>> Narrator: From San Mateo, California, it's theCUBE covering SnapLogic Innovation Day 2018. Brought to you by SnapLogic. >> Hey, welcome back everybody, Jeff Frick here with theCUBE. We're in San Mateo, California right at the crossroads. The building's called The Crossroads but it's right at the crossroads of 92 and 101. It's a really interesting intersection over the years as you watch these buildings that are on the corner continue to change names. I always think of the Seibel, his first building came up on this corner and we're here to see a good friend of SnapLogic and their brand new building. Gaurav Dhillon, Chairman and CEO, great to see you. >> Pleasure to be here. >> So how long you been in this space? >> Gosh, it's been about a year. >> Okay. >> Although it feels longer. It's a high-growth company so these are dog years. (laughs) >> That's right. and usually, you outgrow it before you all have moved in. >> The years are short but the days are long. >> And it's right next Rakuten, I have to mention it. We all see it on the Warriors' jerseys So now we know who they are and where they are exactly. >> No they're a good outfit. We had an interesting time putting a sign up and then the people who made their sign told us all kinds of back stories. >> Oh, good, good Alright. So give us an update on SnapLogic. You guys are in a great space at a really, really good time. >> You know, things been on a roll. As you know, the mission we set out to... engage with was to bring together applications and data in the enterprise. We have some of the largest customers in high technology. Folks like Qualcomm, Workday. Some of the largest customers in pharmaceuticals. Folks like Astrazeneca, Bristol-Meyers Squibb. In retail, Denny's, Wendy's, etc. And these folks are basically bringing in new cloud applications and moving data into the cloud. And it's really fun to wire that all up for them. And there's more of it every day and now that we have this very strong install-base of customers, we're able to get more customers faster. >> Right. >> In good time. >> It's a great time and the data is moving into the cloud, and the public cloud guys are really making bigger plays into the enterprise, Microsoft and, Amazon and Google. And of course, there's IBM and lots of other clouds. But integration's always been such a pain and I finally figured out what the snap in SnapLogic means after interviewing you >> (laughs) a couple of times, right. But this whole idea of, non-developer development and you're taking that into integration which is a really interesting concept, enabled by cloud, where you can now think of snapping things together, versus coding, coding, coding. >> Yeah Cloud and A.I, right We feel that this problem has grown because of the change in the platform. The compute platform's gone to the cloud. Data's going to the cloud. There was bunch of news the other day about more and more companies moving the analytics into the cloud. And as that's happening, we feel that this approach and the question we ask ourselves when we started this company, we got into building the born in the cloud platform was, what would Apple do if they were to build an integration product? And the answer was, they would make it like the iPhone, which is easy to use, but very powerful at the same time. And if you can do that, you can bring in a massive population of users who wouldn't have been able to do things like video chat. My mom was not able to do video chat, and believe me, we tried this and every other thing possible 'till facetime came along. And now she can talk to my daughter and she can do it without help, any assistance from teenage grandchildren on that side, Right? >> Right, Right >> So what we've done with SnapLogic, is by bringing in a beautiful, powerful, sleek interface, with a lot of capability in how it connects, snaps together apps and data, we've brought in a whole genre of people who need data in the enterprise so they can serve themselves data. So if your title has analyst in it, you don't have to be programmer analyst. You could be any analyst. >> Right >> You could be a compensation analyst, a commissions analyst, a finance analyst, an HR analyst. All those people can self-serve information, knock down silos, and integrate things themselves. >> It's so interesting because we talk a lot about innovation and digital transformation, and in doing thousands of these interviews, I think the answer to innovation is actually pretty simple. You give more people access to the data. You give them more access to the tools to work with the data and then you give them the power to actually do something once they figure something out. And you guys are really right in the middle of that. So before, it was kind of >> (laughs) Yeah >> democratization of the data, democratization of the tools to work with the data, but in the API economy, you got to be able to stitch this stuff together because it's not just one application, it's not just one data