Grid Dynamics Holdings, Inc. (GDYN) Earnings Call Transcript & Summary

Good morning, everyone, and welcome to Grid Dynamics first ever Investor Day at the NASDAQ market site. My name is Anil Doradla, and I'm the Chief Financial Officer of Grid Dynamics. And I wanted to kick off today's event by inviting each one of you. I know many of you have traveled from far off places to come here in person. And many of you have joined us online. To each one of you, we at great dynamics really appreciate it. I know you guys are very busy. You're taking time out of your busy schedules. So we really appreciate you spending the effort in understanding our story. Many of you have interacted with us on investor events or we've interacted after earnings call, but today is different. Over the next 3 to 4 hours, you'll get an opportunity to have a very deep dive into who we are. Why Grid Dynamics is such a strong company from a technology point of view and why we solve some of the most pressing problems? And how are we differentiated from the rest of the industry. You'll also get a sense of our vision, our strategy and our execution. Perhaps most importantly, you'll be able to meet our extended management team who are taking all our visions and strategies and making them into a reality. So before you we leave, what we really hope is you have a very deep understanding of our story. And most importantly, you support us in our long-term journey of becoming a much bigger company and we realizing our GigaCube strategy. So with that, once again, welcome and I'd like to pass it on to Bin Jiang, Head of Investor Relations.

Thank you, Anil, and good morning, everyone. I'm very pleased to see many familiar faces and new faces. We have a very busy day -- busy schedule today. And before I start, I would like to remind you, we have a forward-looking statement for today's presentation. I'm sure nobody want me to read this page word by word. But just for your attention. All these forward-looking statements involve significant risks and uncertainties that could cause the actual results to differ materially from the expected results. Most of these factors are outside Grid Dynamics' control and are difficult to predict. If you're interested to know more about these factors, please visit our Investor Relations website and to understand from our SEC filings. After this event, today's presentation will also be posted on the website. With that being said, I want to have a quick walk-through of today's agenda. Our CEO, Leonard Livschitz, will have a great overview of Grid Dynamics, our long-term strategy, GigaCube, and specifically, our capability and its unique positioning in AI and GenAI. Following Leonard, Rahul Bindlish, we discussed about our sales strategy and growth opportunities in the area of AI. And after that, we are very pleased to hear from our guest speaker, Melissa Pint from Frontier Communications. After Melissa, our CTO, Rajeev, Tech fellow, Eugene Steinberg will give you a interviews -- give you an introduction about our unique DNA in technology and innovation, our core expertise and more importantly, a deep dive in AI and GenAI offerings. We will wrap up the morning session with 30 minutes Q&A, followed by a short break of a lunch. In the afternoon session, Yury Gryzlov will give you -- will discuss our global operation, our GigaCube strategy. Follow that is Vadim Kozyrkov, talking about global delivery and our wonderful engineering team. Our CFO, Anil Doradla, will discuss our financials and the target model. And after that, I will invite all the executive team to the stage to answer your questions. Before I wrap up here, I have two short announcements. First, our wonderful engineers have set up 4 live demos, very interesting and exciting talking about AI offerings for our clients. So please stop by their booth to understand the power of AI. And second, we have a special guest -- special gift for guests today. It's a book over there, a book called Enterprise AI authored by our VP of Engineering, Ilya Katsov. And you'll have a special opportunity to speak with him directly to understand. And believe it or not, I heard one of our C-suite executives of our client, carry this book with him most of the time. Without further ado, I would like to introduce you to Great Dynamics and our people. [Presentation]

Ladies and gentlemen, please welcome our CEO, Leonard Livschitz.

Let's see how technology works. It doesn't. Hello, everybody. A little bit down. My voice is loud anyway. So first event and I thought it would not happen because we had to postpone it three or four times. And finally, we're here. And I'm sure you guys have some level of expectations, what we're going to talk about. And today, really, we try to do something which we haven't done before. We actually have seen -- you will see people who do work. Not just me and Anil, right? And before we get into the -- dive into details, I want to acknowledge the entire team for helping to make it happen. There were countless adjustments and reviews. We tried to figure out what information is public because when anyone talk, we know what to tell you, want not to tell you, but you'll have opportunity to ask people who have not done it before. So we want to make sure you're kind of reasonable. Don't ask him questions which they will gladly answer and then regret. But anyway, it's so nice to have all of you here, and thank you so much. So Great Dynamics. Most of you know the data that was kind of put on a screen to acknowledge the fact we're doing something very special, but there's nothing very special this year, right? So when you grow that much, year-over-year, it means the previous year we grew a lot. But it's not the first time we're resilient. So we get back on the way horse and drive the business because we have [indiscernible] capital, locations, trainings, et cetera. Why we're a trusted partner. It's kind of a used term. People use the word strategy, partnerships, trust. For us, it means a repeat business. when we go with the clients and we deliver something which clients appreciate or, in many cases, don't even think about when they start. That means that we go on and on with making their business success. Their ROI is what we strive for. And of course, the trust means that the people who get on the projects, standard projects and continue to build relationships. The technology DNA. You will see a lot of words associated with the AI because somebody told me every time we say AI, $0.02 per share will go up. So I could just stay and say AI, guys, keep buying. But the reality is more than words, and we will give you through the depth of what the technology work we have done. And again, most of you guys here and a lot of guys online, they know us well. So you know our core, but we'll give you more examples because the guys who sit in the back of the this wonderful exhibit, actually we've done some work. So I will acknowledge them later when they come. But again, we fundamentally, as a core of the company are not just computer engineers, we're mathematicians that makes a big difference. Diversity of the pool -- well, 18 countries is already too many for a size of our company. So we definitely touch on multiple universities across the globe. And in terms of the balance sheet, you know me. We started with a very humble roots as a company, and we stay that way. So we are growing, but we're still a small company mentality, which means we care about money as much as we care about our own assets. The client retention. I mean, for some client companies, 2007 doesn't mean too far out. Well, it's 16 years, right? But it's one year after we started. So if you think about it, going through the journey with our relationship for good, it takes a lot of effort and goodwill on both sides. Now there's a little bit propaganda. So top largest companies. Well, the top largest companies today were not the top largest companies when we started working with them. This is very important, and this is a lot of investment comes from the Dynamic side. It's built a relationship with the technology companies with a great vision, great potential and stay along with as they grow. Some of them have infamous S curve, right? So they grow and then things change. and that happens with some clients. But we continue that relationship expecting that by building a relationship with the technology companies, we can greatly contribute to our enterprise clients because that's what drives that interest. Same goes with the brands. Same goes with the companies. When you're with a big enterprise, many people ask me, is there's a lower-hanging fruit, the midsized companies. Why you're not having a lot of midsized companies. And we do have other clients. But if you go to the top guys and you succeed against Indian big 5s or Accentures of the world, then you know that you're not only creating a bespoke solution, but your scalability will greatly align with the strategy for GigaCube. So it's not an inspiration. It's also positioning our company for growth. So as we announced about a year ago with our GigaCube strategy, we have to diversify our verticals. So far, we talk about horizontal scale, many, many times. Well, part of our verticalization diversity was driven by you guys many moons ago. You keep saying you're too concentrated, you're too concentrated. And the [indiscernible] always a moving target, right? So we were concentrated with one client. They were countries with one vertical. We were concrete with the three verticals. Now we'll be concentrated with five verticals and seven to go. But there is something there. And the reason being is we also transformed not only into the bespoke open source product solution and customer engagements with partnerships with technology innovative software company. And that makes a difference because when you go into the general skills to build open source system, there's not much of personalization of the vertical gravity. But if you want to scale deep into the engagement with the clients, you need to understand the package associated with this particular , whether it's insurance manufacturing, of course, with the pharmaceutical life sciences et cetera. So that keeps us also on the toes to invest into the relationship, and Rahul will mention more about how we build our partnerships going forward. So I just said it. I don't know, sometimes we run ahead of my slide. 30x wonderful number. I haven't counted. But I know that there was one of the cheapest investments I had and Rahul is in the room, some there here. It was $8 investment. To become -- invest into partnership. You're asking how. So Rahul and I some years ago met for breakfast. I asked him for this one of those cheap joints. So it was $8 on my side to invest in his breakfast. And on the piece of napkin, we just drew the map which includes hyperscalers and the key software clients. And he said, what am I supposed to do now, I said, go. And over the years, we've built this amazing team of networking and partnerships and client adoption. So you're seeing the ROI on that breakfast is probably the best you can find in the industry. And that's -- we're very proud that continues to grow. If you want to go for lunch with me to that place, I'm happy to. Again, it's very economical. Just kidding. Not in New York. So we're talking about locations. And before the meeting started, I mentioned that we are about to open the third strategic location in India. So we've been to Hyderabad and Chennai now we're going to be also in Bangalore. Our CTO, Rajeev, is going to India tomorrow night, right? So after dancing and drinking and all the parties, him will have with the families, he's actually going to stay there, not by choice, but my request. And he was going to actually kick off that opening office because we're growing very fast, and we need to make sure that we are going to meet our clients. This is probably the most incredible journey from 0, not quite 1,000 yet, but we're getting closer every day because a lot of our clients are distributed through Indian location with our centers as well. So in addition to the U.S. relationship, Eastern European relationship, we are getting more and more involved in India as well. In term of seniority, remember, we used to write somebody who'd been with us for a very long time, 95% of masters degree in hires, right? I don't know. You guys remember who's been with me for a long time and maybe not too many. But that was because it was mostly Russia and Ukraine at that time, right? And if you don't get master degree you're nobody, right? As a matter of fact, you don't get a diploma. So it was very easy to claim. We had 95% because there was no such thing as Bachelors in that time. which today, people think it's a degree, some of us don't. Anyways. And because of that, we are more adaptable to the world, and then we remove that number. So we focus on universities [indiscernible] and internship. So the key is actually not a piece of paper. The key is how much the people are demonstrating, young talent can demonstrate in terms of the positioning themselves to be a technology innovator. And that's really where Great Dynamics is. Now I don't know why they chose me to talk about first about the technology. So I'm not going to talk a lot because otherwise, I still under people who really know what they're talking about. But there are a few things I just want to tell from a business perspective. When people say generally about AI, it's all about one very small thing. The industry allowed models to make mistakes. Because for many, many years, your conversion needs to be perfect. Now with creating the stochastic development and allowing the models -- the self learning capabilities, and variations, obviously, not in the mission-critical solutions. You open up access to lots of extra data. And that's where we're kind of riding the wave as well. But fundamentally, we've been in statistics for a very long time. And the skills were developed, they are tapping on the top of the existing mathematics and statistics which now is [ complemented ] with a variety of models and products in the industry. And of course, our CTO will talk about what accelerators we do today. All right. So this is just an effect that the first large implementation of what today would be called AI systems started for us in 2017. And Eugene was the person who behind the [indiscernible] technology fellow who was in charge of that particular implementation in 2017. And we continue to grow it every year. We just take a quick lever of what we've done. With the large language models and with other features, which now weave into the company or DNA. Again guys, sorry, more propaganda, all right. Numbers. We take a good pride of Grid Dynamics University. This is the program which we invest a lot of time and resources because the programs continue to evolve. Even today, the models which exist will not exist tomorrow. This is still early. So when you build a specific skill into managing and building certain model, especially if they're open source, we know that a lot of free stuff is not supported well. It will be changed in the near future. So we need to also open the door for the newcomers which will learn in parallel, so we can not only adapt to what's available in the market today, which continues to grow in the future. And that's fundamentally what we do to stay at the cutting edge there. And this is -- just if you think about it, we would have been sitting here as one of our very large competitor with 0.5 million people, even then it would be very impressive. But we have less than 4,000 people. And that's really -- that's a belief that's an investment we do into making in Grid Dynamics, a fundamentally very strong company to grow. So this is the trusted curve which I think all of you need to think about. We started with a small innovative projects because everybody asking how much actual revenue you generate with the clients in artificial intelligence business. There were small enhancements. Efficiencies. We're adding the services. Eventually, we're looking through the code changes. We came up with our own metrics and the guys will talk about the success probability of certain features, which will drive the enabling AI automatous at the client demand. And the important thing about this probability is that we're actually -- want to guide consult our clients not only what could be done with their money, but even more important for them, what should not be done with their money. Because a lot of early ventures may create a sour taste if the conversion doesn't happen. So we need to stay always at the top of understanding of capabilities and capacity of various models, whether it's open source or proprietary, we need to stay on the cutting edge of carriers of data. There's a lot of stuff you guys probably. Many of you recommended NVIDIA, right? I mean I'm sure that's easier to pick today. But remember the time when NVIDIA was not as popular, right? And Dell, an integrated chip, Oh my God, if you remember, Sun Microsystems, God bless it all. I mean they always want to integrate data and protocols on the chip. That's the whole thing would the Polaris system. And we're coming -- turning around back, which means that the large massive cloud may not be the best media to generate the traffic because of the costs associated with that. So we're approaching rapidly the edge of the edge computing. And during this age, we will see many more devices which will carry and distribute the data. And that's part of our investment, too. Now we're not talking today about quantum computing yet because we need you to invest into us. We're not -- we don't want you to run away from us. So we're not building our quantum computer yet. But we understand how to manage the edge-based devices. And it's not only Internet of Things, right? So different but the same. I think it's very important. It will be much larger, but we should not be treated and viewed different than we are today in terms of our core DNA. We'll continue to bring the technology excellence and as we grow, which by the way, is not the easy -- is an easy challenge to handle is how to stay relevant as you grow. But that's what we believe our transformation. We even added new terminology. It's artificial intelligent foundation. Digital transformation, everybody coined, I asked a lot of people, what is the thing digital transformation, nobody really knows, but it sounds good. So now it's AI foundation, Leonard Livschitz, actually, Rahul Bindlish. So if you want to use our reference point, maybe you'll give us extra the brownie points. And this is what we are seriously looking in the future. Be AI foundational company with our growth. Without further ado do, Rahul, you can steal the thunder. Now remember, clicking is important. Thank you. Thank you so much.

