 It's my pleasure to be one of the hosts of theCUBE on cloud and the startup showcase brought to you by AWS. This is Dave Vellante and for years theCUBE has been following the trail of data. And with the relentless march of data growth, this idea of a single version of the truth has become more and more elusive. Moreover, data has become the lifeblood of a digital business. And if there's one thing that we've learned throughout the pandemic, if you're not digital, you're in trouble. So we've seen firsthand the critical importance of reliable and trusted data. And with me to talk about his company and the trends in the market is Manish Sood who's the CTO and co-founder of RELTO. Manish, welcome to the program. Thank you, Dave. It's a pleasure to be here. Okay, let's start with, let's go back to you and your co-founders when you started RELTO. It was back in the early days of the big data movement. Cloud was kind of just starting to take off. But what problems did you see then? And what are enterprises struggling with today, especially with data as a source of digital innovation? Dave, if you look at the changes that have taken place in the landscape over the course of the last 10 years, when we started RELTO in 2011, there were a few secular trends that were coming to life. One was cloud compute type of capabilities being provided by vendors like AWS. It was starting to pick up steam where making compute capabilities available at scale to solve large data problems was becoming real and possible. The second thing that we saw was this big trend of, you can not have a wall-to-wall one single application that solves your entire business problem. Those visions have come and gone. And we are seeing more of the best of breed application type of a landscape where even if you look within a specific function, let's say sales or marketing, you have more than a dozen applications that any company is using today. And that trend was starting to emerge where we knew very well that the number of systems that we would have to work with would continue to increase. And that created a problem of where would you get the single source of truth or the single best version of a customer, a supplier, a product that you're trying to sell, those types of critical pieces of information that are core to any business that's out there today. And that created the opportunity for us at RELTO to think about the problem at scale for every company out there, every business who needed this kind of a capability and for us to provide this capability in the cloud as a software, as a service offering. So that's where the foundation of RELTO started and the core problem that we wanted to solve was to bridge the gap with that was created by all these data silos and create a unified view of the core critical information that these companies run on. I mean, the cloud is this giant hyper-distributed system. Data by its very nature is distributed. It's interesting what you were sort of implying about the days of the monolithic app are gone. My business partner years ago, John Furrier on theCUBE, said data is going to become the new development kit. And we've certainly seen that with the pandemic. But tell us more about RELTO and how you help customers deal with that notion of data silo, data silos, data fragmentation. How do you solve that problem? So data fragmentation is what exists today. And with the RELTO software as a service offering that we provide, we allow customers to stitch together and unify the data coming from these different fragmented siloed applications or data sources that they have within their enterprise. At the same time, there's a lot of dependence on the third-party data. When you think about different problems that you're trying to solve, you have for B2B type of information that in Bradstreet type of data providers in Life Sciences you have IQVIA type of data providers. As you look at other verticals, there is a specialized third-party data provider for any and every kind of information that most of the enterprise businesses want to combine with their in-house data or first-party data to get the best view of who they're dealing with, who are they working with, who are the customers that they're serving and use that information also as a starting point for the digital transformation that they want to get to. And that's where Reltio fits in as the only platform that can help stitch together this kind of information and create a 360-degree view that spans all the data silos and provides that for real-time use, for DI and analytics to benefit from, for data science to benefit from, and then this emerging notion of data in itself is a key starting point that is used by us in order to make any decisions. Just like if they wanted to look at information about you, I would go to places like LinkedIn, look up the information, and then arm my next set of decisions with that information. If somebody wanted to look up information on Reltio, they would go to, let's say, Crunchbase as an example and look up who are the investors, how much money have we raised, all those details that are available. It's not a CRM system by itself, but it is an information application that can aid and assist in the decision-making process as a starting point. And that user experience on top of the data becomes an important vehicle for us to provide as a part of the Reltio platform capabilities. Awesome, thank you. And I want to get into the tech, but before we do, maybe we just cut to the chase and maybe you can talk about some of the examples of Reltio in action, some of the customers that you can talk about, maybe the industries that are really adopting this. What can you tell us there, Manish? We work across a few different verticals, some of the key verticals that we work in are life sciences and travel and hospitality and financial services, insurance, retail as an example. Those are some of the key verticals for us. But to give you some examples of the type of problems that customers are solving with Reltio as the data unification platform, let's take CarMax as an example. CarMax is a customer who's in the business of buying used cars, selling used cars, servicing those used cars. And then, you as a customer don't just transact with them once. You've had a car for three years, you go back and look at what can you trade in that car for. But in order for CarMax to provide a service to you that goes across all the different touch points, whether you are visiting them at their store location, trying to test drive a car or viewing information about the various vehicles on their website or just punching in the registration number of your car just to see what is the appraisal from them in terms of how much will they pay for your car. This requires a lot of data behind the scenes for them to provide a seamless journey across all touch points. And the type of information that