source. >> Correct >> You're bringing from lots and lots of different things and that's really what you guys are taking advantage of this cloud infrastructure which has everything available, so it's there to connect, >> (laughs) Versus, silo in company one and silo in company two. So are you seeing it though, in terms of, of people enabling, kind of citizen integrators if you will, versus citizen developers. >> Yeah. Heck Yeah. So I'll give you an example. One of our large customers... Adobe Systems, right here in San Jose has been amazingly successful flagship account for us. About 800 people at Adobe come to www.snaplogic.com, every week to self-serve data. We replaced legacy products like TIBCO, informatica web methods about four years ago. They first became a customer in 2014 and usage of those products was limited to Java programmers and Sequel programmers, and that was less than 50 people. And imagine that you have about 800 people doing self-service getting information do their jobs. Now, Adobe is unique in that, it's moved the cloud in a fantastic way, or it was unique in 2014. Now everybody is emulating them and the great success that they've had. With the cloud economic model, with the cloud ID model. This is working in spades. We have customers who've come on board in Q4. We're just rounding out Q1 and in less than 60, 90 days, every time I look, 50, 100, 200 people, from each large company, whether it's a cosmetics company, pharmaceuticals company, retailer, food merchandise, are coming in and using data. >> Right >> And it's proliferating, because the more successful they are, the better they are able to do in their jobs, tell their friends about it sort-of-thing, or next cubicle over, somebody wants to use that too. It's so interesting. Adobe is such a great example, cause they did transform their business. Used to be a really expensive license. You would try to find your one friend that worked there around Christmas >> (laughs) Cause you think they got two licenses a year they can buy for a grand. Like, I need an extra one I can get from you. But they moved to a subscription model. They made a big bet. >> Yes. Yes >> And they bet on the cloud, so now if you're a subscriber, which I am, I can work on my home machine, my work machine, go to machine, machine. So, it's a really great transformation story. The other piece of it though, is just this cloud application space. There's so many cloud applications that we all work with every day whether it's Basecamp, Salesforce, Hootsuite. There's a proliferation of these things and so they're there. They've got data. So the integration opportunity is unlike anything that was ever there before. Cause there isn't just one cloud. There isn't just one cloud app. There's a lot of them. >> Yes. >> How do I bring those together to be more productive? >> So here's a stat. The average enterprise has most cloud services or SAS applications, in marketing. On the average, they have 91 marketing applications or SAS applications. >> 91. That's the average. >> 96% of them are not connected together. >> Right. >> Okay. That's just one example. Now you go to HR, stock administration. You go into sales, CRM, and all the ancillary systems around CRM. And there is this sort of massive, to us, opportunity of knocking down these silos and making things work together. You mention the API economy and whilst that's true that all these SAS applications of APIs. The problem is, most companies don't have programmers to hook up those API's. >> Right. To connect them. >> Yes, in Silicon Valley we do and maybe in Manhattan they do, but in everywhere else in the world, the self-service model, the model of being able to do it to something that is simple, yet powerful. Enterprise great >> Right. Right >> and simple, beautiful is absolutely the winning formula in our perspective. So the answer is to let these 100 applications bloom, but to keep them well behaved and orchestrated, in kind of a federated model, where security, having one view of the world, etc., is managed by SnapLogic and then various people and departments can bring in a blessed, SAS applications and then snap them in and the input and the way they connect, is done through snaps. And we've found that to be a real winning model for our customers. >> So you don't have to have like 18 screens open all with different browsers and different apps. >> Swivel chair integration is gone. Swivel chair integration is gone. >> Step above sneakernet but still not-- >> Step above but still not. And again, it may make sense in very, very specific super high-speed, like Wall Street, high frequency trading and hedge funds, but it's a minuscule minority of the overall problems that there needs to be solved. >> Right. So, it's just a huge opportunity, you just are cleaning up behind the momentum in the SAS applications, the momentum of the cloud. >> Cloud data. Cloud apps. Cloud data. And in general, if a customer's not going to the cloud, they're probably not the best for