Thank you, Leonard. Good morning, everyone. Can you hear me? It looks like. Very good to see all of you here and also those online. It's a pleasure to be speaking here. I had strategic sales and partnerships with the company. I've been with the company for more than 9 years. Before that, I was with Infosys for 14 years. And part of their growth from $200 million to more than $8 billion. But what's happening here today in the industry is very, very exciting. According to McKinsey, there is an opportunity out there to create enterprise value somewhere between $3.5 trillion to almost $6 trillion annually. In the next few years, leveraging AI and generative AI. We believe we are in a pull position to really enable that transformation. And why is that? Because from our very inception, we have been hyper-focused on creating business transformation, leveraging leading and emerging technologies. These technologies have changed over time. starting off with cloud, then it was about digital transformation and digital experiences, then came an era of data platforms, real-time analytics than it was about AI and machine learning. And now it's all about generative AI. Across all of that, there are a few key things that we have been hyperfocused on. Number one, drive business transformation. Number two, focus on enterprises. By enterprises, I mean Fortune 1000 companies, mostly around Americas and Europe, we'll expand to others in the future. But even within those enterprises, we focus on the other adopters. Leonard talked about our strategy of how we started working early with many of these technology companies, which actually became leaders in the future, and we do that consciously. While going through this growth, our sales strategies have changed. Of course, every startup starts with founder-led growth and word of mouth. But as we grew, we built up best practices around land and expand, around building a very strong account management organization. Expanding our marketing from initially just being content marketing to really adopting the best practices around digital marketing, conference participations, joint marketing with partners, account-based marketing. So we have a very strong marketing organization today. And over the last 3 years, we have built a very strong partnership network Leonard alluded to that, and I'll talk about that a little bit more later in our presentation. Now as we stand today, we are focused on 4 key things. Number one, building a specialized hunting organization. Number two, verticalization of our sales teams. I talked about business transformation, which means we have to be able to speak the language of the customer, which is typically in specific industries, and we are moving towards verticalization of our teams. At the same time, we also realized there will always be a set of services, which is better sold horizontally. A classic example is user experience design. So we will -- and we are investing in a horizontal organization to focus on horizontal sales or practice sale. And finally, we are creating a team focused on large deals. Both from a people and practice perspective. A few numbers to show that the strategies that I talked about are working. We have 14 customers who have been with us for -- actually 14 enterprise customers who have been with us for more than 5 years. And in fact, many of them have been with us for more than 10 years. Now I know we say we have -- or in our quarterly earnings reports, you will see that we have more than 200 customers overall. A subset of them are enterprise customers, which give us the largest share of our revenues. 70% of revenues come from those Fortune 1000 companies. This 14 is a subset of that. 90% of our sales are repeat sales. What this means is our existing customers come back to us to buy more or extend the services they're buying from us. Land and expand strategies are working for us. We have added 56 new customers in the last 8 quarters. Our sales engine is working. We are very proud of that. But how do we win trust and really win business in the industry? As I said before, we are focused on business transformation, leveraging our capabilities in leading technologies. So a key function of the sales team is to really understand the business objectives of our prospects and customers and link that to our capabilities in leading technologies. And to convince our customers that we do it better and faster than everyone else. And we have 4 key enablers to really drive that. Relationships, domain expertise, technology excellence and partnerships. Let me talk about each of them, starting with relationships. People buy from people. These are not companies buying from companies. Relationships are critical. And we have been very fortunate to have many great relationships. I'll give you anecdote here. This was a few years ago. One of senior executives changes job, joined a Fortune 1000 retailer and brought us in to help them transform their e-commerce and omnichannel commerce ecosystem. And I met him and I thanked him, appreciated his gesture. And he told me, Rahul, please understand, I made it a precondition for me to take up this job. Because why I'm undertaking, I need a trusted partner, and I cannot do this transformation without you. That kind of a trust, that kind of confidence on our capabilities is what we thrive on. And how do we go about doing that? Each of the executives that you see in this room and outside actually take responsibility for nurturing and building relationships with the top executives across our major customers. We have QBRs with them. We understand what their company objectives are, but also what their personal objectives are. It's important for us to make sure these executives are successful in their goals. And based on that take our solutions and offerings to them. But enterprises are complex organizations. There are other leaders in the organization, technology executives and engineering managers and our delivery leaders as well as senior architects in the CTO organization, are responsible for building and nurturing those relationships. We have tools and processes in place, including our CRM to really track that these relationship building activities are happening, and there are alerts in place to make sure we are making progress towards those. So second enabler, I talked about domain expertise. Of course, if we are focused on business transformation, understanding the domain, understanding the industry is critical, but we are focused -- hyper focused, I would say, on a specific type of business transformation. The one that is delivered with high technology innovation. So really in this 2x2, we are focused on the top right box or the top right quadrant. Why? Because the largest enterprise value is created in that quadrant. Also, the most complex problems in the industry are in that quadrant, and that's the mix that we thrive on solving complex business problems and driving business transformation using technology innovation. And I looked at business benefits in 2 key categories. There are gain creators that impact your top line revenue generators. And there are pain relievers, which are our efficiency plays and cost place, right, cost reductions. Historically, we have been very focused on gain creators. Even for cloud transformations, while many of the companies have been going after cost savings, we were really after driving transformation to drive revenues. And as an example, for a large automobile manufacturer, we created their new cloud platform for e-commerce, both to drive their B2B sales which is mainly for ICE vehicles through their dealers or B2C sales, the EVs, which is direct to consumer, right? So cloud platform still driving your top line growth. But an interesting change is happening. AI and generative AI is creating opportunities for us to really drive pain relievers are efficiencies and cost reductions. A few examples of things that we have executed, driving inventory optimization. Leveraging AI, workforce scheduling, leveraging AI or look at driving efficiencies in contact centers using generative AI. So what I'm seeing here is the market for us is certainly expanding. There is a huge opportunity for us, and we are prepared to really tap into that opportunity. Driven through AI and GenAI transformation that will happen over the next few years. Quick recap. I'm going through the four enablers of sales. I've covered the first two. I'll go to the third one now which is about technology excellence. Technology excellence is what drives differentiation for us in the marketplace. This is where we are better than everyone else. And if you look at our technology offerings, they really fall into four key categories. Your customer experiences and digital commerce, cloud transformations and application modernization, data engineering and data platforms and advanced analytics. In the past, AI and generative AI was part of the bottom right box, advanced analytics. Over the last couple of years, really AI and generative AI has been infused into all our service offerings. And going forward, I see that being a core part of everything that we talk about. But how do our sales team use that to create differentiation? And I'll give you another story here. This is how we acquired one of our largest technology customers. A few years ago, we had release a technology blueprint for in-stream. And as part of that, we had also run campaigns, digital campaigns. even we invested in SEO. And our CTO participated as a speaker in one of the data analytics conference in Silicon Valley. Some other technology executives from this company actually approached us after the conference and said, "hey, guys, what you talked about is exactly what we want to do. Because we want to leverage that kind of an architecture to drive real-time analytics on signals that we are getting from our phone apps across the world." Long story short, we got into a POC engagement with them for 3 months. Subsequently, they really replaced their largest SI on that specific program with us, and that was a start of a multiyear journey where they are today, one of our largest customers. So really, sales team leverages the artifacts created by our CTO organization, the technology blueprints, the white papers, the e-books and the marketing campaigns we do around them to create that differentiation and leverage our most senior architects to run discovery programs for customers to get into transformative engagements. And then let me talk a little bit about partnerships. They have become very, very important for us in the last 3 years, and we look at our partnerships. In two major categories. You have the hyperscalers, the Amazon, Google and Microsoft. And then we have a set of SaaS providers, which are really focused on specific domain solutions, digital commerce, supply chain, data analytics. Over the last few months, we have been able to extend our partnership with hyperscalers across all their AI and Generative AI offerings. As an example, we were the launch partner for Google for the generative AI offering. Now how do we leverage these partnerships? Three key ways. Number one, it gives us early access to their technologies. So we are able to build solutions and accelerators and launch it on their marketplaces, giving us our solutions better visibility. We work together on marketing programs with them, be it conference participation, digital marketing and so on. We're also able to leverage marketing development funds from hyperscalers to extend our marketing dollars. And finally, on the sales side, we've worked very collaboratively with their sales teams to extend the reach of our sales teams. Sometimes, we bring them to opportunities and deals. Other times, they bring us to their opportunities and deals where they want to accelerate their sales cycles. Many times, they make funds available to us that we could use to subsidize our services because they want to accelerate movement of workloads to their platforms. All of that effectively results in greater pipeline for us accelerated deal closures and larger deals. Many times, it also results in -- or helps with new industry penetrations. And we have been very successful over the last 3 years. During that period, our partner influence revenues has gone from less than 1% to more than 12%. Of course, the number of partnerships has also increased significantly from close to 4 to more than a dozen. I expect the number of partners to continue increasing as we start to focus on specific industry partnerships as well. And I also expect the partner influence revenues to go even higher than 12% in the coming years. So let me take a pause here. and play a video for you to hear from one of our partners, Fluent Commerce, which is in a very interesting space. They are one of the leaders in auto management, which really plays at the intersection of digital commerce and supply chain. The person speaking is the CEO of Fluent Commerce, Graham Jackson. He's part of the Advisory Board of MACH Alliance as well. So here you go. [Presentation]

Hi. My name is Graham Jackson, and I'm the CEO at Fluent Commerce. We offer world-leading inventory data and order management solutions to retail and wholesale organizations worldwide and Grid Dynamics plays a vital part in our global growth. So Fluent order management offers real-time inventory visibility across all sales channels and then it enables merchants to fulfill orders in the most profitable way to the business and in the most convenient way to the end customer consumer. It's built on a cloud-native API-first, micro services architecture, and that caters to really complex requirements. We have a prestigious industry leaders for using Fluent order management to turn what is the complexity of multi-region, multibrand, multi sales, channel multi-location environments into a serious competitive advantage. Grid Dynamics are an extremely trusted partner of us here at Fluent. And that's due to three main things. First, exceptional engineering talent. They've always really focused on collaboration and -- and we have done joint product development and innovation, which has been very successful. Second, they have program reliability in project delivery. Obviously, that's extremely important to us. And thirdly, business case preparations and implementations, which, in our case, means building capabilities that use our API first architecture. But also extending Fluent and adding other components of the ecosystem that provide a wider set of commerce capabilities. Our customer base trusts us to recommend partners that we know will be just as passionate about a successful outcome as we are, and is competent. I have no hesitation in recommending Grid to our customers back on their experience, technical know-how and drive to achieve our joint goals. We have big plans. And big plans can only be achieved with excellent partners who support us all the way. And there's a few things on our road map specifically for our partnership with Grid Dynamics in the coming months. Firstly, we're growing our footprint into our newer sectors, such as supply chain and manufacturing. Second, geographic expansion into DACH in Central Europe. Third, a collaborative innovation with third parties such as Google and Relex in Europe. And last but not least, an ongoing joint development of Fluent's AI capabilities, making full use of our AI rocket fuel, that's clean, organized, accessible and real-time data.

Thank you, Graham. Later, during the day, you'll also hear from one of our hyperscalers. So let me change from talking about strategy to execution. How do we execute these strategies. We really look at our portfolio of accounts into three key categories. The top is a key accounts, which are our largest accounts. These are our most deep relationships. We understand the business plans, the budgets and the goals of these organizations, and we take customized solutions and customized offerings that will enable their business objectives and goals. We have dedicated account teams and both from a leadership and operations perspective for these customers. We have delivered many times multiple transformation initiatives for them. Majority of them have been our customers for a very, very long time. The second category is then your core accounts, which is the next set of accounts. That's where we take our industry knowledge and our industry solutions, leveraging our industry SMEs to them. We also leverage techniques like account-based marketing to extend the reach of our sales teams. All of this to drive their innovation agenda. And finally, the last category, the seeding and nurturing accounts is where we drive efficiencies of the sales and account organizations. We use best practices like BDR campaigns, marketing teams to really take our offerings to them by driving efficiencies within the sales process. And earlier, Leonard had talked about many of the GenAI accelerators and co-innovation discussions we are having. Majority of those discussions happen with our key accounts and core accounts. New accounts always start as core accounts over a period of time. Some of them will move up to being key accounts. That's what we drive the entire sales organization towards. It's -- proof of the pudding is in the eating. So I talked about business transformations. Here are a few examples of transformation that we have delivered over the recent years. I'm not going to walk through each of them. But there are some common themes. You will see that each of them is about AI. Each of them or another leading technology. Each of them is about business transformation. Each of them is with a large enterprise. Let me talk about one of them, which is very interesting. And that is unique because not very often you come across a scenario where you're able to impact both your top line and the bottom line. That is an example, which is -- your second on the right-hand side, right? Am I right? Yes -- it's a large beverage manufacturer, global presence, we drove a 3% increase in sales in one market. At the same time, 22% improve in efficiency of their merchandising team. By implementing a solution that their sales team could use to take a picture of the shelf of retailers in developing countries. Think about Latin America, Africa, Asia and so on. Where merchandisers did not have visibility to inventory on shelf of the retailers. But by taking this picture, our developed software was able to really determine the inventory on shelf of these retailers using [indiscernible] and AI. And the merchandisers were then able to make intelligent merchandising decisions, which drove higher sales as well as improvement in their efficiencies. Great example, but that's what we strive towards. Drive business benefits, leveraging our technology competence. And guess what, when we do that, those customers come back to us again and again. Here are examples of a few quotes that I pull together that our customer leaders have made about us. Again, I'm not going to read each of them. There is a common theme across all of them. It's about innovation. It's about business benefits. It's about customer satisfaction. Customer satisfaction and innovation and focus on these things will drive our growth in the future. So thank you for listening to me. I'll end my presentation here. But instead of me talking about what our customers say I would like to welcome Melissa Pint on stage. Melissa has been our key customer since 2016 across multination, she has -- she is a key leader in the industry with more than 25 years of experience across many, many Fortune 500 companies, including Cargill, Target, JCPenney, and now see the Chief Digital Information Officer at Frontier Communications. Very interestingly, she spent 2 years in Bangalore, living and working towards building a development center for one of the companies she worked for. She has been very gracious to come all the way from Dallas to talk about her experiences of working with us, Melissa.

