly functional to meet the need. >> Right, right. And I don't think RPA is the end all solution, I think it's just a great tool to add to your toolkit and utilize moving forward. >> Right. All right we'll have to leave it there. Thanks ladies for coming on, it was a great segment. Really appreciate your time. >> Thanks. >> Thank you. >> Thank you for watching, everybody. This is Dave Vellante with theCUBE. We'll be right back from UiPath Forward III from Las Vegas, right after this short break. (technical music)

>> Live, from Las Vegas, it's theCUBE covering UiPath Forward Americas 2019. Brought to you by UiPath. >> Welcome back to the Bellagio in Las Vegas, everybody. You're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante. Day one of UiPath Forward III, hashtag UiPathForward. Elena Christopher is here. She's the senior vice president at HFS Research, and Elena, I'm going to recruit you to be my co-host here. >> Co-host! >> On this power panel. Jean Youngers here, CUBE alum, VP, a Six Sigma Leader at Security Benefit. Great to see you again. >> Thank you. >> Dave: And Amy Chandler, who is the Assistant Vice President and Director of Internal Controls, also from Security Benefit. >> Hello. >> Dave: Thanks for coming on theCUBE. >> Thank you. >> Alright Elena, let's start off with you. You follow this market, you have for some time, you know HFS is sort of anointed as formulating this market place, right? >> Elena: We like to think of ourselves as the voice-- >> You guys were early on. >> The voice of the automation industry. >> So, what are you seeing? I mean, process automation has been around forever, RPA is a hot recent trend, but what are you seeing the last year or two? What are the big trends and rip currents that you see in the market place? >> I mean, I think one of the big trends that's out there, I mean, RPA's come on to the scene. I like how you phrase it Dave, because you refer to it as, rightly so, automation is not new, and so we sort of say the big question out there is, "Is RPA just flavor of the month?" RPA is definitely not, and I come from a firm, we put out a blog earlier this year called "RPA is dead. Long live automation." And that's because, when we look at RPA, and when we think about what it's impact is in the market place, to us the whole point of automation in any form, regardless of whether it's RPA, whether it be good old old school BPM, whatever it may be, it's mission is to drive transformation, and so the HFS perspective, and what all of our research shows and sort of justifies that the goal is, what everyone is striving towards, is to get to that transformation. And so, the reason we put out that piece, the "RPA is dead. Long live integrated automation platforms" is to make the point that if you're not- 'cause what does RPA allow? It affords an opportunity for change to drive transformation so, if you're not actually looking at your processes within your company and taking this opportunity to say, "What can I change, what processes are just bad, "and we've been doing them, I'm not even sure why, "for so long. What can we transform, "what can we optimize, what can we invent?" If you're not taking that opportunity as an enterprise to truly embrace the change and move towards transformation, that's a missed opportunity. So I always say, RPA, you can kind of couch it as one of many technologies, but what RPA has really done for the market place today, it's given business users and business leaders the realization that they can have a role in their own transformation. And that's one of the reasons why it's actually become very important, but a single tool in it's own right will never be the holistic answer. >> So Jean, Elena's bringing up a point about transformation. We, Stew Bennett and I interviewed you last year and we've played those clips a number of times, where you sort of were explaining to us that it didn't make sense before RPA to try to drive Six Sigma into business processes; you couldn't get the return. >> Jean: Right. >> Now you can do it very cheaply. And for Six Sigma or better, is what you use for airplane engines, right? >> Right. >> So, now you're bringing up the business process. So, you're a year in, how's it going? What kind of results are you seeing? Is it meeting your expectations? >> It's been wonderful. It has been the best, it's been probably the most fun I've had in the last fifteen years of work. I have enjoyed, partly because I get to work with this great person here, and she's my COE, and helps stand up the whole RPA solution, but you know, we have gone from finance into investment operations, into operations, you know we've got one sitting right now that we're going to be looking at statements that it's going to be fourteen thousand hours out of both time out as well as staff hours saved, and it's going to touch our customer directly, that they're not going to get a bad statement anymore. And so, you know, it has just been an incredible journey for us over the past year, it really has. >> And so okay Amy, your role is, you're the hardcore practitioner here right? >> Amy: That's right. >> You run the COE. Tell us more about your role, and I'm really interested in how you're bringing it out, RPA to the organization. Is that led by your team, or is it kind of this top-down approach? >> Yeah, this last year, we spent a lot of time trying to educate the lower levels and go from a bottom-up perspective. Pretty much, we implemented our infrastructure, we had a nice solid change management process, we built in logical access, we built in good processes around that so that we'd be able to scale easily over this last year, which kind of sets us up for next year, and everything that we want to accomplish then. >> So Elena, we were talking earlier on theCUBE about you know, RPA, in many ways, I called it cleaning up the crime scene, where stuff is kind of really sort of a mass and huge opportunities to improve. So, my question to you is, it seems like RPA is, in some regards, successful because you can drop it into existing processes, you're not changing things, but in a way, this concerns that, oh well, I'm just kind of paving the cow path. So how much process reinvention should have to occur in order to take advantage of RPA? >> I love that you use that phrase, "paving the cow path." As a New Englander, as you know the roads in Boston are in fact paved cow paths, so we know that can lead to some dodgy roads, and that's part of, and I say it because that's part of what the answer is, because the reinvention, and honestly the optimization has to be part of what the answer is. I said it just a little bit earlier in my comments, you're missing an opportunity with RPA and broader automation if you don't take that step to actually look at your processes and figure out if there's just essentially deadwood that you need to get rid of, things that need to be improved. One of the sort of guidelines, because not all processes are created equal, because you don't want to spend the time and effort, and you guys should chime in on this, you don't want to spend the time and effort to optimize a process if it's not critical to your business, if you're not going to get lift from it, or from some ROI. It's a bit of a continuum, so one of the things that I always encourage enterprises to think about, is this idea of, well what's the, obviously, what business problem are you trying to solve? But as you're going through the process optimization, what kind of user experience do you want out of this? And your users, by the way, you tend to think of your user as, it could be your end customer, it could be your employee, it could even be your partner, but trying to figure out what the experience is that you actually want to have, and then you can actually then look at the process and figure out, do we need to do something different? Do we need to do something completely new to actually optimize that? And then again, line it with what you're trying to solve and what kind of lift you want to get from it. But I'd love to, I mean, hopping over to you guys, you live and breathe this, right? And so I think you have a slightly different opinion than me, but-- >> We do live and breathe it, and every process we look at, we take into consideration. But you've also got to, you have a continuum right? If it's a simple process and we can put it up very quickly, we do, but we've also got ones where one process'll come into us, and a perfect example is our rate changes. >> Amy: Rate changes. >> It came in and there was one process at the very end and they ended up, we did a wing to wing of the whole thing, followed the data all the way back through the process, and I think it hit, what, seven or eight-- >> Yeah. >> Different areas-- >> Areas. >> Of the business, and once we got done with that whole wing to wing to see what we