us. >> Right. >> Right. Our customers' almost always going towards the cloud, have lots of data and applications on premise. And in that hybrid spot, we have the capability to straddle that kind of architecture in a way that nobody else does. Because we have a born in the cloud platform that was designed to work in the real world, which is hybrid. >> So another interesting thing, a lot of talk about big data over the years. Now it's just kind of there. But AI and machine learning. Artificial intelligence which should be automated intelligence and machine learning. There's kind of the generic, find an old, dead guy and give it a name. But we're really seeing the values that's starting to bubble up in applications. It's not, AI generically, >> Correct. >> It's how are you enabling a more efficient application, a more efficient workflow, a more efficient, get your job done, using AI. And you guys are starting to incorporate that in your integration framework. >> Yes. Yes. So we took the approach, 'doctor heal thyself.' And we're going to help our customers do better job of having AI be a game changer for them. How do we apply that to ourselves? We heard one our CIOs, CI of AstraZeneca, Dave Smoley, was handing out the Amazon Alexa Echo boxes one Christmas. About three years ago and I'm like, my gosh that's right. That was what Walt Mossberg said in his farewell column. IT is going to be everywhere and invisible at the same time. Right. >> Right. >> It'll be in the walls, so to speak. So we applied AI, starting about two years ago, actually now three, because we shipped Iris a year ago. The artificial intelligence capability inside SnapLogic has been shipping for over 12 months. Fantastic usage. But we applied to ourselves the challenge about three years ago, to use AI based on our born in the cloud platform. On the metadata that we have about people are doing. And in the sense, apply Google Autocomplete into enterprise connectivity problems. And it's been amazing. The AI as you start to snap things together, as you put one or two snaps, and you start to look for the third, it starts to get 98.7% accurate, in predicting how to connect SAS applications together. >> Right. Right. >> It's not quite autonomous integration yet but you can see where we're going with it. So it's starting to do so much value add that most of our customers, leave it on. Even the seasoned professionals who are proficient and running a center of excellence using SnapLogic, even those people choose to have sort-of this AI, on all the time helping them. And that engagement comes from the value that they're getting, as they do these things, they make less mistakes. All the choices are readily at hand and that's happening. So that's one piece of it >> Right. >> Sorry. Let me... >> It's Okay. Keep going. >> Illustrate one other thing. Napoleon famously said, "An army marches on its stomach" AI marches on data. So, what we found is the more data we've had and more customers that we've had, we move about a trillion documents for our customers worldwide, in the past 30 days. That is up from 10 million documents in 30 days, two years ago. >> Right. Right >> That more customers and more usage. In other words, they're succeeding. What we've found as we've enriched our AI with data, it's gotten better and better. And now, we're getting involved with customers' projects where they need to support data scientists, data engineering work for machine learning and that self-service intricate model is letting someone who was trying to solve a problem of, When is my Uber going to show up? So to speak. In industry X >> Right. Right. >> These kinds of hard AI problems that are predictive. That are forward changing in a sense. Those kind of problems are being solved by richer data and many of them, the projects that we're now involved in, are moving data into the cloud for data lake to then support AI machine learning efforts for our customers. >> So you jumped a little bit, I want to talk on your first point. >> Okay. Sorry >> That's okay. Which is that you're in the very fortunate position because you have all that data flow. You have the trillion documents that are changing hands every month. >> Born in the cloud platform. >> So you've got it, right? >> Got it. >> You've got the data. >> It's a virtual cycle. It's a virtual cycle. Some people call it data capitalism. I quibble with that. We're not sort-of, mining and selling people's personal data to anybody. >> Right. Right. >> But this is where, our enterprise customers' are so pleased to work with us because if we can increase productivity. If we can take the time to solution, the time to integration, forward by 10 times, we can improve the speed that by SAS application and it gets into production 10 times faster. That is such a good trade for them and for everyone else. >> Right. Right. >> And it feeds on itself. It's a virtual cycle. >> You know in the Marketo to the Salesforce integration, it's nothing. You need from company