Appreciate it. Yes. No, I don't have any slides, don't worry. I will just share my experience working with Grid. So first of all, thank you. Thank you, Grid, for inviting me here today. I am happy to be here. I do consider good dynamics to be a partner. And I'll tell you a little bit about how that happened. So as Rahul was mentioning my background is largely in retail IT. I've been at Target and then at JCPenney, starting in our Bangalore office over there in Target, as he mentioned. So I know Target very well. I know engineering and development talent very, very well and our global talent very well. I sure you can imagine Target, a huge user of a lot of different labor companies, JCPenney, same thing. And I'll talk about my journey into Frontier and why Grid has been part of our transformation at Frontier. So on the retail side, digital, of course, is the name of the game. No surprise. The bar is very high for digital solutions in retail that is because Amazon sets the bar. We're all familiar with that. And so retailers are expected to have phenomenal digital experiences. No exception at Target and at JCPenney. Grid was a key partner of mine at JCPenney a completely customized solution, both web and app and was a key part of building that solution. to attract, obviously, and retain customers and drive sales. I moved over from retail, where I've been for about 20 years or so into the telco tech industry. So Frontier communications, we are a fiber Internet provider. We're the largest pure-play fiber provider in the U.S. Why did I go there? Why did they want me? They wanted me to come over there to bring some of that -- the digital experience from retail into the telco space in our provider space. We compete with cable companies. I think we can all agree, cable companies' digital services for their customers, not super awesome. Certainly, a lot of telcos, also not super awesome, self-serve solutions digitally. And so that is my job to create great solutions for our customers where they can self-serve. They have great tools. and they can use our tools to help them troubleshoot, upgrade, whatever they need to do with our service offerings. But we're starting from almost nothing in that industry. We had almost no digital presence as a team. We had almost all digital experience as a team. So when I came in just a little over 2 years ago, that is my mandate. We have to build a great digital solution. So one of the first things I did with my management team, my leadership team is start to build our team, and we brought in two partners that we've worked with. One of them, Grid Dynamics to help us build out our digital experience and transform Frontier to a legacy telco into a digital player. And Grid is one of those. Why do we bring in Grid? Why were they trusted? How did they gain our trust when we could have picked a lot of different providers. All of the [ partners ] we use are global. That's a given in today's world. I'm not going to use anybody that doesn't have a global presence. Why? I need a little bit of price arbitrage, but really what I need more than anything is 24/7, right? I need the level of velocity. I cannot get that if you're only work getting my day time. So global is a must, which means though I do need high-quality engineers across the world in all those different geographies. And that is where our Grid has really differentiated in my experience. is that they are able to attract that, retain really high-quality engineers. And that is super important because I need to move very, very quickly. I'm in an industry that's behind in digital, not a company that emerged from bankruptcy. So we have not had a very strong technology in the past. And so we had a lot of ground to make up. We need to move very, very quickly. And this is also a company that had not had a lot of experience working with third-party vendors and/or global vendors. And so I needed a partner who could come in, hit the ground running and help us accelerate super fast, and they have. We have increased our velocity of output. We have increased the quality of our delivery, and we have increased the innovation and the thinking that they -- just like they're talking about, that they've talked about today. And so 18 months into our digital journey, we've got a great app. Grid is our primary partner on our mobile app. Our ratings have gone from 4.2 in the app store to 4.4, continue to go grow. It's not -- that's not bad. I don't think in just 18 months, I'm pretty much having almost no app to start with a very bad app to start with. They are core to how we are moving forward. Today, you hear a lot about GenAI, which is interesting because that's one of the areas that, of course, every company is into now. It was like a year ago, where we hit the market and all companies now are trying to figure out how to leverage it, we're no exception. And again, we've turned to just a couple of our partners to help us in our GenAI journey. Grid Dynamics is one of them. Again, same reasons because of their innovation, their quality and their ability to deliver. So those are the things that I really count on and trust. So I'm one of the customers that's moved across interest rates across your verticals, but I think it translates because of the deep technology expertise and quality of engineers that Grid Dynamics has allowed them actually to move industries with us. The reasons when the same people actually not work with us in the retail team, we brought them over from the grids team, brought them over to work with us here in this industry, and they're doing a phenomenal job. So to me, that is what a trusted partnership is about. They will also invest with us, help us innovate. And that's also really key because I need a partner who will help me but it can't be always something I start. So Grid is really good. One of the better partners we have actually in helping to innovate with us and invest with us and help us think, help to prove concept with us. to get us moving forward. So that is where we position grid in our labor matrix, so to speak, is a highly trusted partner, help us move quickly, complex digital space and now in the GenAI space. And I am -- we plan to continue to work with them. And I have no doubt that should I change industries, which I'm not going to do any time soon. But should I, I'd bring them with me. So I just want to thank them for inviting me here today to share our experience or my experience with Grid Dynamics. Thank you.

Good morning, everyone. My name is Rajeev Sharma. I'm the CTO of Grid Dynamics. I've been with Grid for about 2.5 years now. By training, I'm an aerospace engineer. A rocket propulsion engineer to be more precise. And I've spent many years in the Indian Army, a former Colonel. For the last more than 30 years, I've had many diverse careers in engineering and technology on the CV Street or the civilian street. And my specialties are generally in the areas of enterprise architecture, product architecture, systems design, mathematical modeling, machine learning, deep learning, and at some part of my career, I also ran a startup from 2018 to 2020 when deep learning was still catching on. I led a start up as a CEO for a deep learning company. So that in a nutshell is my background. Let me start this discussion with a small story. A tale of two companies, if you will. One is, of course, Grid Dynamics. The story starts in 2008 when Grid Dynamics was still in its evolutionary journey. We were founded in 2006. The other is one of our customers who's an iconic retailer, big brand, 150 years old history. And this journey of taking a customer up the business value and up the digital savviness is deeply entwined the Grid Dynamics evolution as a strong engineering company and technology company. So our customer, in 2008, when the whole world was reeling under the financial crisis, our customer was actually grappling with the onslaught of online retailers, right? And their e-commerce platform was not really geared for that online presence, and they were losing many -- a lot of sales dollars, revenues on that. So we started a journey to help them establish their online presence. We built a scalable platform for them. We packed many features like superfast catalog, faceted navigation. And we help them improve on their conversion, whatever conversion levels they were there, improve on those by -- at least by 30% overnight. And then we took them through the Black Friday that year without a sweat. This kind of cemented that trust and relationship. The next phase was the iPhone mobile era. By now, our customer had grown in its engineering strength with thousands of developers. When they were here, they were starting as a small team. But now they had already grown with thousands of developers and they were trying to work in parallel and then go to market quickly with new product offerings. Now such flexibility and speed requires the power of cloud. We helped them build -- break that monolith platform that they had. Took them through the micro services journey and helped them scale online in an omni-channel manner to meet their customers in the era of mobile commerce. And around that time, we also wrote a book by the previous CTO, Max Martynov, along with one of my cloud practice colleagues, Kirill Evstigneev. And this captured the experiences on taking a company to a micro services journey through a continuous integration, continuous delivery mode of operation. The next era -- the next phase was one of social media and influencer-based marketing, now this was a time when you had to redefine customer experiences. And how do you engage with the customer in a manner that is seamless for them. So we took this customer on a journey. We built search engines and recommendation engines powered by advanced natural language processing capabilities, NLP. Now you will -- you've been hearing GenAI again and again, but we started NLP 8 years ago. And at that time, it was BERT transformer-based model. And then, of course, it went into GPT-3, then GPT-3.5 and now GPT-4,and I'm sure it will continue. So we've helped them build this foundation and actually, again, helped them lift their conversion by another 20% over 30%. And the same thing we captured in a book called Algorithmic Marketing. Again written by Ilya, who's my colleague in my CTO team. Today, we are helping this customer travels this complicated ecosystem of GenAI, Enterprise AI. And we're trying to help them build these new customer experiences like through conversational shopping, virtual try on, all powered by large language models. And we -- of course, we have written a book that we will be carrying with you today, titled Enterprise AI and Ilya, I think, has signed that book. Now why would we do this? Because clearly phase to help our customers, Grid Dynamics had to be ahead of this on the leading edge of each wave. So we could do this because of a deep DNA of engineering and technology and rigor, and I'll come to it in a minute. And that allowed us to punch above our weight as we were growing as a technology and engineering company and publish along the way. Writing is a very powerful form of sharing your world view and point of view with the world and the market. And I think this helped us in a big way. The CTO office has three pillars on which we operate. The first one is our R&D and innovation are moat. This is with our customers in the center. The second is keeping the customer-first mindset, which means thinking about our customers' customer and trying to map what business solutions or technology solutions would work best for them. and then mapping it to our innovation and service offerings. And last but not the least, how to take these processes and hand it over to the implementation team in a very seamless and a scalable manner through blueprints and framework. And the way we are able to do this, the CTO team, the CTO office is an eclectic mix of architects and engineers of with covering 40 disciplines for key engineering disciplines and even liberal disciplines. And this gives us -- and I think 2/3 of our team is -- they have advanced degrees and including Ph.Ds, Dr. Steinberg is here. And that allows us to actually address some of the most complex problems because if this team gets together, and applies this problem-solving lens to any problem in software development, mathematics, machine learning, what have you. This team has the firepower to solve those problems with our customers. And this gives us the trust that we win from our customers and the right to play and the right to win. Now the CTO office is the propulsive force and the glue in Grid Dynamics. We integrate this 3-in-a-box kind of an approach, bringing sales, marketing, delivery together with a customer in the center. For the sales engine, we bring our explore and experiment phases of interaction and try to take this discussion with a customer in a direction that allows our customers to see our value faster through our demos, our solution accelerators, our white papers and our blogs. And the whole idea is around how do you generate this confidence to shorten the sales cycle for the sales team. For the marketing team, we make sure that we are ready with the right papers -- white papers, blogs and thought leadership through our speaking at different conferences and through our interactions with the analysts so that we put our best foot forward and convey the right message in our go-to-market approach. And last but not the least, all this has no meaning. If in the end, we cannot transfer this to our implementation team. Grid Dynamics essentially is not the CTO office with 50 architects. It is the engineering powerhouse with 2,900 or 3,200 engineers behind the scene that actually worked the miracle. We only as a first step forward, make that miracle possible. And with all the support that we give, what it translates to is, for our customers, a very rapid time to value, time to market. A much more seamless experience on how to work with Grid Dynamics. The CTO office is the first beachhead you encounter. Pardon my -- some liberal use of some military terms, beachhead is not a civilian term, but I think everybody uses it. So beachhead is the word. So we are the first group of people the customers see along with the sales folks and our account management team. So we create the building of trust and the ability to work seamlessly with a customer. And last but not the least, this strengthens our brand equity in the market. Now there are leaders here. There are analysts here, there are investors. The pressures and the sea-saw effect between the business and technology is nothing new. It has been there for decades, and it will be there forever. The businesses always will have the cyclical nature of the world, the geopolitics and the complexity of the market, the demands of the customer. And the technology will always be grappling some legacy they want to get rid of. The budgets are limited. They want to have a nimble technology base so that they can address changing business dynamics. And of course, there is always the need for a scalable, flexible infrastructure. There is a need to break the data silos and so on and so forth. This is not going anywhere. But the era of enterprise and GenAI has changed the kind of the dynamics and there are now additional priorities that both business and technology now have. For the business, it's about -- how do you infuse enterprise AI and GA in the business value stream to make sense into the business and to make sense to their customers. For the technology team, it's all about understanding the inner nitty-gritties of these technology stacks on emerging tech and then making sure that how does this all add value to the business. Technology for technology's sake is meaningless unless it can impact the quality of human life. And that is the point where the technology team always have to follow the business. Form follows function. Now it is very important, and this has been our work in the last 6, 7 months. It's been very confusing. Just to give you a sense I think Chat -- OpenAI launched ChatGPT somewhere around end of November last year. By January, they had 100 million users. And this November, nearly about a year now, they have opened ChatGPT stores. So the rate of change of these large language model powered, foundation model powered ChatGPT, GenAI tsunami, has created too many confusing images with our business partners, with our clients. So step 1 to clear the cloud, to clear this fussiness. Enterprise AI, which is now -- Grid Dynamics has been at it for nearly 7.5, 8 years now. As I showed you in that example, where we were building NLP, advanced natural language processes based techniques for one of our customers. So the machine learning that we all started in engineering schools, the regression models. Those are our statistical models, the machine learning. That is decades old. Some of the technology, some of the methods like gradient descent and loss minimization were built in 1958. So the mathematics is not new. The deep learning happened thanks to Google who open sourced TensorFlow somewhere around December of 2015. So that is when deep learning became some kind of a -- every high school student had access to the open source TensorFlow, right? And that is when deep learning kind of became mainstream and now it is part of enterprise business value chain through neural networks or computer vision and so on. Of course, Grid has built next best action for our customers. We have written blogs on it and computer vision drives the visual search today, and you may have seen some demos there. My colleagues tasks out there to show you the demos. This is enterprise AI. Decades old. What has happened today is that with the advent of large language models, the foundation models powered by deep learning under the hood. It is still deep learning. But the way it's been trained on such a large corpus of data. And just to give you a sense, in 2019, my startup had trained using BERT at that time. trained a machine learning model to learn military law. This was 2019. And in about 4.5 months, I had a fully trained JAG assisted on our hands, right? And around 2019, we had trained an AI engine to decipher thoracic chest disease X-rays with 120,000 open source chest x-rays. So now the GenAI, what has happened is, as one of our Board members kind of remarked that the whole world learned about GenAI through a simple chat interface, through a simple UI. That's how the whole world learned about ChatGPT. So today, with normal text, we can manipulate images, videos, you can have conversations with them and you can even have them as a payer programmer. But this is not the whole story. Now the ecosystem is growing. There is money to be made, right? The market moves to close the arbitrage, MBA101 semester first, right? Every market will close the arbitrage. The moment -- even if you're an early mover, right? And that is where today, you have Chat GPT-4 from OpenAI, you have Anthrophic Cloud from Anthropic. And then, of course, there are open source model. You have Bard from Google. And then you have OpenAI giving you Chat GPT-4 and then you have open source models like Llama from Meta and not -- it doesn't stop there. Now the hyperscaler said, you know what, you can access these through our APIs. If you are a partner on our cloud, just use our APIs. They don't tell you these APIs cost a bum, right? Bum is a bad word these days, but they're very expensive right? Now what it means is -- it means that the complexity today in business and technology is not going away, which is where a partner like Grid Dynamics is central with most of our customers. We are helping them understand this landscape. This was just to clear the air on enterprise AI, GenAI and what the ecosystem is all about and where there is a problem. Should you work with hyperscalers, should you work directly with open AI and have a managed services account, these are all important discussions when you're taking this for your business. Now with this part of the discussion, having told you a lot about GenAI, Enterprise AI. My esteemed colleague, Dr. Eugene Steinberg, who has been working for about 6, 7 months in the GenAI space and much earlier deep learning space, we talk about some of our GenAI service offerings and our use case as well. Dr. Eugene Steinberg.