could optimize, it turned into what, sixty? >> Amy: Yeah, sixty plus. Yeah. >> Dave: Sixty plus what? >> Bot processes from one entry. >> Yeah. >> And so, right now, we've got 189 to 200 processes in the back log. And so if you take that, and exponentially increase it, we know that there's probably actually 1,000 to 2,000 more processes, at minimum, that we can hit for the company, and we need to look at those. >> Yeah, and I will say, the wing to wing approach is very important because you're following the data as it's moving along. So if you don't do that, if you only focus on a small little piece of it, you don't what's happening to the data before it gets to you and you don't know what's going to happen to it when it leaves you, so you really do have to take that wing to wing approach. >> So, internal controls is in your title, so talking about scale, it's a big theme here at UiPath, and these days, things scale really fast, and boo-boos can happen really fast. So how are you ensuring, you know that the edicts of the organization are met, whether it's security, compliance, governance? Is that part of your role? >> Yeah, we've actually kept internal audit and internal controls, and in fact, our external auditors, EY. We've kept them all at the table when we've gone through processes, when we've built out our change management process, our logical access. When we built our whole process from beginning to end they kind of sat at the table with us and kind of went over everything to make sure that we were hitting all the controls that we needed to do. >> And actually, I'd like to piggyback on that comment, because just that inclusion of the various roles, that's what we found as an emerging best practice, and in all of our research and all of the qualitative conversations that we have with enterprises and service providers, is because if you do things, I mean it applies on multiple levels, because if you do things in a silo, you'll have siloed impact. If you bring the appropriate constituents to the table, you're going to understand their perspective, but it's going to have broader reach. So it helps alleviate the silos but it also supports the point that you just made Amy, about looking at the processes end to end, because you've got the necessary constituents involved so you know the context, and then, I believe, I mean I think you guys shared this with me, that particularly when audit's involved, you're perhaps helping cultivate an understanding of how even their processes can improve as well. >> Right. >> That is true, and from an overall standpoint with controls, I think a lot of people don't realize that a huge benefit is your controls, cause if you're automating your controls, from an internal standpoint, you're not going to have to test as much, just from an associate process owner paying attention to their process to the internal auditors, they're not going to have to test as much either, and then your external auditors, which that's revenue. I mean, that's savings. >> You lower your auditing bill? >> Yeah. Yeah. >> Well we'll see right? >> Yeah. (laughter) >> That's always the hope. >> Don't tell EY. (laughter) So I got to ask you, so you're in a little over a year So I don't know if you golf, but you know a mulligan in golf. If you had a mulligan, a do over, what would you do over? >> The first process we put in place. At least for me, it breaks a lot, and we did it because at the time, we were going through decoupling and trying to just get something up to make sure that what we stood up was going to work and everything, and so we kind of slammed it in, and we pay for that every quarter, and so actually it's on our list to redo. >> Yeah, we automated a bad process. >> Yeah, we automated a bad process. >> That's a really good point. >> So we pay for it in maintenance every quarter, we pay for it, cause it breaks inevitably. >> Yes. >> Okay so what has to happen? You have to reinvent the process, to Elena's? >> Yes, you know, we relied on a process that somebody else had put in place, and in looking at it, it was kind of a up and down and through the hoop and around this way to get what they needed, and you know there's much easier ways to get the data now. And that's what we're doing. In fact, we've built our own, we call it a bot mart. That's where all our data goes, they won't let us touch the other data marts and so forth so they created us a bot mart, and anything that we need data for, they dump in there for us and then that's where our bot can hit, and our bot can hit it at anytime of the day or night when we need the data, and so it's worked out really well for us, and so the bot mart kind of came out of that project of there's got to be a better way. How can we do this better instead of relying on these systems that change and upgrade and then we run the bot and its working one day and the next day, somebody has gone in and tweaked something, and when all's I really need out of that system is data, that's all I need. I don't need, you know, a report. I don't need anything like that, cause the reports change and they get messed up. I just want the raw data, and so that's what we're starting to do. >> How do you ensure that the data is synchronized with your other marts and warehouses, is that a problem? >> Not yet. >> No not yet! (laughter) >> I'm wondering cause I was thinking the exact same question Dave, because on one hand its a nice I think step from a governance standpoint. You have what you need, perhaps IT or whomever your data curators are, they're not going to have a heart attack that you're touching stuff that they don't want you to, but then there is that potential for synchronization issues, cause that whole concept of golden source implies one copy if you will. >> Well, and it is. It's all coming through, we have a central data repository that the data's going to come through, and it's all sitting there, and then it'll move over, and to me, what I most worry about, like I mentioned on the statement once, okay, I get my data in, is it the same data that got used to create those statements? And as we're doing the testing and as we're looking at going live, that's one of our huge test cases. We need to understand what time that data comes in, when will it be into our bot mart, so when can I run those bots? You know, cause they're all going to be unattended on those, so you know, the timing is critical, and so that's why I said not yet. >> Dave: (chuckle) >> But you want to know what, we can build the bot to do that compare of the data for us. >> Haha all right. I love that. >> I saw a stat the other day. I don't know where it was, on Twitter or maybe it was your data, that more money by whatever, 2023 is going to be spent on chat bots than mobile development. >> Jean: I can imagine, yes. >> What are you doing with chat bots? And how are you using them? >> Do you want to answer that one or do you want me to? >> Go ahead. >> Okay so, part of the reason I'm so enthralled by the chat bot or personal assistant or anything, is because the unattended robots that we have, we have problems making sure that people are doing what they're supposed to be doing in prep. We have some in finance, and you know, finance you have a very fine line of what you can automate and what you need the user to still understand what they're doing, right? And so we felt like we had a really good, you know, combination of that, but in some instances, they forget to do things, so things aren't there and we get the phone call the bot broke, right? So part of the thing I'd like to do is I'd like to move that back to an unattended bot, and I'm going to put a chat bot in front of it, and then all's they have to do is type in "run my bot" and it'll come up if they have more than one bot, it'll say "which one do you want to run?" They'll click it and it'll go. Instead of having to go out on their machine, figure out where to go, figure out which button to do, and in the chat I can also send them a little message, "Did you run your other reports? Did you do this?" You know, so, I can use it for the end user, to make that experience for them better. And plus, we've got a lot of IT, we've got a lot of HR stuff that can fold into that, and then RPA all in behind it, kind of the engine on a lot of it. >> I mean you've child proofed the bot. >> Exactly! There you go. There you go. >> Exactly. Exactly. And it also provides a means to be able to answer those commonly asked questions for HR for example. You know, how much vacation time do I have? When can I change my benefits? Examples of those that they answer frequently every day. So that provides another avenue for utilization of the chat bot. >> And if I may, Dave, it supports a concept that I know we were talking about yesterday. At HFS it's our "Triple-A Trifecta", but it's taking the baseline of automation, it