A to company B. >> I bet you somebody in this building is doing it on a different floor right now. >> Exactly. >> (laughs) >> So I think that's such an interesting thing. In the other piece that I like is how again, I like your kind of Apple analogy, is the snap packs, right. Because we live in a world, with even though there 91 on-averages, there's a number of really dominant SAS application that most people use, you can really build a group of snaps. Is snap the right noun? >> That's the right word. >> Of snaps. In a snap pack around the specific applications, then to have your AI powered by these trillion transactions that you have going through the machines, really puts you in a unique position right now. >> It does, you know. And we're very fortunate to have the kind of customer support we've had and, sort of... Customer advisory board. Big usages of our products. In which we've added so much value to our customers, that they've started collaborating with us in a sense. And are passing to us wonderful ideas about how to apply this including AI. >> Right. >> And we're not done yet. We have a vision in the future towards an autonomous integration. You should be able to say "SnapLogic, Iris, "connect my company." And it should. >> Right. Right. >> It knows what the SAS apps are by looking at your firewall, and if you're people are doing things, building pipelines, connecting your on-premise legacy applications kind of knows what they are. That day when you should be able to, in a sense, have a bot of some type powered by all this technology in a thoughtful manner. It's not that far. It's closer at hand than people might realize. >> Which is crazy science fiction compared to-- I mean, integration was always the nightmare right back in the day. >> It is. >> Integration, integration. >> But on the other hand, it is starting to have contours that are well defined. To your point, there are certain snaps that are used more. There are certain problems that are solved quite often, the quote-to-cash problem is as old as enterprise software. You do a quote in the CRM system. Your cash is in a financial system. How does that work together? These sort of problems, in a sense, are what McKinsey and others are starting to call robotic process automations. >> Right. >> In the industrial age, people... Stopped, with the industrial age, any handcrafted widget. Nuts, and bolts, and fasteners started being made on machines. You could stamp them out. You could have power driven beams, etc., etc. To make things in industrial manner. And our feeling is, some of the knowledge tasks that feel like widget manufactures. You're doing them over and over again. Or robotic, so to speak, should be automated. And integration I think, is ripe as one of those things and using the value of integration, our customers can automate a bunch of other repeatable tasks like quote-to-cash. >> Right. Right. It's interesting just when you say autonomous, I can't help but think of autonomous vehicles right, which are all the rage and also in the news. And people will say "well I like to drive "or of course we all like to drive "on Sunday down at the beach" >> Sure. Yeah. >> But we don't like to sit in traffic on the way to work. That's not driving, that's sitting in traffic on the way to work. Getting down the 101 to your exit and off again is really not that complicated, in terms of what you're trying to accomplish. >> Indeed. Indeed. >> Sets itself up. >> And there are times you don't want to. I mean one of the most pleasant headlines, most of the news is just full of bad stuff right. So and so and such and such. But one of the very pleasing headlines I saw the other day in a newspaper was, You know what's down a lot? Not bay area housing prices. >> (laughs) >> But you know what's down a lot? DUI arrests, have plummeted. Because of the benefits of Lyft and Uber. More and more people are saying, "You know, I don't have to call a black cab. "I don't need to spend a couple hundred bucks to get home. "I'm just getting a Lyft or an Uber." So the benefits of some of these are starting to appear as in plummeting DUIs. >> Right. Right >> Plummeting fatalities. From people driving while inebriated. Plunging into another car or sidewalk. >> Right. Right. >> So Yes. >> Amara's Law. He never gets enough credit. >> (laughs) >> I say it in every interview right. We overestimate in the short term and we underestimate in the long term the effects of these technologies cause we get involved-- The Gartner store. It's the hype cycle. >> Yeah, Yeah >> But I really I think Amara nailed it and over time, really significant changes start to take place. >> Indeed and we're seeing them now. >> Alright well Gaurav, great to get an update from you and a beautiful facility here. Thanks for having us on. >> Thank you, thank you. A pleasure to be here. Great to see you as well. >> Alright He's Gaurav, I'm Jeff. And you're watching theCUBE from SnapLogic's headquarters Thanks for watching. (techno music)