Thank you very much, and good morning, ladies and gentlemen. I'm very pleased to be here. And quite honestly, for me, it's a very, very personal event. Why is that? Because I'm the first employee of Grid Dynamics. And it's a big, big milestone for my very long journey with the company. So I witnessed this company to grow from a very tiny startup on the kitchen somewhere in San Ramon, to the boutique consulting company to the midsized professional service company and now to the public company public technology company I represent today. And during this growth, we grew, we transformed, we changed industries. We scaled industries, we scaled confidence, scaled countries, technology capabilities, different waves of innovation. But we always try to keep one thing very constant, and we keep our laser focus on one thing, maybe three things like actually. Number 1 is our passion for innovation; number two, our passion for engineering excellence; and number 3 is our relentless focus on customer success. So there are three things which I believe define our engineering culture. And as Rajeev talked about the story of our -- like it was one of our first large kind of serious big enterprise customers. I was there. I was there every step of their journey. And I remember some amazing days in this journey. I remember the day the new superfast catalog and search engine which, by the way, my colleague, Ilya, has helped to write as a junior engineer. Overnight, really kind of changed the business of our customer and deliver 30% uplift in the conversion rates. Or another day when all our data centers, all the servers and all data centers steaming hot on a Black Friday and running like almost like 100% CPU utilization, but still not slipping a single transaction and delivered the first ever $100 million day for a very, very large retailer without breaking a sweat. And I remember that day, when we read the industry first [indiscernible] and visual recommendation solution, which was really astonishing because Google released its usual search model only like few months before that. The kind of very first adopter, and we moved the customer to go there. So with new wave of innovation, which is powered by Generative AI, I believe that we will see more such great days to come. And today, I want to talk about some of the examples. Everybody, of course, as we know, is an AI company right now and everybody is exploring the potential of AI. I want to speak more about very pragmatic things, which we are seeing in engagements with our customers, like what our customers are actually doing instead of like trying to kind of [indiscernible] about like what can be done. So of course, one of the biggest trend right now and new wave is the second coming of Conversational AI. So many of you probably remember the first coming of Conversational AI in 2016. But now -- and it's actually flopped. But now the Conversational AI is coming back. It's coming back as a new UI paradigm. And now it's not just talks back according to the specific rails, which were laid out by developers. Now it understands, now it keeps you context, now it has access to enterprise data. And now it really transforms the way how we do product discovery and e-commerce, how we do customer support, how we do -- access to enterprise knowledge, for example, so this is like one of the zone in which we are actively working, and I will talk about examples later in my talk today. Customer experience. Customer experience is probably the most important things for many, many companies. And Generative AI here actually unlocks not only improves over the existing capabilities, but unlocks completely new capabilities, which we are not possible before. Think about shop-the-look capabilities. Think about virtual try ons, which many companies try to address using all kinds of technologies before, nothing really worked. But now we see an evidence and we work with our customers. And we strongly believe that this is the wave when it will actually start working and will be adopted by a mass market. In process automation, Generative AI helps a lot in taking away the pain of mundane and repeatable tasks. So this is when we are able to perform efficient routing issues or classification of e-mails and reaching right people, understanding what needs to be done in a specific situation with a low-code automation. So this is when the Generative AI drives the employee efficiency and takes away the boring stuff from people and helps them to focus on the more interesting things. In content creation, of course, Generative AI is all about content creation. And we see a lot of engagement with our customers when we help them to develop solutions which, for example, creating marketing narratives or create a very enticing and interesting product descriptions or create an astonish product images out of very boring, like on the white background, like product images, you can put it and be seen, you can make it work, and you can personalize it to specific customer segments. And data engineering. [indiscernible] data engineering is probably something which will benefit the most behind the scenes. Because now Generative AI gives us access to the wealth of the enterprise data which was accumulated, but nobody used it because it was not structured form. We can now understand all this text, communication logs with the customers. Some reports, some data, which is laying around but not used to drive any sides of the business. We can harmonize our data. We can bring order to it. We can slice and dice it and put it to use. And all this, thanks to the power of large language models in really understanding the human language and human testing. And last but not least, for developers like us, Generative AI is a huge force multiplier. So this is when we expect a lot of great things happen in many of the different zones of software development. For example, legacy modernization, understanding all the sub secure kind of languages in which like systems were written in 1980s, nobody remember saying anything about them anymore. Where [ Nursery Home ] or probably somewhere else, but we need to transform understand and reverse engineer and transform in and this is where Generative AI can really help us to do that, as well as modernize systems, as well as bring automated quality assurance easier and faster, basically improving our productivity, allowing us to move faster and do more things in the Generative AI. So let me give you one of the examples about the force multiplication for employees. So business key study of one of very large wealth management company. So this wealth management company is supporting about 9,000 financial advisers, and the digital platform helps them to manage their practices to find opportunities to rebalance customer portfolios to communicate with the customers through the marketing and personal channels with different messages to keep notes about their meetings and action items, everything which financial advisers are doing in their daily jobs. As a result of that and as a big financial company, this firm keeps a huge knowledge base and with knowledge base consists of frequently asked questions, policies, marketing materials, analytic materials. You name it, like financial -- different kind of things which are needed in the daily life of the financial advisers. So the idea is very simple how to give them the access to all this knowledge, how to give financial advisers to access [indiscernible] a seamless and easy-to-use manner. And of course, in a large -- in the last few years, the neuro search capabilities. And likely-wise models really transport away how the companies consolidate, organize and provide access to the enterprise information to a very simple and natural interface of Conversational AI. So we were selected by this customer to run the knowledge AI project to actually connect the financial advisers to all the systems using Conversational AI based on life language models, which will really help them to understand the practices and policies and talk with a system like we are talking with a human expert. Or remind them about a content of the previous meeting with a particular customer and like what is the action items, or access their financial services systems and understand when the portfolio was last rebalanced. But more than that, it's also at also creating personalized messages to help financial advisers to find an opportunity to speak with their customers, right? For example, like somebody wants to congratulate the particular customer with the [indiscernible] by the way, how about we to discuss your retirement plan. And this all which is in financial advisers to be more effective, more productive and many more informed and timely decisions. So we are piloting this system right now across a large number of financial advisers. And we are looking forward for a lot of improvements in their productivity and many other creative ways that we are kind of collaborating with us and giving a lot of feedback on how the systems can further improve their productivity. So back to you, Rajeev.

Yes, thank you. But it is important to understand that to bring everything together, AI is not the only story in turn, as an enterprise. And Grid Dynamics, given our DNA of strong cloud data, advanced analytics and user experience design. We've been at it for nearly now 17 years and riding on this foundational strength, right, unless you have this foundational strength, you cannot really do much of enterprise AI or AI or GenAI for that matter. And riding on this trend, we've been at it on enterprise AI journey for more than 8 years with our customers now. And now GenAI is a new toolkit in our repository. I think this is very important to understand that you just cannot overnight become a GenAI company. You need to have expertise in advanced natural language processing, deep learning, understanding the advanced mathematics of how to choose the right optimizer, how to choose the right activation function, designing of some of these open source neural networks, and that is when you build that muscle, engineering and technology muscle, that we've built over many years now. And because of this muscle, right, as you said, certain things don't change. For example, no enterprise data, no scalable infrastructure, no enterprise AI and no GenAI. So these things remain constant. And it is important to understand that a company that has core competence in some of the foundational technologies, you can call it the pilates of engineering is your cloud data, user experience and advanced analytics. Now this story -- now Eugene will take it forward for some of the other customers using this foundational stack that we are talking about. Over to you, Eugene.

Yes. Thank you, Rajeev. So let me talk a little bit about exactly what Rajeev just said. You cannot just use AI if your platform and your business is not ready for it. So I can give you an example of a very well-known and esteemed global footwear brand. So this company has a very -- it operates about 1,000 stores, 35 countries. And we have a very ambitious goal. How about we double our digital business, how, by going into LatAm, by going into China, by employing some of the very exciting AI capabilities, which came to the market and available through the API from our partners and different start-ups. So this strategy sounds very good, but it was really held back by the problems of the legacy digital platform. So the platform had closed architecture. It was based on the older version of SAP Hybris. And it was a platform which provided a very solid experience to the different customers, like customers in B2C channel and customers on B2B channel, customers on mobile and customer in store, all had different experience powered by different versions of the same platform and rolling out any new features was extremely painful, slow and with a lot of duplication of effort. So we came in with a proposal to replatform the whole thing to the new innovative solution and approach to the system engineering called Composable Commerce. And the idea of the Composable Commerce is all about achieving strategic flexibility, which means that you are not just buying one package and sit on it and fully dependent on the road map of this particular partner. But you mix and match like Lego blocks solutions, which are built from API-first components. And all of these components are joined in an open architecture and providing an omnichannel experience. So within just 14 months, we, from the inception to the launch, we managed to create, test, and launch the whole platform end-to-end and unified. I think you know that. This was by the compressed time lines, right? So yes, so we managed to launch it and achieve the unified experience across different channels. We achieved an open architecture, which is very friendly for integration of API first components and systems, which are so much available and ready on the market front, the start-ups and from the established companies, which provide a lot of AI capabilities, which are so useful for engaging customers in a new way. And because of this architecture and integration this will be a component, our customers are now free to innovate, to experiment and to enjoy the speed to market for years to come. And again, reiterating the value of data, scalable infrastructure in the adoption of enterprise AI. I will give you another example. Where we used the enterprise AI methods to really help in a different industry, in the pharmaceutical industry. So this is where we used analytics and user experience. And this is the case study of one of the top 5 pharma companies. So this pharma company has a sales and marketing department. And this sales and marketing department is engaging about 180,000 of health care providers, globally. However, despite a very high frequency of communications, the efficiency of those messages is very low. Why is that? Well, because actually, the health care providers receive communications from different silos of this company, which was not organized and not planned. And as a result, the health care provider could receive an email message in the morning talking about a particular product, a call in the afternoon talking about a different product, SMS or push notification in the evening, talking about something completely different. All this led to frustration and a really low level of engagement despite a lot of efforts and money going into the markets and communication. So within 3 months, we developed a new system, new marketing communication and optimization systems. We analyzed the history of marketing communications and trained the next best action AI model, which made the decisions when, how, through what channel and how frequently to reach a particular health care provider. So this system enter production in about 3 months, and resulted in a very significant uplift in all the metrics, which matter for marketing people, right? The click through like e-mail open rate, click-through rate, despite the overall decrease of frequency of communications by 60%, which really helped to reduce the level of frustration and keep the health care providers informed and help the growth of the business of our esteemed customer. Thank you. Rajeev, back to you.

Yes. So I think last 6, 7 months, right, Gen AI has been on the agenda of every CXO and rightly so because it has a lot of transformative power, especially its impact on the business. And in our Grid Lab, which is under the CTO organization at Grid Dynamics, we've built many such small short demos, blueprints, solution accelerators to help our customers understand how these kind of models can actually be infused in a business value chain and how that can then be taken into production for large-scale exploitation. And in that sense, we've been discussing the ROI and business use cases with our clients and customers across different industries. We've been telling -- talking to them about what kind of models need to be used? Where do you use a Chat GPT-3.5 versus another Chat GPT-4, which is a proprietary paid kind of a model. And where do you use a Hyperscaler and what are the best ways of using these models? And what kinds of models, how do you manipulate images, data, voice and so on and so forth. And of course, educating our customers along the way, as we educated ourselves through our demos in the lab, around the guardrails of customer IP, customer data and especially the guardrails around security and data security for that matter. And last but not the least, educating our customers on the economics of taking these foundation models into production. And I'll come to that in a bit. But the important piece is that given Grid Dynamics's high depth in mathematics, computer science, deep learning, machine learning at the very foundational levels, given our high skills density in this area, the customers trust us because we've been working with them in enterprise AI for around 8 years now. So GenAI was not something that we had to tell our customers that we do GenAI. It's not that we do GenAI. We understand the power of natural language processing and how such experiences can be woven into a business process. I think that was the key. The next piece, I think another important aspect is, I have missed talking about it is, every system today is a sociotechnical system. Every platform today is a sociotechnical system. You will be using technology to interact with the sociology and the deep beliefs ingrained in different regions of the world. And each of these experiences have to be picked into the digital platform powered by the scalability and the flexibility of cloud. And when you work with a company like Grid Dynamics, what our customers have come to see is or experience is that we are able to change the narrative of how do you take these models into production. If you just use without any software engineering manipulation and open API or you will get such a fat invoice at the end of the month. And now through the regular software engineering techniques that we all know and some of them are more specialized in the AI world, like semantic caching, classification or fine-tuning of these retrieval of these embeddings and some of the mix and match of open source versus proprietary APIs, we are able to help our customers understand the economics, and we have changed the narrative of this optimization of this model through our own experience in Grid Lab. In some of -- in one of the use cases, we have reduced the cost by as much as 65%. Now this is a very specific example. What I want to tell you is -- what I'm trying to convey is that using the expertise of our platform engineering, cloud engineering, data engineering, core software engineering skills, we are able to help our customers go into production with all these safeguards. Now again, as I said, every platform will be a sociotechnical system. I don't think anybody will build a mobile app, at least we never advise a customer to build a mobile app without getting a handle on the data strategy. Getting a handle on the customer's experience and without a handle on how machine learning can solve this and create a better experience. So in the CTO office, we have our architects, we have subject matter experts, we have user experience designers, we are business analysts, and we always start with the business first discussion. I remember, I think we were in a QBR at Frontier where we started about the 4 levers to pull in the industry that you are in. And that kind of a discussion allows us to build a road map of feature-driven, business value-driven, experiences for our customers with AI in the loop. As I said, every platform today is a sociotechnical system. And if you miss this point as an engineering and technology company and as a UX design expertise company, that will be a huge loss to the business. And most of these GenAI models rely on core software engineering principles because these GenAI models are pretrained. Somebody has done the heavy lifting. This is not a regression model where you have to go and say tune some of the hyper parameters or neural network where you change the dropout ratio or you change -- choose a different hyperparameter tuning or learning rate. It is not that. Somebody has done that for you, and they have spent billions of dollars on it. So you need to understand how do you design an API economy, infuse it into the business, drive through good software engineering practices, the cost of deployment and make business sense out of it. So this is where the Grid Dynamics has kind of mastered this interaction of intelligent, digital platforms where conversations, everything is the new norm. You can converse with your co-pilot, you can converse with your image, you can converse with your audio voice, chat, anything. So this, in this era of conversation, everything, it is rooted in core deep engineering practices. Now how are we able to do this? Well, how does Grid keep ahead of every innovation way? This is where it is rooted in our Grid Lab. This is where our innovation engine, our customer-first mindset is incubated with the deep -- with our interactional between SMEs, sales and marketing and my architects, we kind of created a pretty solid Stage Gate process before even we build some of these accelerators that we decide to build. So many -- the pipeline is big. Most of them don't see the light of the day, only the ones that make business sense for our customers, with high monetization value pass the Stage Gate. And through these accelerators, we are able to define our capabilities, new capabilities, our service offerings, which makes sense to our sales team because they are the ones on the trenches with the customer, listening and talking to them about the daily problems. So we are able to map these accelerators through this rigorous Stage Gate process to map to a service offerings and then right about them, create the right demo wherein starter kits, sales accelerators, if you will, and delivery accelerators, which actually reduce the time to market for our customers and kind of reduce the time to value for our customers. And through constant thought leadership and writing, we fine-tune our own logic, we sharpen our own saw and get better at it, as we go along. Now the CTO office, again, has been at the forefront of interactions with the analysts. We've been recognized by the Forrester as one of the leading players in Modern Application Development powered by cloud and micro services and AI intelligence. We have been a leading AI service provider, and we have been awarded by the MACH Alliance for one of the projects in the healthcare and the pharma industry. We are a strong MACH Alliance partner. We are a strong Google launch -- retail -- launch partner. We were recognized as a launch partner for Google Retail Search, Google's Vertex AI, Google's GenAI. So I think our partnership with a company like Google, which is, again, an AI-first company. Today, every company wants to be an AI-first company, easier said then done. Because to be an AI-first company, you need to have a technology foundation and the muscle to support that kind of a vision. I will now take you through a short video clip from our Google partner. And she will talk about our deep partnership in practically every area of modern intelligent platform engineering sphere across different verticals. [Presentation]