intersects with components of AI, and then potentially with analytics. This is starting to touch on some of the opportunities to look at other technologies. You say chat bots. At HFS we don't use the term chat bot, just because we like to focus and emphasize the cognitive capability if you will. But in any case, you guys essentially are saying, well RPA is doing great for what we're using RPA for, but we need a little bit of extension of functionality, so we're layering in the chat bot or cognitive assistant. So it's a nice example of some of that extension of really seeing how it's, I always call it the power of and if you will. Are you going to layer these things in to get what you need out of it? What best solves your business problems? Just a very practical approach I think. >> So Elena, Guy has a session tomorrow on predictions. So we're going to end with some predictions. So our RPA is dead, (chuckle) will it be resuscitated? What's the future of RPA look like? Will it live up to the hype? I mean so many initiatives in our industry haven't. I always criticize enterprise data warehousing and ETL and big data is not living up to the hype. Will RPA? >> It's got a hell of a lot of hype to live up to, I'll tell you that. So, back to some of our causality about why we even said it's dead. As a discrete software category, RPA is clearly not dead at all. But unless it's helping to drive forward with transformation, and even some of the strategies that these fine ladies from Security Benefit are utilizing, which is layering in additional technology. That's part of the path there. But honestly, the biggest challenge that you have to go through to get there and cannot be underestimated, is the change that your organization has to go through. Cause think about it, if we look at the grand big vision of where RPA and broader intelligent automation takes us, the concept of creating a hybrid workforce, right? So what's a hybrid workforce? It's literally our humans complemented by digital workers. So it still sounds like science fiction. To think that any enterprise could try and achieve some version of that and that it would be A, fast or B, not take a lot of change management, is absolutely ludicrous. So it's just a very practical approach to be eyes wide open, recognize that you're solving problems but you have to want to drive change. So to me, and sort of the HFS perspective, continues to be that if RPA is not going to die a terrible death, it needs to really support that vision of transformation. And I mean honestly, we're here at a UiPath event, they had many announcements today that they're doing a couple of things. Supporting core functionality of RPA, literally adding in process discovery and mining capabilities, adding in analytics to help enterprises actually track what your benefit is. >> Jean: Yes. >> These are very practical cases that help RPA live another day. But they're also extending functionality, adding in their whole announcement around AI fabric, adding in some of the cognitive capability to extend the functionality. And so prediction-wise, RPA as we know it three years from now is not going to look like RPA at all. I'm not going to call it AI, but it's going to become a hybrid, and it's honestly going to look a lot like that Triple-A Trifecta I mentioned. >> Well, and UiPath, and I presume other suppliers as well, are expanding their markets. They're reaching, you hear about citizens developers and 100% of the workforce. Obviously you guys are excited and you see a long-run way for RPA. >> Jean: Yeah, we do. >> I'll give you the last word. >> It's been a wonderful journey thus far. After this morning's event where they showed us everything, I saw a sneak peek yesterday during the CAB, and I had a list of things I wanted to talk to her about already when I came out of there. And then she saw more of 'em today, and I've got a pocketful of notes of stuff that we're going to take back and do. I really, truly believe this is the future and we can do so much. Six Sigma has kind of gotten a rebirth. You go in and look at your processes and we can get those to perfect. I mean, that's what's so cool. It is so cool that you can actually tell somebody, I can do something perfect for you. And how many people get to do that? >> It's back to the user experience, right? We can make this wildly functional to meet the need. >> Right, right. And I don't think RPA is the end all solution, I think it's just a great tool to add to your toolkit and utilize moving forward. >> Right. All right we'll have to leave it there. Thanks ladies for coming on, it was a great segment. Really appreciate your time. >> Thanks. >> Thank you. >> Thank you for watching, everybody. This is Dave Vellante with theCUBE. We'll be right back from UiPath Forward III from Las Vegas, right after this short break. (technical music)

>> From New York City, it's theCUBE. Covering Automation Anywhere Imagine. Brought to you by Automation Anywhere. >> We're in midtown Manhattan at Automation Anywhere Imagine 2019. It's about 1,500 people talking about RPA which is part of the story but it's really a much broader story than RPA. It's about the ecosystem, it's about new ways to work, and really, RPA is an enabler but that's not the story in and of itself. It's really about helping people do their jobs better like a whole bunch of other tools that've come out over the years to help us out. We're excited to have a return guest who was here with us last year. He's Ankur Kothari, co-founder, another co-founder and chief revenue officer of Automation Anywhere. Great to see you again. >> Always good to see you, Jeff. >> So, it's been a year since last we spoke in June. >> We've been way less on ground, a lot on the flight. >> Yeah. >> Yeah. >> And, you brought in a bunch of money. You got a lot of resources really to support you now. So, how has that kind of changed? You know, you guys have grown a lot. You've put $500 million in the bank. How's that changing what you're working on now? >> Well, we are deploying that capital in three major ways. One is global expansion. We have now grown into, we have offices now in more than 30, 35 countries, 30 plus countries. So we are getting closer to all our customers worldwide in all top 30 economies and major business hubs where we are now we have opened offices, so, that's one. We are using this capital to build our ecosystem with our partners and all the developers. And, obviously we have invested a lot in our product. Taking the product stack more and more broader which allows us to automate any process that can be automated. >> Yeah, I mean, it's a great resource that you have at your disposal now. And Mihir talked about a lot of kind of higher level topics which I found really good in the keynote, really reframing RPA and personal digital assistance, if you will, around it's just another tool to help people get their job better. And he had some ridiculously sad stats about how much time that people are being asked to do robotic tasks which they really shouldn't be doing those tasks. >> Yes. >> There's much higher value stuff. It's not really rip-and-replace, it's really augment and help people do better. >> Augmenting, yes, yes, absolutely, generally most of these journeys start with this goal of productivity and rightly so. There's nothing wrong with that but as you scale in this journey and you start working, as you onboard more digital workers, digital colleagues as we like to call it, you find that the conversation in your organization changes from productivity to progress because that's what any technological transformation is about. It's not just about productivity, it's truly about progressing your team, your company, your industry, your customers forward. >> Right. >> So, that's what you face. And the second big prize on that front is it allows you to make work human. The moment you start automating every process that can be automated, we start using computers what they were designed for, to process things and not just to be used as a system of records. >> Right. >> So, we can do what we are good at. Solving complex problems using our creativity and empathy. >> Right, one of the things I thought was really interesting was the launch of the community addition, which is free. Free for small businesses, free for developers. I can't remember if there's an academic component-- >> Yes. >> Or not, but, you know, you're the guy who's puttin' money in the cash register. I'm sure there were some interesting conversations about having a free community edition. I wonder if you can share some insight 'cause, you know, that's taking money out of the bank, but obviously there's a much larger strategic goal. >> There's a strategic goal. The problem that we are falling in love with is that what would it take for us to accelerate the journey of every