>> Narrator: From San Mateo, California, it's theCUBE covering SnapLogic Innovation Day 2018. Brought to you by SnapLogic. >> Hey, welcome back everybody, Jeff Frick here with theCUBE. We're in San Mateo, California right at the crossroads. The building's called The Crossroads but it's right at the crossroads of 92 and 101. It's a really interesting intersection over the years as you watch these buildings that are on the corner continue to change names. I always think of the Seville, his first building came up on this corner and we're here to see a good friend of SnapLogic and their brand new building. Gaurav Dhillon, Chairman and CEO, great to see you. >> Pleasure to be here. >> So how long you been in this space? >> Gosh, it's been about a year. >> Okay. >> Although it feels longer. It's a high-growth company so these are dog years. (laughs) >> That's right. and usually, you outgrow it before you all have moved in. >> The years are short but the days are long. >> And it's right next Rakuten, I have to mention it. We all see it on the Warriors' jerseys So now we know who they are and where they are exactly. >> No they're a good outfit. We had an interesting time putting a sign up and then the people who made their sign told us all kinds of back stories. >> Oh, good, good Alright. So give us an update on SnapLogic. You guys are in a great space at a really, really good time. >> You know, things been on a roll. As you know, the mission we set out to... engage with was to bring together applications and data in the enterprise. We have some of the largest customers in high technology. Folks like Qualcomm, Workday. Some of the largest customers in pharmaceuticals. Folks like Astrazeneca, Bristol-Meyers Squibb. In retail, Denny's, Wendy's, etc. And these folks are basically bringing in new cloud applications and moving data into the cloud. And it's really fun to wire that all up for them. And there's more of it every day and now that we have this very strong install-base of customers, we're able to get more customers faster. >> Right. >> In good time. >> It's a great time and the data is moving into the cloud, and the public cloud guys are really making bigger plays into the enterprise, Microsoft and, Amazon and Google. And of course, there's IBM and lots of other clouds. But integration's always been such a pain and I finally figured out what the snap in SnapLogic means after interviewing you >> (laughs) a couple of times, right. But this whole idea of, non-developer development and you're taking that into integration which is a really interesting concept, enabled by cloud, where you can now think of snapping things together, versus coding, coding, coding. >> Yeah Cloud and A.I, right We feel that this problem has grown because of the change in the platform. The compute platform's gone to the cloud. Data's going to the cloud. There was bunch of news the other day about more and more companies moving the analytics into the cloud. And as that's happening, we feel that this approach and the question we ask ourselves when we started this company, we got into building the born in the cloud platform was, what would Apple do if they were to build an integration product? And the answer was, they would make it like the iPhone, which is easy to use, but very powerful at the same time. And if you can do that, you can bring in a massive population of users who wouldn't have been able to do things like video chat. My mom was not able to do video chat, and believe me, we tried this and every other thing possible 'till facetime came along. And now she can talk to my daughter and she can do it without help, any assistance from teenage grandchildren on that side, Right? >> Right, Right >> So what we've done with SnapLogic, is by bringing in a beautiful, powerful, sleek interface, with a lot of capability in how it connects, snaps together apps and data, we've brought in a whole genre of people who need data in the enterprise so they can serve themselves data. So if your title has analyst in it, you don't have to be programmer analyst. You could be any analyst. >> Right >> You could be a compensation analyst, a commissions analyst, a finance analyst, an HR analyst. All those people can self-serve information, knock down silos, and integrate things themselves. >> It's so interesting because we talk a lot about innovation and digital transformation, and in doing thousands of these interviews, I think the answer to innovation is actually pretty simple. You give more people access to the data. You give them more access to the tools to work with the data and then you give them the power to actually do something once they figure something out. And you guys are really right in the middle of that. So before, it was kind of >> (laughs) Yeah >> democratization of the data, democratization of the tools to work with the data, but in the API economy, you got to be able to stitch this stuff together because it's not just one application, it's not just one data