Hello. My name is Rebecca Pat, and I am the Director of North American Partner Solutions at Google Cloud. My team is responsible for working across our ecosystem to align our partners with our go-to-market motion and develop differentiated solutions based on the GCP platform. Given that a cornerstone of Google's go-to-market philosophy is that we're an open-source platform. We heavily rely on our partner ecosystem for innovation in addressing our customers' business challenges and driving business outcomes. Grid Dynamics has been a great partner of Google Cloud for several years. As a premier partner, which is our highest tier, they've achieved several Google Cloud specializations across infrastructure, cloud migration, application modernization, and machine learning. Most importantly, they have leveraged their team's formal learning and industry experience to drive successful customer consulting and delivery engagements in our most strategic customer accounts. Additionally, I'd like to call out Grid Dynamics investment in building out their Google focused AI practice as it supports one of our most strategic priorities. Grid Dynamics has been a thought leader related to innovating in the areas of Google Cloud Retail Search, recommendations AI and Vision AI. Their industry-leading solutions for forward-thinking retailers have enabled our customers to enrich their product catalogs with details of scale. Specifically, they support generation of hyper-personalized content experiences for shoppers, including virtual try-on capabilities. Solving for these types of business outcomes makes Grid Dynamics a retail industry leader within our partner ecosystem. Grid Dynamics has also leveraged Google's advanced image generation capabilities, which we see as particularly impactful across the CPG, manufacturing, banking and pharma industries. So as we look to the future, we look forward to working closer with Grid Dynamics as they expand their use and application of Google Cloud's Generative AI solutions. Together, we can help our customers drive cost efficiencies and competitive advantage through the use of Google's responsible and secure AI platform.

Thank you. That's it from the CTO team. Happy to take any questions. Yes.

Wonderful. All right. Okay. So what we're going to do right now we're going to pause for a Q&A. So from our sales organization, can we have Valery, Vasily and Rahul. And from our CTO organization, Ilya, Eugene and Rajeev. All right. Now you've -- we've introduced some of the folks here, but I know some of them are talking for the first time. So why don't we have a quick round of introduction. So Vasily, why don't you start off?

Sure. Thank you. Some of you probably met me during the -- okay. Awesome. Yes, met me during the investors Zoom sessions. So I run the account management for the company. My official title is Vice President of Client Services.

Valery?

Hey, guys. So I am a new entrant here. And by the way, you can see it, I was told that it's busy schedule today. So I run the sales team. Right now focusing on hunting and we'll see, what else?

Ilya.

Yes, hello, my name is Ilya Katsov. I'm VP of technology basically around our technology practices in data engineering, advanced analytics and cloud areas. Nice to meet you.

Thank you. All right. So what you have is the brains of the company out here. These are the guys who make things happen. So we've got two mics around. And what we're going to do is that we're going to open up for Q&A. So yes, Moshe, you have a question? Can you pass on the mic.

Thanks. Great event, Moshe Katri with Wedbush. So clearly, you have an additized exposure to two large verticals, TMT, retail. Maybe you can talk of that. So I guess, it's two questions. First, more about strategy and the other one is more about the numbers. What are you doing internally to be able to replicate the success in these two verticals in terms of diversifying and expanding into others, maybe healthcare/pharma, CPG is another one that you're talking about. It's still pretty small. So maybe you can talk about strategy. And clearly, you have the unique technical capabilities to get there. And then from a P&L perspective, what are your aspirations in terms non-GAAP EBITDA margins for the next few years? And what are the levers here in the model?

All right. Lots of questions. So why don't I kick off this. And then I know we have sales, and we've got CTO. So they'll talk from their perspective. You're absolutely right. We tend to be -- historically, we've come from some of these industry verticals. And if you look at our focus, it's always about expanding to what we call through our GigaCube strategy, right? It's basically taking those experiences and learning and replicating across this industry. One of the things that we've always talked about is Grid Dynamics when you compare us relative to the other IT peers, we are more horizontal in nature. And time and again, you've seen that over our 10-year history where we've pivoted from one industry to the other. So from an executive point of view, strategy point of view, we have the resources, we have the capabilities. What we're doing is that we're investing in the front end, whether it's the CTO front end, whether it is the sales front end. But what I'll do is that I'll pause here, and I'll have maybe, Rahul talk about from sales and Rajeev talk from CTO.

Sure. Thanks, Anil. So like I mentioned before, our approach is look at business transformation and connect it to how can we leverage our technology capabilities to drive that transformation. Now we have done those in retail and technology sectors. The technology capabilities are not changing. We are not building new technology capabilities to go after these verticals. So what we are doing is connecting it to the business transformations which are relevant to these industries. And for that, we are doing two things. Number one, we are hiring subject matter experts who can help us make that connection. Number two, we are also investing in tools and accelerators which are more relevant to those industries, leveraging our partnership channel. So using that combination, we are really building the front end that Anil talked about.

Rajeev?

I would add -- thank you for stealing my points. No. But I think what I would add there is, the hiring of the SMEs in manufacturing supply chain, we have Rohit here in the payments, wealth management. So we have kind of focused with a much [ finer comb ] on areas that are really important to our customers in pharma, BFSI and manufacturing and supply chain. And using these, the SMEs, the domain functional experts who can use the right lingua franca and the right semantics in the front-line engagements with the sales and account management team. We are then able to focus -- map them to our service offerings, which are powered by technology. One -- I think one thing that we are doing together between sales and the CTO office, is trying to get granular with service offerings. We can't be everything to everybody. So making sure that we focus on the play from our strengths in payments, wealth management, supply chain, global transaction banking, a little bit of retail banking, and then focusing on clinical trials, the next -- the commerce side of the pharma. And maybe in not so distant future, we will invest in other subject matter experts. So focusing on GigaCube, doing less and getting more focused with service offering and then going with the named customers and new logos in a very clinical fashion with business first mindset. Not with going with a Java or a Python solution or a GenAI solution. But starting with the business, the drivers of the industry and then mapping it to the technology capabilities of Grid. We are getting better at that.

Yes. And just a small addition from my side. And the lowest hanging fruit, of course, is our experience in digital commerce. Because if you see, for example, like automotive companies are trying to be closer to the end customers like direct-to-consumer things. And that's a global trend like personalization, one-on-one kind of relationships with your customers. And that has been our bread and butter for years, and that's what we can bring to those new industries, and that's the easiest way to get there.

Wonderful. And Moshe, we'll talk about your second part later on. Okay. Yes, sir.

Thank you for taking the time. [indiscernible] New York based [indiscernible] Partners. We've been a shareholder for a while. This like is more a question for the sales leadership. Obviously, the industry has seen quite a bit of challenges last like 12, 18 months, lot of the clients been "cost optimization". And if I were to look at some of your larger peers what they're doing. And they say, hey, look, we have a two advantage that Grid Dynamic doesn't have that can allow us to outperform. One is that we do more cost reduction programs that you can see nearly ROI. So in this cycle, part of this economic cycle, that gives them more resiliency. Number 2 is that typically, they have a large like consulting arm, and they say that helps them to like get into the door, at least continue that conversation. So I'm just curious, from your perspective, especially the sales leadership how have you sort of like adjust it, your sales strategy, sales tactfully talking to these customers and new logo versus existing clients like the same-store sales growth, how are you balancing those two parts of the equation.

So let me kick off with the answer, and I know Rahul or Valery, you guys can -- so when you refer to some of our peers, right? I mean, it's never -- there's a lot of similarities, there's overlap. So some of the issues that you talk about as their advantages, I mean, we have those as our advantages too, right. Rahul talked about where we focus on the quadrant. And he did talk about the fact that it's not only the top right, but there was one other element where he did refer to some of the cost optimization. So some of these elements that you're talking about, we are seeing it, too. But I'll pass it on to Valery, do you want to talk about specifically, some of the things you're seeing?

Yes. So first of all, despite the situation right now in the market, innovation still drives a lot of conversations. So GenAI was not a topic about 8 months ago, nobody was talking about this. Now suddenly, it's actually a topic where pretty much any large company will actually take a meeting. Now what I've been seeing quite a lot is that what is the learning and expand in Grid Dynamics terms, I've seen quite a few examples where we land with a very small pilot. And we land with this more fire because we actually are really knowledgeable, deeply knowledgeable about specific space. And it will take 6, 8 months before the pilot actually grows into a real program that -- where we have an advantage right of the entrants. So I've seen quite a few of these recently and this is a reflection of the depth of the expertise. Now you're absolutely right about the scale in the business consulting capabilities. So I think what will be -- and what we're doing, we're hiring people that actually understand both the lingo and the approach and the key pain points. But I think what the unique advantage here is what Vasily was talking about, for example, commerce. If you think about commerce, everybody was equating commerce with retail for a while. Actually, it's not at all the case right now, right? If you look at B2B, B2B2C or B2C, it's really expanding everywhere, even financial services companies today are trying to sell things via commerce, right? So that is the core of the company. Plus if you marry it with the cloud and the data capabilities that we have, it's actually a very dangerous combination in terms of solving real-world problems. And I don't think brand by itself covers anybody. These days, it's really based on merit. And when you go head to head into these pilots, we actually shine. So I'm very optimistic.

Very good. Thank you. Maggie, I think you had a question.

Thanks for putting this together. Maggie Nolan with William Blair. I was interested in exploring your partnerships a little bit more. You talked about partner influenced revenue going from less than 1% to over 12%. Where do you think is the right number for you to settle at? And what types of investments maybe in the sales force and elsewhere, do you need to make to continue growing that?

Let me kick off this and then I know we got the expert here. So one thing I've always told investors is our partnership strategy is different for many of the industry peers. Many -- I mean one extreme is resellers, right, that you have. The other extreme is what I call is a packaged software kind of decoupling and working around it. When you look at us, and what Rahul shared was a very unique set of very highly capable partners where we're actually working very close with them. So what I tell investors is that our partnership is very different from many of the people in the industry. But I'll let Rahul kind of build up and...

Thanks, Anil. You're absolutely right. we look at partnerships differently. We will not get into [ resell ]. That's not where we bring value. We'll always be about driving innovation, leveraging partnerships. So in terms of answering your question, I do want to drive the organization to get to about 20% in inference revenues coming from partnerships. That's a journey. I think we have had a good start. We have already made significant investments in the last 2 years in terms of hiring salespeople focused on specific partnerships. Going forward, I see more investments coming in, in terms of specific industry partnerships, and we expect to make those investments. Actually, we are doing that right away in building specific partnerships. And the investment is not just on the sales side. There's also investments that Rajeev's organization makes in terms of building solutions accelerators in collaboration with those partners.

Bryan?

Thank you all for the details. They've been great. So Bryan Bergin, TD Cowen. I've got two for you. So first, on the sales side, so I understand you've been building a direct enterprise sales or you mentioned large deal team development. Can you just dig in a bit more there? What's the threshold at what you're qualifying as a large deal. Talk about the progress on that team build as it furthest along in any particular verticals. And is this hunters for new logos? Or are you mining the existing base?

So the last part of the question, the answer is both. Clearly now, large deals don't fall from the sky and they don't develop kind of independently right away, right? So for more services companies, large deals are germination of a longer-term effort where you establish reputation and you are there in the right space, in the right spot to actually be a part of that deal when it comes. The size of the company clearly dictates also what large deal is. So far as anything above 2 million today is a sizable deal. And the -- so what I'm trying to do is from a large deal perspective, is to actually develop a playbook the way we would approach it. And actually, I think probably more important thing about what kind of deal you want to get into is disqualifying what's wrong? Because it's very easy to spend resources of the company on things that are just not the right fit, despite the fact that it's [ shinning ] object and instead really focusing so the very first thing that I started focusing on when I joined is go, no-go, what we don't go after. And I think we're making progress.

I'll just add one point, right? I think large deals is also about deal shaping. I mean, in the sense, you can very quickly jump into a technology solution rather than missing the big point of the business problem. So I think to somebody's point, we have now building this intelligent digital engineering advisory group, we call it the Idea Group. It's an acronym for intelligent digital engineering advisory. And that is where the SMEs, the investments in subject matter experts, these are functional experts, along with technical architects, the UX designers and the business analysts they interact with the customers with sales and account management team and shape the conversation. And then it becomes an MPP driven kind of a dialogue. Like as a company, we would never advise our customers to do a big bang in today's time. So it will be a road map-based delivery, feature business value map delivery, which is what I think Valery was alluding to, that 10, $2 million over in the 9 months or 8 months or 12 months makes a sizable deal and that becomes a road map over a couple of months. So I think that is how the deal shaping is paying up.

Yes, just a small addition to that to basically double this message is like, typically by big deals, someone would think of procurement-driven RFPs type of things. We are not talking about that. We're talking about deals shaped by us when we map our capabilities to business problems and try to convert it in a large-scale program.

Mayank.

Rahul, you talked about the benefits of GenAI adoption. Could you talk about the challenges customers face in terms of adopting Gen AI? What are the gating factors? And also a related question would be, how hard is it to source talent to be able to find the skills to be able to deploy GenAI solutions for your clients?

I can start, and then I'll let Eugene and Ilya help me with some of the granular discussions. So firstly, I think we help our customers understand, is it a problem for GenAI or not, right? Because if you take a -- I don't want to get into specific names of options, but it can cost you just to deploy a managed services model, $3 million a year. You're getting charged for asking questions, you're getting charged for receiving answers and plus the infrastructure behind it. So first step is we make sure that in our initial discussion of discovery and conversation, our team discusses whether this is AI solvable problem or can it be done through regular digital platform engineering ways. That is number one. Number 2 is, once it becomes an enterprise AI or GenAI problem, then we try to explain to the customer what kind of mix and match of proprietary versus open source can do the job and how we can, using our accelerators help them take on the journey of cost optimization over a period of time, right? Now you want to add something, Eugene and Ilya, please. If you get anything to add?