they use Reltio for aggregating, unifying, and then making available across all these touch points is all of the information about the customers, all of the information about the household, understanding that they're trying to achieve because life events can be buying signals for consumers like you and I, as well as who was the associate who helped you either in the selling of a car, buying of a car because their business is all about building relationships for the longer term lifetime value that they want to capture. And in that process, making sure that they're providing continuity of relationship, they need to keep track of that data. And then the vehicle itself, the vehicle that you buy or sell, there's a lot of information in order to price it right that needs to be gathered from multiple sources. So the continuum of data all the way from consumer to the vehicle is aggregated from multiple sources, unified inside Reltio, and then made available through APIs or through other methods and means to the various applications can be either built on top of that information or can consume that information in order to better aid and assist the processes, business processes that those applications have to run end to end. Wow, sounds like we've come a long, good good, sorry. I was just going to say, that's one example and across other verticals that are other similar examples of how companies are leveraging Reltio. Yeah, so I was just saying we've come a long way from simple linear clickstream analysis of a website. I mean, you talk about really rich information and happy to dig into some other examples, but I wonder, how does it work? I mean, what's the magic behind it? What's the tech look like? I mean, obviously you're leveraging AWS, maybe you could talk about how so and maybe some of the services there and some of your unique IP. Yeah, so the unique opportunity for us when we started in 2011 was really to leverage the power of the cloud. We started building out this capability on top of AWS back in 2011. And if you think about the problem itself, the problem has been around as long as you have had more than one system to run your business. But the magnitude of the problem has expanded several fold. For example, I have been in this area was responsible for creating some of the previous generation capabilities. And most of the friction in those previous generation, MDM or master data management type of solutions as the technical term that is used to refer to this area was that those systems could not be paced with the increasing number of sources or the depth and breadth of the information that customers want to capture, whether it is about a patient or a product or let's say a supplier that you're working with. There is always additional information that you can capture and use to better inform the decisions for the next engagement. And that kind of model where the number of sources were always going to increase, the depth and breadth of information was always going to increase. The previous generation systems were not geared to handle that. So we decided that not only would we use ad scale compute capabilities in the cloud with the products like AWS as the backbone, but also solve some of the core problems around how more sources of information can be unified at scale. And then the last mile, which is the ability to consume such rich information. Just locking it in a data warehouse has been sort of the problem in the past. And you talked about the click stream analysis. Analytics has a place, but most of the analytics is a rear view mirror picture of the work that you have to do. Versus everybody that we talked to as a potential customer wanted to solve the problem of what can we do at the point of engagement? How can we influence decisions? So I'll give you an example. I think everybody's familiar with quick and loans as the mortgage lender. And in the mortgage lending business, quick and loans is the customer who's using Reltio as the customer data unification platform behind the scenes. But every interaction that takes place, their goal is that they have a very narrow time window, anywhere from 10 minutes to about an hour where if somebody expresses an interest in refinancing or getting the mortgage, they have to close that business within that heart window. The conversion ratios are exponentially better in that heart window versus waiting for 48 hours to come back with the answer of what will you be able to refinance your mortgage at? And they've been able to use this notion of real time data where as soon as you come in through the website or if you come in through the Rocket Mortgage app or you're talking to a broker by calling the 1-800 number, they're able to triangulate that it's the same person coming from any of these different channels and respond to that person with an offer ASAP so that there is no opportunity for the competition to get in and present you with a better offer. So those are the types of things where the time to conversion or the time to action is being looked at and everybody's trying to shrink that time down. That ability to respond in real time with the capabilities was sort of the last mile missing out of this equation which didn't exist with previous generation capabilities and now customers are able to benefit from that. That is an awesome example. I know at first hand, I'm a customer, quick in and rocket and when you experience that environment it's totally different than anything you've ever seen before. So it's helpful to hear you explain like, what's behind that? Because it's truly disruptive and I'll tell you the other thing that sort of triggered a thought was that we use the word real time a lot and we tried to, years ago we said what does real time really mean? And the answer we landed on was before you lose the customer and that's kind of what you just described and that is what gives as an example, quick and a real advantage again of having experienced it first hand. It's pretty tremendous. So that's a nice reference. So and the other thing that struck me is that I wanted to ask you how it's different from sort of legacy master data management solutions and you sort of described that they've seems to me they got to take their traditional on-prem stack, rip it out, stick it in the clouds. Okay, we got our stack in the cloud now. Your technical approach is dramatically different. You had the advantage of having a clean sheet of paper, right? I mean, from a CTO's perspective, what's your take there? Yeah, the clean sheet of paper is the luxury that we have. Having seen this movie before having looked at solving this problem with previous generation technologies it was really the opportunity to start with a clean sheet of paper and define a cloud native architecture for solving the problem at scale. So just to give you an example, across all of our customers, we are today managing about 