source. >> Correct >> You're bringing from lots and lots of different things and that's really what you guys are taking advantage of this cloud infrastructure which has everything available, so it's there to connect, >> (laughs) Versus, silo in company one and silo in company two. So are you seeing it though, in terms of, of people enabling, kind of citizen integrators if you will, versus citizen developers. >> Yeah. Heck Yeah. So I'll give you an example. One of our large customers... Adobe Systems, right here in San Jose has been amazingly successful flagship account for us. About 800 people at Adobe come to www.snaplogic.com, every week to self-serve data. We replaced legacy products like DIBCO, informatica web methods about four years ago. They first became a customer in 2014 and usage of those products was limited to Java programmers and Sequel programmers, and that was less than 50 people. And imagine that you have about 800 people doing self-service getting information do their jobs. Now, Adobe is unique in that, it's moved the cloud in a fantastic way, or it was unique in 2014. Now everybody is emulating them and the great success that they've had. With the cloud economic model, with the cloud ID model. This is working in spades. We have customers who've come on board in Q4. We're just rounding out Q1 and in less than 60, 90 days, every time I look, 50, 100, 200 people, from each large company, whether it's a cosmetics company, pharmaceuticals company, retailer, food merchandise, are coming in and using data. >> Right >> And it's proliferating, because the more successful they are, the better they are able to do in their jobs, tell their friends about it sort-of-thing, or next cubicle over, somebody wants to use that too. It's so interesting. Adobe is such a great example, cause they did transform their business. Used to be a really expensive license. You would try to find your one friend that worked there around Christmas >> (laughs) Cause you think they got two licenses a year they can buy for a grand. Like, I need an extra one I can get from you. But they moved to a subscription model. They made a big bet. >> Yes. Yes >> And they bet on the cloud, so now if you're a subscriber, which I am, I can work on my home machine, my work machine, go to machine, machine. So, it's a really great transformation story. The other piece of it though, is just this cloud application space. There's so many cloud applications that we all work with every day whether it's Basecamp, Salesforce, Hootsuite. There's a proliferation of these things and so they're there. They've got data. So the integration opportunity is unlike anything that was ever there before. Cause there isn't just one cloud. There isn't just one cloud app. There's a lot of them. >> Yes. >> How do I bring those together to be more productive? >> So here's a stat. The average enterprise has most cloud services or SAS applications, in marketing. On the average, they have 91 marketing applications or SAS applications. >> 91. That's the average. >> 96% of them are not connected together. >> Right. >> Okay. That's just one example. Now you go to HR, stock administration. You go into sales, CRM, and all the ancillary systems around CRM. And there is this sort of massive, to us, opportunity of knocking down these silos and making things work together. You mention the API economy and whilst that's true that all these SAS applications of APIs. The problem is, most companies don't have programmers to hook up those API's. >> Right. To connect them. >> Yes, in Silicon Valley we do and maybe in Manhattan they do, but in everywhere else in the world, the self-service model, the model of being able to do it to something that is simple, yet powerful. Enterprise great >> Right. Right >> and simple, beautiful is absolutely the winning formula in our perspective. So the answer is to let these 100 applications bloom, but to keep them well behaved and orchestrated, in kind of a federated model, where security, having one view of the world, etc., is managed by SnapLogic and then various people and departments can bring in a blessed, SAS applications and then snap them in and the input and the way they connect, is done through snaps. And we've found that to be a real winning model for our customers. >> So you don't have to have like 18 screens open all with different browsers and different apps. >> Swivel chair integration is gone. Swivel chair integration is gone. >> Step above sneakernet but still not-- >> Step above but still not. And again, it may make sense in very, very specific super high-speed, like Wall Street, high frequency trading and hedge funds, but it's a minuscule minority of the overall problems that there needs to be solved. >> Right. So, it's just a huge opportunity, you just are cleaning up behind the momentum in the SAS applications, the momentum of the cloud. >> Cloud data. Cloud apps. Cloud data. And in general, if a customer's not going to the cloud, they're probably not the best