So regarding your question about like talent management I think this is a very comprehensive problem for us because previously, like machine learning, data science, that was a kind of specialized skill, but with GenAI basically like every aspect of our operations including like software development, DevOps, cloud engineering but also impacted by GenAI, right, because engineers needs to be very instrumental in using GenAI tools. We also build custom tools for these purposes and so on. So from the talent perspective, like there are different aspects of it. One of it is that we invest heavily in the building like talent in-house. We build in basically different types of trainings. We also have R&D programs that are engineers basically get the skills, then there is, of course, like exchange of like these engineers between like CTO programs and delivery programs, working on actual projects and so on. So in other words, we heavily invest in the building this, like talent development capability around GenAI and AI, internally. So it's literally like focused on pretty much enabling like every engineer in the company with proper GenAI skills.

I also want to add little bit. So I want add a little from a customer perspective, and like the engagements, which we are running to serve our customers. You see like the capabilities of Generative AI are huge. But at the same time, the expectations from it are inflated to much bigger point. So a big part of the work and the challenges which we see is then customers are trying to apply Generative AI for the problems, which are not designed to be sourced with Generative AI. And this is when you have to kind of cut through or breakthrough the smoke and mirrors, which sometimes created by the marketing, by different kind of software vendors and really identify the use cases, approaches, which will really bring an ROI instead of just [indiscernible]. So this is when we see some of the challenges. Of course there is privacy, there is, of course, security, many other things we are developing specific approaches, which are too technical to discuss on this forum, but we see those challenges as well'.

And the final probably on the challenges is general readiness for AI applications because if you want to implement AI use cases, you need to have data. It needs to be certain quality et cetera. That's why when we look at the AI programs, AI usually a part of a bigger program when we help with Data Lakes, data governance, quality of data, et cetera. And it goes back to the definition of the foundational AI revenue and programs, I'll say.

Good. Good. If there's one thing you know about our company is that we love to talk about technology, and we can go on all day. I know many of you are very hungry. Why don't we pause here? We'll take what 15-minute break. Grab food, come back, and we have another Q&A session, where we have equally smart people. Two presentations, and then we have the Q&A session. So 15-minute break for those online. 15-minute break, and we'll be back. Thank you very much. [Break]

All right, guys. Before we jump back to agenda, we want to have a chance for Ilya Katsov to tell you a few words about his book. His number, but the book you're going to get. And please don't forget to pick your copy. They're signed. And if you leave the $20 bill on the table, it will go to his -- to funding his next book. I'm just kidding. But the reality is -- Ilya, please.

Yes. Thank you. Yes. So actually, this book incorporates a lot of experience that we go through executing real projects at 3 dynamics. So if you go through it, actually, the book structured around different enterprise use different domains basically, there is like a part of it on marketing operations and personalization. There is another part on like quantum generation, on pricing optimization, supply chain management, production acceleration. So it's all basically focused on different domains, use cases and get an actual business value, which I believe is quite unusual for this type of books because most books on machine learning or AI are focused basically on fundamentals. So here, we tried to create a kind of new type of book, if you will, that approach AI from enterprise perspective from actual use cases and driving actual business value. And I believe it's quite unique from that perspective. So enjoy.

Thank you. All right. So we're going to get started with part 2 of our session. So we're going to kick it off with our Yury Gryzlov, who's -- I'll let him introduce himself. And we're going to have one more Q&A after a couple of these presentations. So with that, Yury, why don't you kick it off?

Thanks, Anil. All right, I hope you had a great lunch. And thanks again for coming. It's an absolute pleasure to join you today. My name is Yury Gryzlov and I wear 2 hats at Grid Dynamics as a Chief Operating Officer and as a CEO of Europe. I joined more than 16 years ago when the company just started. And Eugene mentioned just recently, right, that he is an employee #1. So my employee badge is #6, not that far. So I -- when the company -- as the company evolved over those years I basically evolved with the company. And I changed many roles over the last 16 years, being an engineer and leading global operations and leading the European P&L. And today, I'm excited about this opportunity. And I think that this is the time where we will be very -- it is transformative time for us. And we -- I think it's very exciting, and I will talk more about it. And another quick thing about me is that I love great coffee. And you probably know that there is a difference, right, between a good cup of coffee and a great cup of coffee. And it's all about knowing those details. And -- which are crucial in the process and executing them flawlessly. And I believe the same is applicable for making a great business. So as Leonard mentioned before and as Anil mentioned as well, we unveiled our GigaCube strategy earlier this year. But in fact, we've been -- obviously, we've been working on that for at least a couple of years back. And this strategy that creating the -- basically those elements, identifying those elements, driving us toward $1 billion revenue. And as a Chief Operating Officer, I'm very passionate about executing those crucial elements toward that goal. So we can achieve it. And it's not just about revenue, obviously. So it's beyond that. It's about having the right foundations in place to drive the business further to $3 billion, $5 billion, $10 billion and above as we grow. So I'll talk a little bit more today about those parts of the apical strategy in a little bit more detail. And I will I'll provide my view from the CEO side and basically things that I'm dealing with. So here are key focuses on 3 dimensions. It's allocation growth, that's innovation and talent acquisition and diversifying industry verticals. And I'll touch a little bit on each and every part of this. Let's start with geo scalability? And yes, this is my version of one of those before and after muscle building photos on social media. And as you can see, we've come a long way just in 3 years. expanding our locations from 5 countries to 18 countries, and we nearly tripled our head count along the way. But at the same time, as you all know, a lot has happened during those 3 years. And we had to go through the massive changes and massive transformations as well. Because of the war, we had to move a lot of people, a huge amount of people out of Ukraine. We had to move out of Russia completely and close all our offices there. And despite all those changes and challenges, we haven't lost a single customer, which I believe is a true testament to our resilience. And we also opened a lot of locations along the way, as I mentioned. And if we're talking about Europe, in Europe, we do have a diversified geography with big, strong centers like Poland and Serbia and many of the emerging ones, for example, Romania, but of course, we also expanded globally as well. I think we mentioned several times today, but many of our Fortune 1000 customers are reconfiguring and reallocating their operations to near shores and friendly shores. And that's where we -- since we have our centers there, since we have centers in the Caribbeans, in Mexico and India, it works to our advantage as we now can help those clients within those regions. And as we go forward and I look into the future, our GigaCube strategy talks about Europe, Americas and India as the anchor points. And as we progress with the strategy, the key question that we ask ourselves as an executive team is pretty much also all about locations and regions. Which countries do we need to add to this mix? Which countries do we have to scale in and sometimes even which countries do we need to scale out of? And we're constantly evaluating and reevaluating those factors and those assumptions in order to understand where to put our investments and as we grow from nearly 4,000 people right now to 10,000 people and above in the future as we grow. And we believe that majority of the people will be still in those regions that you can see here. Obviously, there could be some changes in the mix of the countries. But at the same time, the current regional structure that we have and the right balance of those countries within those regions will give us ability to reach that goal. But let me remind you, if you don't remember that we are in the services business, right? So we need to talk about people because our product is our people. Our success depends on our ability to add talent, to groom talent and basically a pace at which we can do this over and over again. So we also mentioned today that engineering and technology are in our DNA. And in order to preserve it, we need to be very diligent about planning and executing the growth in those regions. And you can see here, there are many building blocks that should work perfectly together when we are creating this growth framework and the growth strategy. For example -- I can give you several examples. For example, we have a very high bar to enter the recruiting funnel. But at the same time, it builds a certain reputation and brand in the engineering community. And plus, we are getting the quality of engineering talent as a result and lower attrition rates as a result of it. We've built a skill first approach to our talent acquisition. And with existing structure in place, we see that we can expand the hiring capacity to 10x without any significant changes to the structure. And obviously, we mentioned our internship program. And that's -- that also this program also plays a key role in our ability to scale and still preserve the talent. And as you can see, the internship program gives us about 15% of our engineering workforce. So it's very important for us. And Vadim will talk a little bit more about it in the next session about engineering and delivery. And obviously, when we're adding inorganic growth to this mix, it's important to have the solid integration framework as well for all those acquired companies to be very aligned and to make this integration as smooth as possible between different departments and different regions. So the next part that I want to touch based upon is our European part. And let me start with the next part of the strategy, the next part of the GigaCube strategy is that entering -- it's basically entering new verticals. That's another part of the -- another aspect of the GigaCube strategy. And traditionally, I think Anil mentioned earlier today, about 80% of our business has been centered around Retail, CPG and TMT. And when we presented the strategy, we mentioned that we will move the focus to those new verticals as well, particularly pharma and life sciences, BFSI and manufacturing. And we should do that in both an organic and inorganic fashion. So that's why part of my role as the Chief Operating Officer is to reach to that point in organic fashion as well. That's why I'm working closely with our M&A team, with Anil, with Vadim, Rajeev and others to get those targets that we can evaluate. And also, there is -- to be honest, there is one selfish reason, since as I mentioned, I also happen to be a CEO of Europe. So I'm constantly looking at European targets for us to acquire. And that leads me to the second part of my role, and that's leading the European P&L. So if I take the same example, the same period of those 3 years, we will see that 3 years ago, almost 100% of our revenue was coming from the U.S. And if we -- but at the same time, most of the delivery locations were in Europe. If we take a look at the snapshot of our revenue right now, you will see that roughly mid-teens of our percentage of our revenue coming from Europe. And -- it's started with, as I just mentioned, it started with M&A efforts in 2020 and 2021 in particular. So we acquired 2 brilliant companies with brilliant' teams. And we used that as a foundation of this European business, and then we expanded on the top of it. So we expanded the capabilities. We expanded the teams, right? So we invested in the sales team and a delivery management team, CTO office and so forth. And this is a good example of transformation from delivery-centric location to grow centric region. And it's not -- so Europe right now is no longer just a delivery location anymore. So it's a fully functional business unit. And I believe there will be more examples -- more examples like that because if you look at this example, we'll see that Grid Dynamics again, as of right now is not only a global -- truly global company from the delivery point of view, but also a truly global revenue-generating company with Europe as a first anchor point. And in order to showcase that, this is a quick customer success story. Since, again, all of our success depends on our ability to help customers. And this is one of many examples of our AI capabilities applied to the customer business and driving the positive results out of it. So this particular one is automotive parts and tire manufacturing company, leading player. And they wanted to create AI-based platform to -- and added to their smart tires portfolio. with advanced tires analytics, basically to look at predictive maintenance of the tires and so forth. And we build this platform. And this allows us to again, leverage different teams from different parts of the world. And this is a very good example of a true synergy between different regions, different teams and overall -- our global AI capabilities apply to the regional structure. And with that, I want to thank you again, and let me turn it over to Vadim. Thank you.