company to become a digital enterprise? How do we share in this new bot economy? And, in order to do that, we have to have every person participate in this whole phenomenon. An idea as big as this can not be one company or a few individuals' ideas. So, we have opened up that whole thing for everyone to participate. The community edition allows students, developers, small businesses, everyone to download. They go to our Automation Anywhere University and they can get freely trained and certified. And they can work with a bot. And they can build a bot and form their own opinion. >> Right. >> And have their own point of view. And the belief behind that is that a good idea can come from anywhere or anyone. And those ideas, once they use our product, they can monetize it in our marketplace which is the Bot Store. >> Right. >> So, that it allows everyone to form an opinion, and contribute to this new bot economy. >> It's pretty interesting. One of the topics Mihir touched on in the keynote was that we often think of, you know, kind of applying new technology to today's world, but we often miss, you know, as he said, that now is not the station, it's the train, and it's moving. And by opening it up to developers now, as you said, you're expanding the width, the breadth, and the potential applications of your technology to problems that you guys have never even thought about before. >> Exactly, that's the real thing. We are automating processes that we are doing now but generally it's about automating what we have not even seen. >> Right. >> These processes were designed for people to do. How would a process look when bots are performing there? I live in Silicon Valley and pretty much a computer science guy working on cutting edge. If you asked me 10 years ago would I let any of my family member live in a stranger's house? I would say, no way. Airbnb is one of the largest hotel chains in the world right now. >> Right, right. >> What that tells you is that human brain mind thinks linearly unless you give them something that allows humans to think exponentially. >> Right >> And that's the whole idea of beauty of technology. It allows us to think exponentially, and once our brain stretch there, then it's not possible to go back. >> Well, the other thing I think is really smart on your play is the competition for developers' attention, right? The developers these days have a lot of power and they can choose of a myriad of technologies in which to apply themselves. So, by having this community edition and opening it up is one part, but the other piece that I think is interesting is the whole bot economy. And I think you opened up the store last time we were here last year. >> Yes. >> Now you're putting money behind it so people can sell. In fact, we had a customer on earlier who's developing some stuff but they can augment that investment by actually selling those bots into this store. >> On the Bot Store, yeah. >> So, I wonder if you can talk a little bit more about how that is evolving? Is it kind of matching your vision? Has it accelerated past your vision? >> It is accelerating much faster than what we imagined first. When we one year ago we launched our marketplace, that is Bot Store. We opened up our University for everyone to get freely trained online. Then we started our community online, which is eight people. And with this community edition, everyone is now participating in it. What that is doing is we believe that more, the one thing that all developers want, is to contribute. Their work to be used by others. >> Right. >> And then, in a Bot Store, it allows them to even monetize it. It allows them to productize it so that personal satisfaction of solving a problem is what the developers get. And such new, creative ideas we are getting once we did that. Yesterday we had Bot Games and more than 250 to 300 developers participated in different games. And they were building these bots on fly, and they were competing. And we believe that when we bring all these people together and we give them a problem, genius comes out. >> Right. >> And it has been true. >> (laughs) So the ecosystem is huge and that's part of why you have your own show. And we go to a lot of shows. We were at Google Cloud a couple weeks ago. So, there's really two components of the ecosystem, traditional ecosystem. You've got the devs we talked about. There's the system integrators and you've got them all here in force. And they don't come out unless they really see a big opportunity. >> Yes. >> And the other part is the ISVs, right? To add all these different components. So, how is that evolving? Where do you see it going over the next year or two? >> It's interesting, you saw today that there was IBM, Microsoft, and Oracle all went on stage with software partnerships, you know Workday. So, we are forming large partnerships with software and how our product works with theirs, and the digital workers are part of that whole equation. And all our service providers and SIs and advisories that've been on this journey with us for the last five to six years and they are ramping up their entire practices to get their customers to become a digital enterprise. So, you see these two different worlds coming together and all the three worlds are working together for the customer to become a digital enterprise. >> Right. >> And, that's the best part. The digital native companies like Amazon, Airbnb, they have got this right. But what about the companies who have been there for 50 years, 100 years? How do they become digital? >> Right. >> And that's a more interesting problem. If you look at the software, and all the service partners and we are working together to solve that problem. So, it's a very interesting mix, an interesting time. And add to that this whole bot economy of developers bringing all these new digital workers. We are seeing the consumption of bot, growing in an exponential way. We are growing multi-force in few months. It's been a great, great ride. >> Right, well, I want to close on that in the last question 'cause you are one of the co-founders. I think there was four founders, if I'm correct. >> Yes. >> And you guys did it a very different way. You basically funded it the best way to fund a company, which is with revenue. >> Yes. >> And customer funded and you didn't go out and get outside money and now you've got this huge round which is actually an A round. >> Yes, it's a... >> So, how does that change the game? I mean, it puts you in a very good spot 'cause you don't have to take that money 'cause you were operating fine. But how does it, from a co-founder point of view, change the trajectory of your journey? >> There is obviously a value that that kind of capital brings because you can grow asymmetrically as well. >> Right, right. >> But the real value, for me, is the five investors who are such tier A, top-tier investors, who are the right partners we have got on this journey. If you think about Goldman Sachs, and NEA, and SoftBank, and General Atlantic which is one of larger growth-- >> Pretty good roster. >> Right. So you get that expertise and you get those partnerships that allows you to think exponentially and grow very fast. So, that's the real value for me in addition to the capital. >> Well, Ankur, thanks for sharing your journey with us. It's really been fun to watch and we're just at another inflection point I think. >> Always great to see you, and again next year. We ought to do this every year. >> All right, very good. >> Bigger and bigger. >> Absolutely, thanks again. >> Thanks a lot. >> He's Ankur, I'm Jeff, you're watching theCUBE. We're at Automation Anywhere in midtown Manhattan. Thanks for watching, we'll see you next time. (upbeat electronic music)