6.5 billion consolidated profiles of people, organizations, product, locations, assets, those kinds of details. And these are the types of crown jewels of the business that every business runs on. For example, if you wanted to, let's say you're a large company like Ford and you wanted to figure out how much business are you doing with another large company because the other large company could be a global organization, could be spread across multiple geographies, could have multiple subsidiaries associated with it. It's been a very difficult answer to understand what is the total book of business that they have with that other big customer. And being able to have the right unified, relevant, rich, clean information as the starting point that gives you visibility to that data and then allows you to run precise analytics on top of that data or drive any kind of conclusions out of the data science type of algorithms or MLAI algorithms that you're trying to run, you have to have that foundation of clean data to work with in order to get to those answers. Nice. And then I had questions on just the models. It's a SAS model, I presume. How is it priced? Do you have a freemium? How do I get started? Maybe you could give us some color on that. Yeah, we are a SAS provider. We do everything in the cloud, offer it as a SAS offering for customers to leverage and benefit from. Our pricing is based on the volume of consolidated profiles and I use the word profiles because this is not the traditional data model where you have rows, columns, foreign keys. This is profile of a customer regardless of attribution or any other details that you want to capture. And that just as an example is what we consider as a profile. So number of consolidated profiles under management is the key vector of pricing. Customers can start small and they can grow from there. We have customers who manage anywhere from a few hundred thousand profiles off these different types of data domains, customer, patient, provider, product, asset, those types of details, but then they grow and some of the customers, HP Inc as a customer, is managing close to 1.5 billion profiles of B2B businesses at a global scale of B2C consumers at global scale. And they continue to expand that footprint as they look at other opportunities to use the single source of truth capabilities provided by RLTO. And your relationship with AWS, you're obviously building on top of AWS, you're taking advantage of the cloud native capabilities. Are you in the AWS marketplace? Maybe you could talk about AWS relationship a bit. Yeah, AWS has been a key partner for us since the very beginning. We are now on the marketplace. Customers can start with the free version of the product and start to play with the product, understand it better, and then move into the paid tier as they bring in more data into RLTO. And we also have the partnership with AWS where customers can benefit from the relationship where they're able to use the spend against RLTO to offset the commitment credits that they have for AWS as a cloud provider. So, we are working closely with AWS on key verticals like life sciences, travel and hospitality as a starting point. Nice, love those credits. Company update, headcount, funding, revenue trajectory, what kind of metrics are you comfortable sharing? We are currently at about slightly north of 300 people. Overall at RLTO, we will grow from 300 to about 400 people this year itself. We just put out a press release where we mentioned some of the subscription ARR. We finished last year at about $74 million in ARR. And we are looking at crossing the $100 million ARR threshold later this year. So we are on a great growth trajectory and the business is performing really well. And we are looking at working with more customers and helping them solve this data silo fragmentation of data problem by having them leverage the RLTO capability at scale across their enterprise. Wow, that's some impressive growth. Congratulations. I'm sure adding 100 people, you're hiring all over the place, but where are some of your priorities? So as the business is growing, we are spending equally both on the R&D side of the house investing more there, but at the same time also on our go-to market so that we can extend our reach, make sure that more people know about RLTO and can start leveraging the benefit of the technology that we have built on top of AWS. Yeah, I mean, it sounds like you've obviously nailed product market fit and now you're scaling the go-to market. You moved from CEO into the CTO role. Maybe you could talk about that a little bit. What was prompted that move? Problems of luxury, as I like to call them, once you know that you're on a great growth trajectory and the business is performing well, it's all about figuring out ways of making sure that you can drive harder and faster towards that growth milestones that you want to achieve. And for us, the story is no different. The team has done a wonderful job of making sure that we can build the right platform, work towards this opportunity that we see, which by the way, they've just to share with you. MDM or master data management has always been underestimated as a, yes, there is a problem that needs to be solved, but the market sizing was not as clear, but some of the most recent estimates from analysts like Gartner put sort of the new incarnation of data unification and master data management at about a $30 billion TAM for this market. So with that comes the responsibility that we have to really make sure that we are able to bring this capability to a wider array of customers. And with that, I looked at how could we scale the business faster and have the right team to work, help us maximize the opportunity. And that's why we decided that it was the right point in time for me to bring in somebody who's worked at the stretch of taking a company from just a hundred million dollars in ARR to half a billion dollars in ARR and doing it at a global scale. So Chris Highland has had that experience and having him take on the CEO role really puts us on a tremendous path to tremendous growth and achieving that with the right team. Yeah, and I think, and I appreciate your comments on the TAM, I'd love to look at the TAM and do a lot of TAM analysis. And I think a lot of times when you define the future TAM based on sort of historical categories, you sometimes undercount them, I mean, to me, you guys are in the digital business, business. I mean, the data transformation, the company transformation business, I mean, that could be the order of magnitude even bigger. So I think the future is bright for your company, Reltio Minesh, and thank you so much for coming on the program, really appreciate it. Well, thanks for having me, really enjoyed it. Thank you. Yeah, us too. Okay, thank you for watching. You're watching theCUBE's startup showcase. We'll be right back.