Good afternoon, ladies and gentlemen. I believe you had good lunch, coffee, and you're ready probably still to keep your attention. So I still don't believe you have to wait for 3 hours to the most exciting part to this presentation. My name is Vadim Kozyrkov, and I'm Head of Engineering -- Global Engineering. And believe me, I would be a wrong Head of Engineering, if I did not believe that it's the most exciting part of Grid Dynamics. I, probably, will be just an imposter. So the task of engineering appears to be very simple, deliver on promise while maintaining high quality, providing full scale. What could be simpler, right? The famous last words. So believe me, if I wanted to give you all the details of that simplicity, I would request you to come with the toothbrush and pajamas because it's really a brilliant lot of different simplicities that comes under the hood. But let's start our journey. Before the lunch, Anil introduced navigation and the computer engine of our business. So it will be my pleasure to take you on a guidance tour to the engine room of our success. So Yury showed this picture, and I'm sure you might have asked yourself, why would the company of our size, which is not that enormous, that large will have a presence in 18 countries? Well, I will give you 3 main reasons. Number one, remember, John Dillinger, okay? The famous bank robber in America in the 30s, when he was asked why do you go for the bank. He said, "Well, but that's where the money is." We go to these countries because that's where the talent is. We choose these locations because that's -- they have biggest universities, the best university, the best infrastructure and most important, the developed markets. So we go there to cream skim best engineers. It also allows us to create a team fully distributed teams and we are not constrained by recruiting in every single location. So we have a freedom to recruit people anywhere in these countries as long as they fit our requirements. So it gives us freedom to expand and give us freedom to do something. Number two, I'm sure you're reading news and you have noticed that recently from geopolitical point of view, the world becomes more interesting. When we spread geographically, it allows us to mitigate the risk of being just in one location [indiscernible]. So when something does happen on this [indiscernible] we quickly can overcome it, and I will give you examples later in my presentation. And number three, from a most important, we're building the follow the sun model. And again, I will give some more details on it. That allows us to bring about the much faster time to market for the customers and faster delivery. So there are 3 pillars of our success. What's the deep tech expertise, follow the sun, our resilient continuity and good processes. Yes, I'm not going to play [indiscernible] Spanish acquisition of just stick with the 3 pillars. So the pillar #1, deep tech expertise. We have this skills pyramid of excellence, and we really have highly specialized engineering workforce. Why do we do this? Well, same reason, as I mentioned -- that's great. Mr. Murphy. Okay. Great. Okay. Same reason I mentioned John Dillinger. We go with the values with the customers. And in order to go where the value of the customers is, you -- inevitably you will have to have very skilled workforce. We go, as I mentioned, to locations where the best engineering environment. We pick up good engineers and we recruit them. And we then make sure that when we go to the customers, we can bring about new technologies and most important, discover the value for the for the clients. So deep technology specifics. Just a few numbers. I know you're addressing this doctrine in physics -- I have doctrine in physics. Doctrine physics and the Head of Engineering will just show you 25,000 slides with the numbers and it's late in afternoon, and we wish he goes away quickly. Guys, I will be showing you numbers, but I will only dwell on those that I believe important, and I'm sure you can read faster, then I can talk. So the rest of the numbers, if you have questions, ask later. So we have a lot of certification, we issue a lot of simplification to our engineers, again, to mention -- to keep them reskill. So when something appears, we can react very quickly. I will have a slide on GenAI separately, but I mentioned that GenAI 8 months ago was unknown entity. Today, we have actually hundreds of engineers trained and ready to be deployed. Now when we go to these locations, again, we don't go for the volume. We are very selective. So that's just a simple example of a number of candidates that will come through our pipeline, a number of candidates that will be hired. So less than 2% of candidates will be hired. That's how selective we are. Can we grow faster? Absolutely. Can we increase? Yes, Yury mentioned that we managed to increase our recruiting capacity by 10x. We -- because we can always apply something else, and I will be talking later to actually increase without dropping the engineering requirements. So what we do? We have internship program. And the internship program of Grid Dynamics is not taken account and teach them to type Hello World. No. Our internship are very tough. Again, this is an example just for this year program. So there's a thousands of applicants that come through as they go through the rigorous filtering. And then we only hire the number of interns that we believe is sufficient for our business. If we need to increase, we can. We have enough capacity to actually dramatically increase number of interns. Then we take those interns and we put through our training, and I will talk in the next slide, we put through our training, and we produce engineers that are capable of doing and because they're spoiled by 10 years of some old technology, you can teach them basically from the -- you can make them ready to accept new technology without this baggage of the old habit. What's more important today? It's a very high retention, and we're using them at 80% of our clients. So this program is extremely successful and scalable. Can we increase it [ 5x ]? Yes, we can. So continuous education. Now I mentioned we have recruiting. We have internship. It doesn't mean we leave our engineers alone. We make sure that they study all the time, okay? So we have hundreds of courses, engineering courses. And you can see that this year alone, the 3,000-plus courses were completed and considering then that we have almost 4,000 people in the company, you can calculate that almost every engineer goes through training every year, okay? And this is additional to internship and additional to recruiting. So basically constantly educate engineers to new technologies. Let's talk about AI. So GenAI, and again, I know you had so many words about AI. And so I'm not going to repeat I just want to say that when GenAI appeared 8 months ago, there was a buzz in the industry, but no one knows what this animal is about and what to do with that, okay? So what we did, we immediately started what is there from a fanatical point of view. Then we tasked our engineering management, okay? That's a theoretical thing that GenAI can bring to the business. So what we did, we immediately created courses, but there were not pure theoretical courses. We ask our delivery to go and see what can we do inside our internal projects? How we test and study how GenAI behaves? So before we take it to the clients and before we just give pure theoretical courses, we actually infuse it with the practical applications. And once we actually have a lot of training, then we continue update the courses, and we make sure that whatever we sell to the customers, we actually know how to do it inside, okay? And I mentioned we have 3 quarters right now. We're going to -- we're in the process of preparing 5 more, okay? And I have some companies claim -- some big companies claim that they're going to put every single engineer through general training. I have seen those courses. It's 10 minutes courses. Sometimes it's 1 hour course. Our introductory course is actually 5 hours. It's just introductory course. Once they got more advanced, and we want engineers to go through all 3 advanced courses, it takes weeks, not weeks in the classroom. Remember, those engineers, they have day job. So we have to spread to make sure they don't impact their production activity, development activity. But up to, for example, after 10, 12 weeks, they go through advanced training in GenAI, not just 30, 60-minutes training, introductory training.. So when I mentioned recruiting, internship and focus on continued education, this creates a universe that we utilize. So they're not separate across it. As part of the big universe as linked to demand generating with our sales. We work with HR or the CTO offices or work with the sales, account management. So we get this information forecast and we try to prepare exactly what it needed in the quantity, what is needed. And we have visibility ahead so we can plan our training ahead. So we spoke so much about AI. So the next 2 slides, I can assure you, have nothing to do with the GenAI. As a real example of real people, and I selected just 2 of them, so don't worry we're not going to spend too much because I believe they are very interesting cases. Okay. Diana, as you can see, she is 10 years with us, so quite a nice retention. She came as the student of Polytechnic Kharkiv. Came as a developer in '20 (sic) [ 2013 ], she selected to be a delivery manager. And why I use particular her out of 4,000 employees, as an example, why? She is proof that universe has a good sense of humor. Why? Her husband used to be a delivery manager in our company when she became delivery manager. Then he decided that the grass is green is somewhere else. So he left for other company. And sometimes his company sent him with his team to the clients. Unbeknownst to our competitor, we're also got involved with our clients. And after a while, Diana became a program manager and her husband reports to her. Isn't it great? Another example is our Bartosz. Now, that example of internship. As mentioned, it's not taking account and teaching to presell a world. That guy has PhD in chemistry. He worked with NASA. He was lecturer. He worked for NASA. In fact, he was instrumental in designing the most important piece of international space station. Anyone wants to guess, which one? The most important. You're right, toilet. Yes. He's PhD in chemistry. So obviously, yes. So after its success with designing a toilet for International Space Station, he decided to actually get educated in development, become an engineer. He went through our internship program, and now he is our principal big data engineer and representing us with the clients in the conference. So again, our internship is not something that we work with -- again, it's a rigorous selection and we can really work with very talented engineers. And when I was talking about education, there was a section that set the quick -- the accelerating development. What it means we constantly make sure that when we hire somebody junior that he will become a staff engineer on the principle in the shortest possible time. That's how accelerated. So we have mentorship and if somebody shows talent, we quickly put him on this quick development path, and that allows us to expand quickly without actually relying constantly on external hiring, which we all know very tough nowadays. So follow the sun, we have a target to achieve up to 40% gain. I know a lot of customers claim that they have follow the sun model, but it's sightly different to what we're trying to achieve. Some customers claim they follow the sun, just because they have development centers all over the world. It's of the same thing. We have the limited team, and we have a rule if it's a large enough team, it means above a certain number of engineers, they cannot be in 1 location. By rule, they have to be spread in more than 1 location. As I mentioned, it's helped us to mitigate the risk. But it also help us to provide this uninterrupted development and will -- with the benefits of reduced delivery time. It might not help with the cost, but time to market, absolutely. And time to market, very often more important than just a few bits when it comes to -- for the clients when it comes to -- I didn't know I pressed. Okay. So what model we deploy, we like to deploy a self-sustained teams. PODs, we call them. Means they can receive the task from customer and quickly turn it in success and actually be responsible for that success because I mentioned the fully scalable on large program, we have a number of teams, we have some clients that would have, I don't know, 20, 30 PODs and still be successful. And very important, this co-innovation model. So we always develop with the customer, try to develop with the customer. As you can see, when we provide VP or POC, it's mostly our job. We make sure that we use our talent, we do what customer wants. But then when we start scaling, we start bringing customer people, we educate them. So then when we move something live, the customer action is actually self-reliant, they can maintain the systems, and we can concentrate on expanding other areas or other programs. Okay. Now I spoke a lot about other -- our capabilities. So here's a few examples that they are not just worth. During quarter we have 0 disruption. 0 disruption. We went through a lot of pretty exciting times and yet not a single project with the customer suffered. Why? We have distributed teams and when big development centers, for example, in India were devastated because the government stopped access to the buildings or to the offices, we haven't noticed. It didn't change a thing we were doing. We trained for years. We have the processes. So for us, COVID was nonevent. When war started, we had 0 interruptions. Why? Well, we have the distributed teams that work together. The one team, the filling for one team. If you example when we have had to vacate more than 4,000 people in Ukraine from the war areas to the safe areas, other engineers in other countries, in Russia, in Poland, in Serbia that we're putting double shift to cover for the engineers. And because they were from the same team, that was easy accomplished, okay? Because they knew this stuff, they knew the work, they knew the storage so they can carry this. That really help us a lot. We are very selective when it comes to managers, and they have to go through training and they have to go through actually exams. And we could achieve all this in spite of [indiscernible] 3x growing the number of engineers and acquiring 4 companies and integrating 4 companies. All that with 0 interruptions. So that probably attest to the resilience and continuing to our business. And the last slide that I will show you, the picture is better than thousand words, right? So I decided to combine picture with thousand words. So here was a what I got, okay? Those are customers from our customers and I have to be very selective because when I ask my delivery people to bring -- if they have any testimonies, I could probably have 10 slides like that, okay? So I hope I bring my point clearly. We have processes. We know how to recruit. We have know-how to train, we know how to deliver. And customers love us. So that's it. Okay.

That's usually the response when I start talking. So look, I'm just going to keep it very short. As I said earlier in the day, this was all about technology, all about understanding who we are. But that said, we had to have a couple of slides, right? And I'm sure all of you will have a lot of questions. So -- all right. So sometimes, it's good to take a little bit of a perspective of how we've executed over the last 3 years. I know we talk about quarters, we talk about some of the near-term things. But when you step back and look at what we've done, I mean, it's pretty impressive. So as Leonard pointed out, we've tripled our revenues on a non-GAAP EBITDA, we've tripled. And if you look at the first 9 months, compare 2020 to 2023, obviously, you have a big growth. Fourth quarter of 2020, we had some pickup. So the comparisons are a little bit more reasonable. But it's a company that went public, you know the history. And we have encountered multiple challenges. We've come out stronger, and we continue to believe that we will be like that. When you look at what we've done, right, if you look at both from a customer concentration as well as looking at our top 5, top 10 concentrations, it's been declining. Now you see a little bit of a stabilization over the last couple of years, but a very interesting thing is going on. Even within our well-known industries, whether it's retail or some of the CPGs where there's an overhaul. Our traditional customers are moving to new types of customers, right? If you look at our distribution across these industry verticals, it's been actually diversifying. And these are all the efforts that we put in place over the last 3 to 4 years. Now let's talk a little bit about our model. Look, you all know about our non-GAAP gross margin of 40% and non-GAAP EBITDA of 20%, but we're introducing our long-term growth target of 20% plus. Let me spend a minute or 2 on each of these. When you look at our growth profile, we feel very confident. We are a growth company. Our whole engine is designed towards growth. You look at our customers, you could kind of parse them into 3 buckets, at least from my point of view. One is our existing customers, and we deal with very large logos. We have not even scratched the surface in terms of what we could do at these very large logos. I don't have to talk about the activity that's going on in the new logos. It's been very robust. Now it's not filtered up to the top this year because we all know about some of the macro things that are going on. But as Leonard pointed out and we talked about in our last earnings call, we're incrementally positive on that. And the third thing is that Rahul talked about his partnerships. We started with nothing. We're now, what, 12%, and he clearly talked about doubling that as a proportion of these. So when you add up all these things and do a bottoms up, we feel very good about our growth profile. Now when you look at our gross margins, non-GAAP and EBITDA, I'll make the common commentary across both of them, we've been at our target model. There are multiple quarters in the past that we've been there. Now as we progress in 2023, obviously, there's a certain macro element. But I think what I want to tell the investors, again, is that we feel very good about our long-term model. Some of the movements that we have seen in 2023 are temporary, that could be -- will be reversed. And as we scale our businesses, you'll start seeing some leverage in the business months. And finally, I just want to make one comment on the M&A. Look, we have made 4 acquisitions. It's a pretty robust pipeline. Just to give you a little bit of a sense over the last 12 months, we looked at multiple acquisitions. This is something that we get a lot of questions about is how many companies have you looked and everything. At any given point, it's a very robust level of activity, and we have a very strict criteria. We have our GigaCube strategy, locations, capabilities, clients and so forth. And that will continue on. So look, with that, I will pause here. I know there's going to be a lot of questions. So can we have the whole management team come up and we're going to have some good Q&A.

Don't be shy guys.

All right. Who wants to kick off? There you go, Bryan.

Maybe we'll touch on the last point there on M&A. So you've done 4 deals for strategic deals. Can you talk about the learnings of those deals. What's worked really well? What hasn't? What have you learned through those? And how does that evolve the process for M&A?

All right. I guess you haven't heard enough from me today. Is it working? I'm not sure. Okay. Good. Yes. So the best way to have M&A is not to have them at all, right? I mean I do think you do you just grow organically and you build your business as fast as you can. The reason you go public in our case, right, one of the reasons is to get capital to acquire companies. And we always stated 3 reasons to buy the company. It's a geography, it's a technology, and it's actually the vertical, right? So each deal has a little bit of a variance in its own. We can tell for sure that the first 2 deals were done with a little bit more depth of the understanding where we will go and both of them converge nicely. As you know, Daxx was more about us to bring together to working with technology startups, both in the United States and Europe, particularly in Israel, some of the deals became really big deals. And we learned how to identify those early nuggets to make them major strategic clients. The second deal with [indiscernible] is a foundation of our European business. As you know, commerce tools, the e-commerce, we are actually catching up to the London office. And what Yury is building in Europe, it's a foundation we laid out in U.K. The next 2 days -- 2 deals were Indian focused. And to some extent, there were more kind of a combination of what we can do with these guys, but also building the capabilities in India. With Mutual Mobile, what was done with the earnout period, it gave us more access to the UX capability and something, again, defies the purpose. If you look at our friendly competitors from Latin America, they will tell you they know how to do UX. I tell you people in India can also do UX. So we established more positioning in Texas. We added a very good capabilities in the UX practice, which are integrated with our UIs in India. When it comes to the final fourth deal, which so far has been done. The deal was more about bringing the specialized services, getting more kind of longer-term traction but also keeping in mind the presence in Chennai, another strategic locations. I mentioned we're going to open the third office, but you needed second. And [indiscernible] where are you going to be in Pune in due time, right? And as we're getting more and more business with manufacturing. As you know, from the [ cradles ] of Tata, it's really the foundation of industrial parts. So in various forms, the all 4 deals were different. We are still integrating a lot of front-end efforts, the back end done well. But the front end, something we keep learning because obviously a set of customers are different. Going forward, Yury kind of slipped the tongue, mentioned that Europe has been our core focus again. We're looking for scaling the business in that region. We go through a lot of discussions. And I would say we have a few [indiscernible], but nothing right now we can definitive, we say what we're going to do. We softly look at the technology associated with our new areas of expansion, which is insurance, insurance is a big part of the recent growth as well as life science. So those 2 areas we look for. And of course, anything we touch is manufacturing supply chain is our key. We believe that the core technology itself, not the software, which we need to maybe buy to catch up. It's internal matters. And Yury mentioned to you, it's hours and hours of thing. You cannot buy knowledge. You can buy experience. So it's a long answer for a short question, but it's to me, that's where we're heading to. And we're a little bit slow because we've been, again, more selective with our size, we can't make mistakes.

Thank you. Mayank, do you have a question?

Yes, please. You had a chart earlier, which broke down the clients by key accounts and core accounts. Could you give us a sense of what the penetration today is within your key accounts? How much more headroom do you have to grow any sort of numbers around that to give us a sense of the opportunity within your top accounts?

Yes. I can't give you specific numbers. But look, all I can say is there's enough headroom out there. And I see the headroom to actually increase because of what I said earlier, AI and Generative AI id creating opportunities for us in the cost savings and efficiencies plays. Those are the areas we have not played in the past, and those are all great headroom for us to grow.

One thing to -- yes, on -- okay. Yes. So by the definition, we call them core accounts if they have potential for growth. So it's kind of -- we actually define those where we can make bets on becoming our kind of Tier 1 accounts in the long run.

Good. Josh?

Perfect. Josh Siegler, Cantor. Great presentation. I really enjoyed it. I want to take a step back to the GenAI discussion, specifically around understanding the framework necessary to plug in GenAI. How many of your current clients, I'm not asking for an exact number here, but rough ballpark percentages how many of your current clients already have that existing enterprise AI framework, you can just plug in GenAI solution? How many still need to build that framework up? And are you seeing demand from those incoming phone calls, "Hey, I want a GenAI solution." How much demand is there to really build that framework right now?