>> Live from Miami Beach, Florida, it's theCUBE. Covering UiPathForward Americas. Brought to you by UiPath. >> Welcome back to Miami everybody. You're watching theCUBE, the leader in live tech coverage. We go out to events, we extract the signal from the noise. A lot of noise here but the signal's all around automation and robotic process automation. I'm Dave Vellante, he's Stu Miniman, my co-host. Guy Kirkwood's here he's the UiPath chief evangelist otherwise known as the chief injector of Kool-Aid. Welcome. (guests chuckling) And Craig LeClair, the Vice President at Forrester. Covers this market, wrote the seminal document on this space. Knows it inside out. Craig, great to see you again. >> Yeah, nice to see you again. It's great to be back at theCUBE. >> So let's start with the analyst perspective. Take us back to when you first discovered RPA, why you got excited about it, and what Forrester Research is all about in that space. >> Yeah, it's been a very a interesting ride. Most of these companies, at least that are the higher value ones in the category they've been around for a long time. They've been around for over a decade, and no one ever heard of them three years ago. So I had covered at Forrester, business process management and some of the business rules engines, and I've always been in process. I just got this sense that there was a way that companies could make progress and digital transformation and overcome the technical debt that they had. A lot of the progress has been tepid in digital transformation because it takes tremendous amount of time and tons of consultants to modernize that core system that really runs the company. So along comes this RPA technology that allows you to build human equivalence that patch up the inefficiencies without touching. I came in on American Airlines and the system that cut my ticket was designed in 1960. It's the same Sabre reservation system. That's the big obstacle that a lot of companies have been struggling to really take advantage of AI in general. A lot of the more moonshot and more sophisticated promises haven't been realized. RPA is a very practical form of automation that companies can get a handle on right now, and move the dial for digital transformation. >> So Guy we heard a vision set forth by Daniel this morning. Basically a chicken in every pot, I call it, a robot for every person. Now what Craig was just saying about essentially cutting the line on technical debt, do you have clear evidence of that in your customer base? Maybe you could give some examples. >> What we're really seeing is that as organizations have to deal with the stresses, what Leslie Wilcox professor at LSE describes as the stresses within organizations and particularly in environments where the demographics are changing. What we're seeing is that organizations have to automate. So the best example of that is in Japan where the Japanese population peaked in 2010. It's now falling as a whole, plus all the baby boomers, people of Craig's and my age are now retiring. So we're now in a position where they measure levels of dangerous overwork as being more that 106 hours a week. That isn't 106 hour a week in total, that's 106 hours a week in addition to the 60 hours a week the Japanese people normally work. And there is a word in Japanese, which is (speaking in foreign language), which means to work oneself to death. So there really is no choice. So what we're seeing happening in Japan will be replicated in Western Europe and certainly in the US over the next few years. So what's driving that is the rise of the ecosystems of technologies of which RPA and AI are part, and that's really what we're seeing within the market. >> Craig, sometimes these big waves particularly in infrastructure, you kind of saw it with virtualization and some other wonky techs, like data reduction. They could be a one-time step function, and not an ongoing business value creator. Where does RPA fit in there? How can organizations make sure that this is a continuous business value generator as opposed to a one time hit? >> Good question. >> Well, I like the concept of RPA as a platform that can lead to more intelligence and more integration with AI components. It allows companies to build an automation center or a center of excellence focused on automation. But the next thing they're going to do after building some simple robots that are doing repetitive tasks, is they're going to say "Oh well wouldn't it be better "if my employee could have a textual chat with a chatbot "that then was interacting with the digital worker "that I built with the bot." Or they're going to say "You know what? I really want to use that machine learning algorithm "for my underwriting process, but I can use these bots "to go out and collect all the data from the core systems "and elsewhere and from the web and feed the algorithms "so that I could make a better decision." So again it goes back to that backing off the moonshot approach that we've been talking about that AI has been taking because of the tremendous amount of money spent by the major players to lay out the promise of AI has really been a little dysfunctional in getting organizations' eye off the ball in terms of what could be done with slightly more intelligent automation. So RPA will be a flash in the pan unless it starts to embed these more learning-capable AI modules. But I think it has a very good chance of doing that particularly now with so much investment coming into the category right. >> Craig, it's really interesting. When I heard you describe that it reminds me of the home automation. The Cortanas and Alexas and consumer side where you're seeing this. You've got the consumer side where you can build skills yourself, you know teenagers people can do that. One of the challenges always on the business side is how do you get the momentum when you don't have the consumer side. How do those interact? >> It's the technical debt issue and it's just like the mobile peak in 2011. Consumers in their hands had much better mobility right away than businesses. It took businesses five, they're still not there in building a great mobile environment. So these Alexa in our kitchen snooping on our conversation and to some extent Netflix that observes our behavior. That's a light form of AI. There is a learning from that behavior that's updating an algorithm autonomously in Netflix to understand what you want to watch. There's no one with a spreadsheet back there right. So this has given us in a sense a false sense of progress with all of AI. The reality is business is just getting started. Business is nowhere with AI. RPA is an initial foray on that path. We're in Miami so I'll call it a gateway drug. >> In fact there's also an element that the Siris, the Cortanas, the Alexas, are very poor at understanding specific ontologies that are required for industry, and that's where the limitation is right now. We're working with an organization called Humly, they're focused on those ontologies for specific industries. So if the robot doesn't understand something, then you could say to the robot Okay sit that in the Wells account, if you're in a bank, and it understands that Wells in that case means Wells Fargo it doesn't mean a hole in the ground with water at the bottom or a town in Somerset in the UK, 'cause they're all wells. So it's getting that understanding correct. >> I wonder if you guys could comment on this. Stu and I were at Splunk earlier this week and they were talking up NLP and we were saying one of the problems is that NLP is sometimes not that great. And they made a comment that I thought was very interesting. They said frankly a lot of the stuff that we're ingesting is text and it's actually pretty good. I would imagine the same is true for RPA. Is that what you see? >> You were talking about that on stage. With regards to the text analytics. >> Yes. So RPA doesn't handle unstructured content the way that NLP does. So NLP can handle voice, it can handle text. For the bots to work in RPA today you have to have a layer of analytics that understands those documents, understands those emails and creates a nice clean file that the bots can then work with. But what's happening is the text analytics layer is slowly merging with the RPA bots platforms so it's going to be viewed as one solution. But it's more about categories of use cases that deal with forms and documents and emails rather than natural language, which is where it's at. >> So known business processes really is the starting point. >> Known business-- >> One example we've got live is an insurance company in South Africa called Hollard, and they've used a combination of Microsoft Cognitive Toolkit, plus IBM Watson and it's orchestrated doing NLP and orchestrated by UiPath. So that's dealing with utterly unstructured data. That's the 1.5 million emails that that organization gets in a year. They've managed to automate 98% of that, so it never sees a human. And their reduction in cost is 91% cost in reduction per transaction. And that's done by one of our implementation partners, a company called LarcAI down there. It's superb. >> Yeah, so text analytics is hard. Last several years we have that sentiment out of it, but if I understand it correctly Craig, you're saying if you apply it to a known process it actually could have outcomes that can save money. >> Yes, absolutely yes. >> As Guy was just saying. >> I think it's moving from that rules-based activity to more experience-based activity as more of these technologies become merged. >> Will the technology in your view advance to the point, because the known processes. okay, there's probably a lot of work to be done there, but today there's so many unknown processes. It's like this messy, unpredictable thing. Will machine intelligence combined with robotic process automation get to the point, and if so when, that we can actually be more flexible and adapt to some of these unknown processes or is