for us. >> Right. >> Right. Our customers' almost always going towards the cloud, have lots of data and applications on premise. And in that hybrid spot, we have the capability to straddle that kind of architecture in a way that nobody else does. Because we have a born in the cloud platform that was designed to work in the real world, which is hybrid. So another interesting thing, a lot of talk about big data over the years. Now it's just kind of there. But AI and machine learning. Artificial intelligence which should be automated intelligence and machine learning. There's kind of the generic, find an old, dead guy and give it a name. But we're really seeing the values that's starting to bubble up in applications. It's not, AI generically, >> Correct. >> It's how are you enabling a more efficient application, a more efficient workflow, a more efficient, get your job done, using AI. And you guys are starting to incorporate that in your integration framework. >> Yes. Yes. So we took the approach, 'doctor heal thyself.' And we're going to help our customers do better job of having AI be a game changer for them. How do we apply that to ourselves? We heard one our CIOs, CI of AstraZeneca, Dave Smoley, was handing out the Amazon Alexa Echo boxes one Christmas. About three years ago and I'm like, my gosh that's right. That was what Walt Mossberg said in his farewell column. IT is going to be everywhere and invisible at the same time. Right. >> Right. >> It'll be in the walls, so to speak. So we applied AI, starting about two years ago, actually now three, because we shipped iris a year ago. The artificial intelligence capability inside SnapLogic has been shipping for over 12 months. Fantastic usage. But we applied to ourselves the challenge about three years ago, to use AI based on our born in the cloud platform. On the metadata that we have about people are doing. And in the sense, apply Google Autocomplete into enterprise connectivity problems. And it's been amazing. The AI as you start to snap things together, as you put one or two snaps, and you start to look for the third, it starts to get 98.7% accurate, in predicting how to connect SAS applications together. >> Right. Right. >> It's not quite autonomous integration yet but you can see where we're going with it. So it's starting to do so much value add that most of our customers, leave it on. Even the seasoned professionals who are proficient and running a center of excellence using SnapLogic, even those people choose to have sort-of this AI, on all the time helping them. And that engagement comes from the value that they're getting, as they do these things, they make less mistakes. All the choices are readily at hand and that's happening. So that's one piece of it >> Right. >> Sorry. Let me... >> It's Okay. Keep going. >> Illustrate one other thing. Napoleon famously said, "An army marches on it's stomach" AI marches on data. So, what we found is the more data we've had and more customers that we've had, we move about a trillion documents for our customers worldwide, in the past 30 days. That is up from 10 million documents in 30 days, two years ago. >> Right. Right >> That more customers and more usage. In other words, they're succeeding. What we've found as we've enriched our AI with data, it's gotten better and better. And now, we're getting involved with customers' projects where they need to support data scientists, data engineering work for machine learning and that self-service intricate model is letting someone who was trying to solve a problem of, When is my Uber going to show up? So to speak. In industry X >> Right. Right. >> These kinds of hard AI problems that are predictive. That are forward changing in a sense. Those kind of problems are being solved by richer data and many of them, the projects that we're now involved in, are moving data into the cloud for data lake to then support AI machine learning efforts for our customers. >> So you jumped a little bit, I want to talk on your first point. >> Okay. Sorry >> That's okay. Which is that you're in the very fortunate position because you have all that data flow. You have the trillion documents that are changing hands every month. >> Born in the cloud platform. >> So you've got it, right? >> Got it. >> You've got the data. >> It's a virtual cycle. It's a virtual cycle. Some people call it data capitalism. I quibble with that. We're not sort-of, mining and selling people's personal data to anybody. >> Right. Right. >> But this is where, our enterprise customers' are so pleased to work with us because if we can increase productivity. If we can take the time to solution, the time to integration, forward by 10 times, we can improve the speed that by SAS application and it gets into production 10 times faster. That is such a good trade for them and for everyone else. >> Right. Right. >> And it feeds on itself. It's a virtual cycle. >> You know in the Marketo to the Salesforce integration, it's nothing. You need from company