[indiscernible]. But I think, firstly, I mean, you don't need to plug in GenAI to start with enterprise AI. They deal with the business problems in different ways. That is number one, right? And customers may have not exploited fully enterprise AI capabilities, for example, they may have not infused deep learning models and supply chain or they may have not infused pair programming using a copilot, something like that. But it does not preclude them from using GenAI. So they can get started. Every customer has a propensity to start at some point given where they are with their data strategy and their business problem. So I just wanted to make sure that it is not a kind of a pretty exquisite, right? But if you build an enterprise culture of using our machine learning and artificial intelligence in your business processes, it's quite likely that you have the foundation and the frustum of mature data -- enterprise data approach, data capture approach and certain set of skills in the company who can define the business problem, which is amenable for a machine learning solution, right? So this is one [indiscernible].

Yes. One very interesting things about GenAI and the reason why it's taken over the world, it is because it's very easy to get started. It's very easy to make a first step. It's extremely hard to take a second. So it's hard -- it's very easy to create a [indiscernible] to excite our executives and to get the things going. However, when you start to roll things out to pilot to production, you start to deal with complexities, with challenges. And this is when the strong engineering capability, access to data, data pipelines, API ecosystem becomes extremely valuable. Even understanding methodology, how to deal with this system, where you cannot make a strong expectation what it will do, right? It's a relative [indiscernible] system. Today, it's like this problem tells you one thing. Tomorrow, it says semantically the same thing but in a different way. You cannot test it very easily. So this is when our experience. Our decades of experience dealing with search systems, which are also [indiscernible] processing systems is really handy. So the answer to your question is the spectrum of maturity of our customers in enterprise AI is very broad. Some of them are even trying to leapfrog the enterprise or like traditional machine learning and action like traditional [indiscernible], let's go all the way to Generative AI. Some of them already have a very high maturity, and it's easier in this case to integrate GenAI capabilities. Hope so.

All right. Moshe, do you have a question?

So how are you finding the skill base of the software engineers are you getting in India, especially comparing that to the skill base that you're getting out of Eastern Europe. And I'm talking about this in the context of some of your peers that had some challenges getting to that parity, if you will. And it took them some time to get there. So maybe some color there, especially in terms if they're able to deliver on time, on budget, et cetera. And then on another question, you also stated an EBITDA -- non-GAAP EBITDA margin objective. Can you talk about some of the levers that you can use to get there?

Let me get Vadim first. I know you can talk about -- yes.

Yes. So great question. Look, I just wanted to also add when the question was what were the challenges. You actually touched on this point. There's a positive challenge for us, and I will explain why I think it's positive. This is a customer perception that somehow engineers in India are different to engineers in Europe. I can assure you that's not the case, okay? Especially when you put them through training, it's more cultural than anything else. Technically, they are very capable engineers. And when we build, as I mentioned, this follow the sun team, we make sure that our training, our processes and our skills are uniform. We cannot build a team where, for example, skills in India will be inadequate to skills in Europe. Because you will never be able to do to follow the sun. So to answer your question, I don't see the difference in skills. It's just about cultural adaptation processes, but they have plenty of good engineers in India. 1.5 billion people. There's plenty of engineers to go around and the best ones. So we just need to find a good engineers to train them that...

So you heard from the guy who runs the whole global business. Let's hear the father of Grid Dynamics for India.

Well, thank you for the title. So I think when we built India, I think we were very clear that it's not a place where you throw QA work and throw low-end work and then keep -- India is a full stack end-to-end location, number one. Number two, -- all the engineers in India today have been selected, interviewed through multiple rounds by all our counterparts in Central and Eastern Europe. So there is a kind of a sense of ownership that these are our engineers. These are not engineers hired interviewed and locally done and onboarded into the company. They have gone through a very selective process with our European engineers. Number one -- number -- the third point the internship program in India is also as rigorous as we have because that was the foundation. We wanted the best interns in India. We started India on 30th November 2022. In January of 2023, we've had the first batch of 30 engineers as interns. Out of the 30, we made 20 offers, 18 joined. And these are all from Tier 1 schools, all the IITs and the bits and NITs. So I think what Vadim as a Global Head of Engineering, the way he articulated that is, for us, India as a geography gives us scale and access to talent. Europe as a geography, we have a history with the best engineers. I don't think there is any kind of a mismatch in the way we blend them. They work together in mixed PODs. The DM is in Europe, the engineers in India, the DM is in India, the engineers and in Europe, they work together as a mixed POD. And learn and deliver together.

It's a long answer to the question. So I just want to answer one question, which everybody has in it's mind. We have great engineers. We have the best in -- we make America great again. Okay. Guys, yes, 3 things, which Anil brought in. Rate of growth, gross margin and EBITDA. I want to answer that because it bothers everybody. So first of all, there's no direct correlation between EBITDA margin and engineers. It's really gross margin, which we need to focus on. And to work through all the 3 parts, they're all interconnected. So first and foremost, in terms of the gross margin. So Indian engineers, Eastern European engineers, Latin American engineers, it's all about the scale of locations. We continue to train the best people. but its ability to efficiently use the skilled people in each location to a substantial number makes a difference. Today, we have more people on [indiscernible] than we have in hydro project, proportion, obviously needs to be corrected. But we're catching up, and we're catching up really quickly. So we train people. We engage with the university, but the most important, we can rate the scale. The second part of the gross margin part is the value to the clients. Our sales people can talk a lot about this. But at the end of the day, there's always been a bit of a discount to Indian engineers versus European and this probably with [indiscernible] this question. So I'm not going to say our Indians are better than other's Indians, right? There's no reason to do that. I'd tell you one thing which is important, where I believe the strength is, if you look at the management leadership of our comp, right? So you talk about the company, how many of that would bring on the stage the Indian experts, people who come for me. Not to me, and this is just the front end, right? We have a lot of more leadership globally. I think the culture of international understanding of the business matters to bring good engineers to them. When you have leadership, the people are very passionate. So we built a very strong machine in Eastern Europe, we are building even better machine in Central Europe. But as we expand our leadership team, we expand location, we expand the value of training, the gross margin part on Indian side will be at least mature growth. And then, of course, you guys always ask at the earnings call, the question about inflationary rate. It's always like that. So that's driven by rate of growth of your business. When you have a generation of new business, then obviously, you can be more efficient. You can have -- you don't want to be only senior engineers. And you want to have many more insurance. The pyramid needs to be a certain way that you need to get efficiency, which we are striving for. But to get higher rates of your business, you need to have fairly non-billable people. I would love to have no billable people, right? But that's not what happens. So you need to have a lot of R&D guys. But you need also the consultancy merit expertise in sales organization. The guy in sweaters, Larry noticed, kind of he's a new guy. So sorry, forgive him for not wearing the jacket. But he has a very unique experience. It's a company [indiscernible] Wipro and EPAM, right? And that gives him a perspective and he drives the excellence and scaling and solutions and bringing top-notch people to Grid Dynamics, not from EPAM from everywhere. Disclosure, right? At least for a year. But the reality is the good people like to join the good leader. So that's inevitable from the EBITDA standpoint because that's kind of overhead you need. So 3 compositions together, assuming the industry growth, which we have to assume because we build the business and we have -- will bring us to this 40-20 model. If we choose to cut off and not invest into all these key skills. We can get you 20-40 tomorrow. That's the dead end because the GigaCube model, a $1 billion revenue model requires all the things to this. So sometime we [indiscernible] we owed on yield to cut a little bit more cost and doing some other crazy stuff. We are bespoken our pursuit and will continue to grow to $1 billion. I think the reason I just use this moment because in many things, they might, okay, it's all great, where is my model. So here's your model. I want you to understand. Next time we'll get together, we'll bring more customers. Of course, were very gracious to Melissa and the frontier that having here. Sometimes the customer is not sure they will understand why they need to be at the suppliers because biased supplier, but you know what you need to be biased. I have been running multi-hundred millions and million dollar businesses on the corporate side. I want to be biased to suppliers. Bias means the partners is the one who you call in midnight, and they pick up the phone in 45 minutes and 2 hours later dispatch. That's not equal opportunity. That means unfair advantage and commitment. And more we have that kind of things, and we follow the sun, by the way, it makes easier because 2:00 at night at somewhere 10:00 in the morning. But I haven't turned the phone off for almost 30 years. It doesn't mean you call me, but this is the competition, which we need to restand with the bigger guys. So thank you for -- thank you by the way, for sticking with us. I had a bet that most of the buy side is going to be gone after lunch is only sales side who -- troopers. But I see both. So thank you for that, and please continue questions.

Yes. So I think we have a question from Ryan Oh, sorry, after that, we'll go with Maggie. Ryan, go ahead.

Ryan Potter from Citi. I'm going to try to combine delivery and sales here in 2 part question. But you mentioned you could 10x the capacity with your current structure. Is that more process base in terms of you mentioned leadership and some of the training you have? Or is it more of the footprint you have in terms of your current geographies and locations? And what gives you confidence in that 10x number on a sales standpoint, how much would you say the follow the sun that you have is kind of driving some of the incremental sales wins you've seen in the most recent years?

It's all the way above because we build the processes, okay? [indiscernible], we build them [indiscernible]. So that we need to be ready. So whatever happens and be excellent. So you cannot go cheap on that. You have to have a machine to do. And we trained our processes to be successful on today's scale. If I need to increase the scale is done. So I believe 10x mentioned was we increased 10x, not that we are going to increase next year 10x. We've increased 10x and it was sustainable. Our processes didn't break -- now can we scale more? Absolutely. Whether it's going to be 5x, 3x or 10x. I don't know.

So let me introduce one of the secret weapons. He was very solid today. We have Igor Yagovoy [indiscernible]. He was not wrapped, so be careful. He doesn't -- he hasn't been free to answer all the way how Rahul has answered. But Igor many, many years ago, has help me to build from virtually ground zero, the office in St. Petersburg. And it's not Florida, it's Russia. And he's been very instrumental to understanding how the scale works, 10x more, he did way more than 10x. And they end up in the United States. Now we are talking about diversity of things. Now I think it represents North America, including Mexico and Jamaica. So obviously, we need to bring more people from the different organizations. But what he's tasked with right now is to add more locations and those locations with the university skills require for us to scale. So Igor please talk a little bit about your experience in your locations.

Well, yes, I started with the company many years ago, like 14, I think Yes. I joined when the company was relatively small. And right now, here we are. We are public company. And I'm pro. Thank you, Leonard. So talking about the locations. I think that Americas region is going to grow further. I think that combination of on-site like U.S. and connection to near shoring is truly like a great service and not only service, actually, it's very convenient to our clients. We will be investing more in LatAm region and it's growing rapidly and it will be growing. We see a lot of demand. We added Jamaica, which is not so obvious. However, even there, we are connected to all local universities. We work directly with them and actually develop kind of a training programs within universities and pretty much use that students or ex students. And actually, this is really a great baseline for us. I don't know if that's probably it.

I mean -- the reason we through this examples sound small, but it's going -- it's going to be 3 legged too. The Americas together with India and Europe. And I think answering the question list on how we do that, more connection with universities, more representative from professors of those universities to be part of our DNA. And I think the other question you asked about sales something. Okay. So what was it?

I think the question was how many of our customers are wanting to go follow the sun. I want to talk about the follow the sun that we are talking about is very different from what other companies talk about. Majority of our customers are actually using follow the sun model today for application support, infrastructure support. We are talking about follow the sun model for core engineering work. And a few of our core and key customers are doing that more from an engineering standpoint, but a lot of them have not tried that, and we are working with them to move towards that model. So I would say a small percentage.

One more question.

Okay. So Maggie, you had a question? .

Yes. Maggie Nolan with William Blair. So you have one of the original team members and you have one of the newest team members. So I wanted to ask maybe as we think about the theme of scale, and you've already scaled so much since you joined, what's kind of core to Grid Dynamics, what hasn't changed -- and then on the flip side of things, as a newer member to the company, what do you see as the biggest opportunities ahead?

Thank you. It's actually a great question. And as founding member of the team, I can say that one thing, which we are carrying forward is our engineering DNA, right, and passion for great engineering and innovation. So this is -- this is a culture which actually makes it not so easy to get in for the engineers because -- and it also helps our engineers to stick together more, right? This is when we are getting in the Grid Dynamics, we are getting into the environment where they are excellent engineering, innovative thinking and skills -- deep understanding of technology is really valued by all the team members, including like the executive team because many of our executive teams are there engineers. And some of them are even quoting rate now, okay? It is there, right? So that is the difference because we really understand engineers because we were engineers, we are engineers. right? And that's one of the big thing. This and also a real dedication to the customer success because and take proud in your work because this pride in your work, this is what keeps you at night when something goes wrong with your service, you stay at night, not because you have to. But because you're proud of your work and you cannot allow this thing to fall. This is a very interesting, I think, and core to our technical culture.

So let me pass to the newer member before Valery says the word. So basically, what Eugene told you, if you like the famous [indiscernible] of eagles, welcome to Hotel California, right? So we started in the Bay Area. It's easy company to get any long as you know your skills, it's impossible to get out. That's why the [indiscernible] and thank you for your service.

So maybe the question was about potential and uptime for the future, right? So when I was at Wipro, very often, the customers would come and say, "Hey, can you give me real good engineers, people that are versatile that can think on their feet. Don't give me people that know from here to here exactly what this is, right?" And if you look at the market overall, what you clearly see is that every company is becoming a software company and everything is becoming software defined. So as we go on EBIT industries that [indiscernible] think about completely brick and mortar everybody is adding digital capabilities, and this will only grow. So the share of the -- so the change versus run, right? As you can see, over the years, the run, even though it's still a big portion of the overall spend, it's actually is not growing. Because the pressure on the cutting costs from everybody is very strong. So that section of the spend is either the stale or going down. The area that is actually growing is the area of the change. And so now this year, it's -- it is different here because everybody is scoping cutting costs. But overall, the future is all about actually getting more of having things done digitally because that's where the world is going. So my opinion is that this company is actually the perfect spot with the kind of talent it has, with the kind of discipline it has and the kind of process it has to actually leverage that and grow with that trend. That's my view.

All right. So with that, I think we are going to wrap up the Q&A. Leonard, do you want to close with any closing thoughts here? Or...

I do want to thank you for being here. I want to thank all the people who have participated in this event. Do we still have people on the line?

Yes, we do.

Okay. Well, if you didn't fall asleep after 4 hours of dealing with us then we're doing something right. And sorry, you didn't get lunch. So you will get virtual lunch when they go. So thank you again. And like any performance on the stage with the [indiscernible].

Thank you