that just decades off? >> No, no, I think we talk at Forrester about the concept of convergence. Meaning the convergence of the physical world and the digital world. So essentially digital's getting embedded in everything physical that we have right. Think of IoT applications and so forth. But essentially that data coming from those physical devices is unstructured data that the machine learning algorithms are going to make sense of, and make decisions about. So we're very close to seeing that in factory environments. We're seeing that in self-driving cars. The fleet managers that are now understanding where things are based on the signals coming from them. So there's a lot of opportunity that's right here on the horizon. >> Craig, a lot of the technologies you mentioned, we may have had a lot of the technical issues sorted out, but it's the people interactions some things like autonomous vehicles, there's government policies going to be one of the biggest inhibitors out there. When you look at the RPA space, what should workers how do they prepare for this? How do companies, make sure that they can embrace this and be better for it? >> That's a really tough and thoughtful question. The RPA category really attacks what we call the cubicle population. And there are we're estimating four million cubicles will be emptied out in five years by RPA technology specifically. That's how we built the market forecast 'cause each one of the digital workers replacing a cubicle worker will cost $11,000 or what. That's how we built up the market forecast. They're going to be automation deficits. It's not all going to be relocating people. We think that there's going to be a lot of disruption in the outsource community first. So companies are going to look at contractors. They're going to look at the BPO contract. Then they're going to look at their internal staff. Our numbers are pretty clear. We think they're going to be four million automation deficits in five years due to RPA technology specifically. Now there will be better jobs for those that are remaining. But I think it's a big change management issue. When you first talk about robots to employees you can tell them that their jobs are going to get better, they're going to be more human. They're going to have a much more exhilarating experience. And their response to you is, What they're thinking is, "Damn robot's going to take my job." That's what they're thinking. So you have to walk them up the mountain and really understand what their career path is and move them into this motion of adaptive and continual learning and what we call constructive ambition. Which is another whole subject. But there are employees that have a higher level of curiosity and are more willing to adapt to get on the other side of the digital divide. Yep. >> You mentioned the market. You guys did a market forecast. I've seen, read stats, a little over a billion today. I don't know if that's consistent with your numbers? >> Yeah that's about right. >> Is this a 10X market? When does it get to 10 billion? Is it five, seven, 10 years? >> So we go out five years and have it be close to three billion. I think the numbers I presented on stage were 3.2 billion in five years. Now that's just software licenses and it's not the services community that surround that. >> You'd probably triple it if you add in services. >> I think two to three times service license ratio. There's always an issue at this point in emerging markets. Some of the valuations that are there, that market three billion has to be a bit bigger than that in eight or nine years to justify those valuations. That's always the fascinating capital structure questions we create with these sorts of things. >> So you describe this sort of one for one replacement. I'm presuming there's other potential use cases, or maybe not, that you forecast. Is that right? >> Oh no for the cubicles? >> Yes, it's not just cubicle replacement in that three billion right? It's other uplifts. >> No there are use cases that help in factory automation, in supply chain, in guys carrying around clipboards in warehouses. There are a tremendous number of use cases, but the primary focus are back office workers that tend to be in cubicles and contact center employees who are always in cubicles. >> And then we'll see if the non-obvious ones emerge. >> I think ultimately what's going to happen is the number of people doing back office corporate functions, so that's both finance and accounting procurement, HR type roles and indeed the industry specific roles. So claims processing insurance will diminish over time. But I think what we're going to see is an increase in the number of people doing customer experience, because it's the customer intimacy that is really going to differentiate organizations going forward. >> The market's moving very fast. Reading your report, it's like you were saying yesterday's features are now table steaks. Everybody's watching everybody else. You heard Daniel today saying, "Hey our competitors are watching. "We're open they're going to steal from us so be it." The rising tide lifts all boats. What do you advise clients in terms of where they should start, how they should get started? Obviously pick some quick wins. But what do you tell people? >> I always same pretty much the same advice you give almost on any emerging technology. Start with a good solution provider that you trust. Focus on a proof of concept, POC and a pilot. Start small and grow incrementally, and walk people up the mountain as you do that. That's the solution. I also have this report I call The Rule of Fives, that there are certain tasks that are perfect for RPA and they should meet these three rules of five. A relatively small number of decisions, relatively small number of applications involved, and a relatively small number of clicks in the click stream. 500 clicks, five apps, five decisions. Look for those in high volume that have high transaction volume and you'll hit RPA goal. You'll be able to offset 2 1/2 to four FTE's for one bot. And if you follow those rules, follow the proof of concept, good solution partner everyone's winning. >> You have practical advice to get started and actually get to an outcome. Anything you'd add to that? >> In most organizations what they're now doing, is picking one, two, or three different technologies to actually play with to start. And that's a really good way. So we recommend that organizations pick three, four, five processes and do a hackathon and very quickly they work out which organizations they want to work with. It's not necessarily just the technology and in a lot of cases UiPath isn't the right answer. But that is a very good way for them to realize what they want to do and the speed with which they'll want to do it. >> Great, well guys thanks for coming on theCUBE, sharing your knowledge. >> Thank you. >> Pleasure. >> Appreciate your time. >> Thanks very much indeed. >> Alright keep it right there everybody. Stu and I will be back from UiPathForward Americas. This is theCUBE. Be right back. (upbeat music)

(lively music) >> Hi and welcome to another CUBEConversation, I'm Peter Burris from our outstanding studio in Palo Alto, California, and today we're talking security which is a specially important topic in today's digital business driven world. And specifically we've got Slavik Markovich, who's the CEO and founder of Demisto. Welcome to theCUBE. >> Thanks for having me here. >> So Slavik, there's so many directions we can take the conversation about security these days, but let's just start with a relatively simple one. Security operations is becoming increasingly important but remains especially complex. How is the problem manifesting itself in business today? >> Yeah, so I would summarize it really simply as having too many with too few. There's just too many alerts, too many security tools, very fragmented landscape, and there's not enough analysts to handle all the security events that are coming up. And so this is a huge problem in a sense that security's hurt by that. You have a lot of events that are just left on the table unhandled. And so, that's what we are kind of trying to solve, is helping the analysts basically have a much better life and process and handling those kind of issues much more efficiently. >> So if you go inside, if you go to a security operation center, a SOC, you rarely encounter a party. >> Yeah, they're not happy. >> The more likely scenario is you see some people who are highly stressed and largely unhappy, and counting the hours until they can retire. And partly, that's a function of the fact that we got all these tools, and we got all these, higher increasing risks as more folks attack, but there's also some uncertainties associated with actually how processes work. So to what degree can a solution like Demisto bring