A to company B. >> I bet you somebody in this building is doing it on a different floor right now. >> Exactly. >> (laughs) >> So I think that's such an interesting thing. In the other piece that I like is how again, I like your kind of Apple analogy, is the snap packs, right. Because we live in a world, with even though there 91 on-averages, there's a number of really dominant SAS application that most people use, you can really build a group of snaps. Is snap the right noun? >> That's the right word. >> Of snaps. In a snap pack around the specific applications, then to have your AI powered by these trillion transactions that you have going through the machines, really puts you in a unique position right now. >> It does, you know. And we're very fortunate to have the kind of customer support we've had and, sort of... Customer advisory board. Big usages of our products. In which we've added so much value to our customers, that they've started collaborating with us in a sense. And are passing to us wonderful ideas about how to apply this including AI. >> Right. >> And we're not done yet. We have a vision in the future towards an autonomous integration. You should be able to say "SnapLogic, Iris, "connect my company." And it should. >> Right. Right. >> It knows what the SAS apps are by looking at your firewall, and if you're people are doing things, building pipelines, connecting your on-premise legacy applications kind of knows what they are. That day when you should be able to, in a sense, have a bot of some type powered by all this technology in a thoughtful manner. It's not that far. It's closer at hand than people might realize. >> Which is crazy science fiction compared to-- I mean, integration was always the nightmare right back in the day. >> It is. >> Integration, integration. >> But on the other hand, it is starting to have contours that are well defined. To your point, there are certain snaps that are used more. There are certain problems that are solved quite often, the quote-to-cash problem is as old as enterprise software. You do a quote in the CRM system. Your cash is in a financial system. How does that work together? These sort of problems, in a sense, are what McKinsey and others are starting to call robotic process automations. >> Right. >> In the industrial age, people... Stopped, with the industrial age, any handcrafted widget. Nuts, and bolts, and fasteners started being made on machines. You could stamp them out. You could have power driven beams, etc., etc. To make things in industrial manner. And our feeling is, some of the knowledge tasks that feel like widget manufactures. You're doing them over and over again. Or robotic, so to speak, should be automated. And integration I think, is ripe as one of those things and using the value of integration, our customers can automate a bunch of other repeatable tasks like quote-to-cash. >> Right. Right. It's interesting just when you say autonomous, I can't help but think of autonomous vehicles right, which are all the rage and also in the news. And people will say "well I like to drive "or of course we all like to drive "on Sunday down at the beach" >> Sure. Yeah. >> But we don't like to sit in traffic on the way to work. That's not driving, that's sitting in traffic on the way to work. Getting down the 101 to your exit and off again is really not that complicated, in terms of what you're trying to accomplish. >> Indeed. Indeed. >> Sets itself up. >> And there are times you don't want to. I mean one of the most pleasant headlines, most of the news is just full of bad stuff right. So and so and such and such. But one of the very pleasing headlines I saw the other day in a newspaper was, You know what's down a lot? Not bay area housing prices. >> (laughs) >> But you know what's down a lot? DUI arrests, have plummeted. Because of the benefits of Lyft and Uber. More and more people are saying, "You know, I don't have to call a black cab. "I don't need to spend a couple hundred bucks to get home. "I'm just getting a Lyft or an Uber." So the benefits of some of these are starting to appear as in plummeting DUIs. >> Right. Right >> Plummeting fatalities. From people driving while inebriated. Plunging into another car or sidewalk. >> Right. Right. >> So Yes. >> Amara's Law. He never gets enough credit. >> (laughs) >> I say it in every interview right. We overestimate in the short term and we underestimate in the long term the effects of these technologies cause we get involved-- The Gartner store. It's the hype cycle. >> Yeah, Yeah >> But I really I think Amara nailed it and over time, really significant changes start to take place. >> Indeed and we're seeing them now. >> Alright well Gaurav, great to get an update from you and a beautiful facility here. Thanks for having us on. >> Thank you, thank you. A pleasure to be here. Great to see you as well. >> Alright He's Gaurav, I'm Jeff. And you're watching theCUBE from SnapLogic's headquarters Thanks for watching. (techno music)