some clarity to how security processes should operate within a SOC? >> Yeah, it's a great question. So as you said, when you go and visit those analysts, they're very unhappy. They're unhappy because people have this concept of when you go into security, you're going to deal with the sophisticated stuff, you're going to deal with finding that nation-state attacker, and this malicious, super persistent malware and some. >> Oh you're at the top. You're going to be a hero. >> Yes, you're going to be the hero. And that's a very interesting perception, but the end result is that most of your day is handling the basic failed logins and VPN alerts, and change password requests, and phishing attempts. Things that are very mundane. >> High risk drudgery. >> Yes, high risk drudgery. That's perfect. And so those analysts just hate this process, and they spend so much time on it, and this is why you see this turnover of analysts that don't last over 18 months or 20 months in a job because they are dealing with all this mundane stuff. And even when you are dealing with the more interesting stuff, that's, as you said, there's no consistent process of how to handle it. And there might be a document somewhere on your weak, your sharp point, that specifies what you should do. But there's no way to actually quality assure that and make sure that what you're doing is indeed matching the process. And so, yeah the analysts are getting bogged down by those mundane alerts, don't have time to look at the interesting stuff, and when they do have time, it's very hard to follow the process. And what we at Demisto are doing and trying to fix that problem, is that we are trying to solve it by having a single platform handling all of the life of the SOC. Meaning handling all the knowledge management, all the processes, and the people are signing in all of that. And so what we're doing is having a full kind of case management for incidents, including all the metrics, and all the salays and assignments, and evidence-tracking and reproductively signing them, and so on. But beyond that, we all you to specify a consistent process like you do in a visual chart. So you basically just drag and drop all the steps, and we then allow you to take those steps and replace them with automations. Because we have integrations with hundreds of security tools. And those hundreds of security tools provide thousands of actions that you can do across those security tools. And so, when you have a step that says check the prevalence of this file, or detonate this in a sandbox, or do any of those, you can actually replace that manual step with an automation and save the analyst the time of actually going ahead and doing that. And so, not only we're bringing consistency to the process, but we're also bringing a lot of efficiencies because you can just replace those manual tasks, and then a lot of the kind of simple mundane incidents, you can just take away from the analyst completely so he can focus on the really important stuff. And then beyond that what we're offering is when you have to get off the pre-defined process, and so we're dealing with a smart adversary, some of them are super smart, it's not-- >> Some of them are the smartest. A lot of money to be made in messing the other companies up these days. >> Exactly, and not all incidents are cookie cutter, and so when you have to get off the pre-defined process, we allow the analyst actually to collaborate with other analysts, invite them to our virtual war room, and then also talk with our bot and do interactive stuff beyond the pre-defined. So we can go to our D-Bot and say, hey, dear D-Bot, retrieve this file from this end point, detonate it in this sandbox, bring me the result. Oh, it's malicious. Then isolate the end-point and block this IP. And you can do all of that in one single place without going to 10 different tools and then copy-pasting it into your case-management system. >> Right, so let me get sure I got the summary. Because you said a lot there. >> Yeah. >> So, trend. A lot more users whether they're actually human beings, or devices. Much greater surface area from an attack standpoint, so a lot more events are being generated. Those events can now be trapped by an existing tool set that, again, corresponds to that degree of specialization, and then when they generate alert, you have a low code approach to being able to, through APIs, capture that information, simply describe automations, and then have the shop follow the processes and conventions and routines associated with the automations that they design. Have I got that right? >> Exactly, and so it's not like we're saying we're going to replace your analyst with automation. That's usually not the case. But we do allow you to basically apply a process, a consistent process, that has automations to make their analysts work much more efficient. And so, as you said, an incident comes in and it can be from various sources. It can be from a high-fidelity security tool, or from your theme, or from your mailbox, somebody reporting abuse or something like that. We take that incident, automatically apply the process, run all the automations, and then allow the analyst to make the important decisions. So the analyst sees the data and then decides, oh, you know what, this is malicious, and then we can do the response. Or it's not malicious, and then we can close the ticket and so on. But we're not replacing the analyst, we're just elevating his level. >> Are a lot of these integrations out of the box? >> Yeah, we have over 200 integrations out of the box with your usual security tools, IT tools, active directory, and your end-point, your network, and so on, so forth. >> And the second related question is obviously one of the biggest challenges that you face with any of these very powerful tools is that they can take a long time to configure, set up, and then roll out. Time to value associated with Demisto. What is it? >> So just the installation and configuration of the integrations, it's a matter of an hour and you're up and running. But then when you take a use case and build a playbook and automation for that, this is usually takes a day. So per use case, it takes time to adjust it to the process of the enterprise. And so out of the box we come with about 50 playbooks, but then an enterprise will take those playbooks and adjust them to their own processes. >> That's great, so you've been around since 2015, first shipped 2016. Where are you on maturity? >> So we've been growing like crazy, in a sense. We're now releasing our fourth version of the product. 4.0 is coming to Black Hat. We have hundreds of customers, about over 100 employees, and we've been growing and hiring aggressively. >> So if you think about what the next two years is going to be, higher risk, more devices, more work to do, but tooling like Demisto is going to be able to better manage a lot of that and facilitate collaboration amongst the team. For example, I believe you have some previous slack integration reckoned in the tool. >> Yeah, that's true. >> So this becomes a way that you can actually, it's a tool for running your SOC. >> Exactly, it's a tool to run your SOC. But when we kind of look ahead of that, what we really focus on, what I'm excited about, is the capability to enhance or add more efficiencies to the process by using machine learning, and then trying to learn from the organization and feed that knowledge back into the organization. So if we see analysts interact with our bot and asking for certain actions for certain types of incidents with certain indicators, we can learn from that and then a new incident comes in, we can then recommend it and say, hey, you know what, what we've seen in previous incidents, this is what worked. This is a sequence of actions that worked, and we can feed that back into the analyst. And we can actually feed it back into building the playbooks and enriching them even more. So I think we can actually use machine learning across the entire kind of platform, and even take it out outside of the SOC and into other use cases. So we already integrate with AWS, so we can actually help you with all the Cloud securities. If you detect something we can take a snapshot, we can change IAM-- >> You mean end to end. >> End to end. >> So they're going to do fine with their own security, but you mean end to end 'cause you're incorporating them into your security chain. >> So we view ourselves as kind of the brain of the process, so we want to help you define what should happen and we'll actually invoke and execute that across your security tools. So part of it can be on AWS, part of it can be with your compliance team or with your vulnerability assessment team or OP security team, kind of expand even beyond the traditional use cases of the SOC into anything in fact in security that has a process tied to it. >> Slavik, thanks very much for being on theCUBE and talking about security. Incredibly important topic that requires a lot more conversation, but even more doing. >> Hey, thanks for having me. >> So once again, Slavik Markovich is the CEO and founder of Demisto, and you've been watching another CUBEConversation. Until next time. (lively music)

>> From Times Square, in the heart of New York City, it's theCUBE. Covering, Imagine 2018. Brought to you by, Automation Anywhere. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We're in downtown Manhattan at Automation Anywhere, Imagine 2018. Eleven hundred people buzzing all around us here. The eco system is hot, everybody's looking at all the various solutions, all the various bots, all the various activities going on. And we're excited to have relatively newcomer to the company. He's Kashif Mahbub, the VP, Product Marketing for Automation Anywhere. Kashif, welcome. >> Thanks for having me. >> So you said you've been here, we've had all the founders on I think, so you've been here about a year. So, first impressions, I imagine this is your first show, what do you think? >> It's actually my third show. >> Oh it is your show. >> Things are moving. >> Oh, were you a customer before? >> Company standard, yeah by company standards I would say I'm a veteran. (Jeff laughing) So we are doing these shows, all of these marketing activities at a very rapid pace. >> Very good, so one of the topics we haven't talked about so much today is this kind of digital workforce concept. And you guys have a really specific idea of what makes, kind of taking these things to actually be considered a digital workforce. So what are those three things that you guys combine, to have something that's unique in the market place? >> So we pioneered the concept of digital workforce. And in our parlance, in our definition, a digital workforce, especially at enterprise scale, comprises of three key components. RPA, which is robotic process automation. Cognitive automation, which is the ability of using AI and machine learning capabilities with the RPA. And last but not least, smart analytics. So, the combination of these three make up what we call a digital workforce. If any of one of these elements is missing, we feel that's not really a true digital workforce. So it is the workforce platform that we call enterprise, combines all of these capabilities together to really deliver a true enterprise class, digital workforce platform. >> Now how long have you guys been baking in the AI component of it, in the cognition piece. 'Cause there's a lot of talk about cognitive computing, and it's a big theme that IBM has had for a long, long time, and we're seeing AI work itself in to all kinds of interesting applications. Now kind of, where was your guys' AI journey, how long have you been at it, and where are you seeing kind of the break through to get to this digital workforce concept? >> So automation anywhere has been around for about 15 years now. So we have a very mature product. I look after the enterprise platform, and we just released version 11. So it makes it the most mature platform in the industry at the moment. Now to answer your question about AI, and bringing AI into it, that's fairly recent. But we are based in the heart of Silicon Valley, Google is one of our customers, so is Tesla, so is LinkedIn. These are three big AI companies, with their own AI Technology, yet they use Automation Anywhere platform as well. So, there is AI, and then there is AI with RPA. So think of it as purpose built AI capabilities that are infused through our digital workforce platform, to enhance our RPA capabilities. And you bring in analytics, then we talk about predictive analytics. So overall again, it's building a digital workforce that is enhanced by AI, that is enhanced by cognitive capabilities, so that RPA is not just RPA. It's RPA to the next level. >> Right, and really RPA that's gonna evolve. RPA that's eventually gonna write itself right, or write new versions of itself based on new things. And process improvement, new discoveries in terms of better ways to get things done. Using those other two legs of the spool. >> Yes, so you will see a lot of publications out there that talk about RPA evolving into AI, or AI taking over RPA. The fact is, there is again AI, and then there is AI combined with RPA. So if you take Google's example. Google uses us in the back end, yet it is one of the largest AI companies in the world. So AI, think of it as a big hammer. It has to be used very carefully, and we have purpose built AI into our product to make sure that we extract all the unstructured data. And then we, as Mihir mentioned, our CEO mentioned earlier in the key note, it is feeding this RPA monster that needs more and more data. And all of that data comes through our AI and cognitive capabilities. >> Right, and we know right, and for the machines to learn, they need more, and more, and more data so they get better and better. It's just the way computers do learn. It's very different from the way humans learn, it's a slightly different model. >> It's about building a digital map. You know, we use Waze and Google Maps and all of these different GPS driven capabilities to find our way around, Manhattan for example. Or Bay area for that matter. (Jeff laughing) Think of our digital workforce platform with AI capabilities and with analytics capabilities, as a digital map of an enterprise. We touch so many different infrastructure components. From CRM systems to ERP systems to HRIS systems, that the amount of data that we capture that passes through our system, gives us perhaps the best look that anyone can have into how data flows through an enterprise. And what's the best way to use it. >> Right, so I'm curious in terms of those vertical applications that you described, where have you seen the biggest impact now that you've started to bring the AI in? Are there certain verticals that are just ripe for significant positive change, and some that are less so? >> Yeah absolutely. So, there is a lot of data locked in documents still. So banking, finance and insurance. Those are the three verticals, three industries where our first step with our IQ Bot, which is our cognitive product. We have seen a lot of traction there. The reason for that is again, when we decipher these documents, when we decipher and capture all the data, we then use it very intelligently in automating the processes. So the first step to answer your question would be, organizations, industries that use unstructured data that is locked into their documents, all this dark data of methodology. We unlock that data, and then we use RPA and we feed this RPA monster to really automate the various processes. >> Every time you guys talk about all the data locked in these documents, I can't help but think of the old OCR days, when I got my first $1000 flatbed scanner to try to read a couple documents. It never worked back then, the era of a different place. >> Funny that you mention that because the OCR technology that got built into a lot of scanners later on, a lot of that technology we use under the covers, but at a much more enhanced level. So we partner with some of the best OCR technologies out there, but then we put AI on top of that to really take it to the next level. So when the data comes out of a simple OCR process, it's no longer just some data that you can, like we used to see. Now it's data that is structured, that can be automated in a few clicks. >> It has context right. And most importantly it has context, which makes all the difference in the world. Okay, so what are some of your priorities for next year, before I let you go. What are some of the things you're working on? If we sit down a year from now, what are we gonna be talking about that's new? Don't tell me any secrets, no NDA's have been signed here. (Jeff laughing) >> At Imagine, we come with an approach of an open book. Open kimono if you will, and we share all that we are working on. And all that we are working today, but also going forward. So AI is a big element of that. Automation, combined with any sort of automation, especially RPA combined with AI and machine learning capabilities, that's already, we have a product, as opposed to just an idea. It's a working product with dozens of organizations using it. But then we are infusing that AI into RPA, and making it intelligent RPA. Making it an intelligent digital workforce platform. That's the ultimate goal, and we are already well on our way. >> Alright well Kashif, thanks for a taking a few minutes of your time and congrats on a great show. >> Thank you, thanks for having me Jeff. >> Alright he's Kashif, I'm Jeff, you're watching theCUBE from Automation Anywhere Imagine 2018 in New York City, thanks for watching. (electronic music)