GDYN 2025Q2

Good afternoon, everyone. Welcome to Grid Dynamics Second Quarter 2025 Earnings Conference Call. I'm Cary Savas, Director of Branding and Communications. Joining us on the call today are CEO Leonard Livschitz, CFO Anil Doradla, CTO Eugene Steinberg, COO Yury Gryzlov, and SVP Americas Vasily Sizov. Following the prepared remarks, we will open the call to your questions. Please note that today's conference call is being recorded. Before we begin, I would like to remind everyone that today's discussion will contain forward-looking statements. This includes our business and financial outlook and the answers to some of your questions. Such statements are subject to the risks and uncertainties as described in the company's earnings release and other filings with the SEC. During this call, we will discuss certain non-GAAP measures of our performance. GAAP to non-GAAP financial reconciliations and supplemental financial information are provided in the earnings press release and the 8-K filed with the SEC. You can find all the information I just described in the Investor Relations section of our website. I'll now turn the call over to Leonard, our CEO.

Thank you, Cary. Good afternoon, everyone, and thank you for joining us today. I'm delighted to report another record quarter in revenue. Our second quarter revenue of $101 million was another all-time high, driven by the continued growth in our engineering billing headcount. More importantly, we're witnessing a strong pipeline of opportunities across industry verticals. I will talk more about it in my prepared remarks. Grid Dynamics is aligning every aspect of its business with an AI-first approach. This includes infusing AI into go-to-market strategies, service offerings, delivery, and talent management. We're doing that while preserving and expanding our core assets around high-caliber technology, consulting and engineering services. While traditional programs face increased scrutiny, innovation-centric initiatives are being prioritized from a spending perspective. Enterprises are actively seeking AI-native partners capable of driving and leading adoption within the enterprise environment. Furthermore, traditional functional structures within large enterprises are often lacking the adaptability needed for efficient cross-functional decision-making regarding AI implementations encompassing both technology and business aspects. This is precisely where Grid Dynamics plays a crucial role, empowering organizations to accelerate AI adoption at enterprise scale. I'm happy to report that in the first half of 2025, AI and Data was 23% of the company's overall organic growth. The AI and Data practice is growing almost 3 times faster than our overall organic business. I'm excited to see the growth in the pipeline of opportunities as we enter the quarter with accelerated business momentum. This is the basis for our positive business outlook, even though macroeconomic uncertainties persist. I'm also pleased to report on the progress with our recent acquisitions. JUXT has significantly elevated our industry expertise in banking and financial services, attracting considerable interest from global banking based in the United States. In the second quarter, a U.S.-based global bank continued to be a top 10 customer. And that was the reason the financial services vertical remained our second largest. Mobile Computing has enhanced our follow-the-sun capabilities and talent acquisition efforts, successfully integrating engineering teams to support our U.S. enterprise accounts. Our partnership-influenced revenues reached 17.9% of the total revenue in Q2 2025, and we continue to experience increased traction with all hyperscalers, notably only with Google. In our European business, we begin implementing a modular B2B digital search solution built on Microsoft Azure for one of the largest worldwide brewing companies. We also have launched AI expert agents at a Tier 1 investment bank to perform in-depth code quality and security reviews as a part of the software development life cycle. Our India expansion continues to be a strategic highlight. India is now among our top two countries by headcount and has emerged as a hub for multi-agent, multi-modal platform engineering, demonstrating a strong talent attraction and upskilling. Our internship program also saw strong momentum with over 16,000 applicants and high placement rates into billable roles. Across the majority of our customers, there is a profound impact of AI on the way they are planning their future initiatives and programs. Customers now expect a flavoring of AI across all their service offerings, even traditional ones. We firmly believe the workforce pyramid of the IT industry space is shifting towards our senior talent and AI-centric agents. As you know, Grid Dynamics' workforce pyramid is more weighted towards senior, more experienced engineers in comparison to our peers in the IT industry. Our alignment in the workforce, along with the technology-centric DNA, positions us well as enterprises embrace AI. Given the critical role of AI, I would like to emphasize Grid Dynamics' unique market position. It's important for investors to remember that our company's core values are built upon a strong foundation in data and data platforms as well as expertise in large-scale data engineering for Fortune 1000 enterprises. I will now turn the call over to Eugene Steinberg, our CTO, to elaborate on the important topic of AI, Eugene?

Thank you, Leonard. Good afternoon, everyone. I'm delighted to share how Grid Dynamics is actively retooling for an AI-first future, where AI capabilities are embedded in every aspect of our operations and service delivery from the ground up rather than added as an afterthought. We are methodically building on a strong foundation of a decade of data and AI experience. We are expanding our key AI capabilities and strategic partnerships. We are delivering production-ready solutions with proven ROI for enterprise clients. We are innovating with major customers and building considerable experience across Agentic AI platforms and solutions and an AI-first Software Delivery Lifecycle. The investments we made are yielding positive results, many of which I'll discuss today. Grid Dynamics's whole AI framework is based on 4 foundational pillars. Let me walk you through each. First, AI-powered business transformation. We are delivering immediate and measurable impacts from our engagements in the areas of customer engagement, enterprise operations and manufacturing. Conversational commerce is redefining customer engagement by driving hyper-personalized customer experiences. Our search solutions have become a key entry point for many new client relationships in retail and CPG industries. From there, we often expand to build conversational commerce capabilities. Our efforts routinely yield conversion improvements of over 5%. This success leads to follow-on engagements that average 2 to 3 times the initial project value as clients expand AI adoption across additional business units. We have specialized domain solutions for many sub-verticals that have been particularly differentiating. Take auto-parts search, for example. Our fitted auto-parts search capabilities have established Grid Dynamics as a preferred partner for most leading auto-parts retailers. With over 150 AI search specialists deployed across customer projects, we are demonstrating our ability to grow with existing accounts while delivering measurable business impact. Agentic AI has significantly enhanced efficiency for a major financial services company by automating intelligent processes that facilitate data-driven decisions. Previously, the cost of covering the vast number of Tier 3 customers was prohibitive for digital sales. Our B2B customer 360 agent now conducts exhaustive research, aggregating client data from diverse sources such as CRM, contract databases and spreadsheets. These detailed profiles integrate automated risk alerts, AI-powered insights and intelligent recommendations informed by prior interactions, ultimately leading to improved customer retention and business growth. This initiative is expected to free up about 20% of seller capacity, allowing for a high-touch approach with more clients and accelerated time to revenue. Within the manufacturing sector, we implemented the remaining useful life prediction system for a leading industrial equipment manufacturer, which enhances maintenance planning and reduces unplanned downtime. We have also delivered facility modeling with G-code generation for a global technology company, optimizing manufacturing processes and improving production efficiency. The rise of physical AI is fundamentally transforming the industrial robotics landscape, leading to the replacement of legacy robotic platforms with modern AI-enabled solutions. We collaborate with innovative platform providers such as Wandelbots, enhancing their offerings with advanced AI components for inspection, welding and precision manufacturing applications. This represents a new and promising revenue stream for our company. Second, AI and agentic platforms. We partner with large enterprises to develop in-house bespoke agentic AI platforms. For instance, we are collaborating with a leading global payment technology company and a multinational beverage giant to construct comprehensive AI platforms. These platforms empower our clients to create a full spectrum of AI agents both low-code and high-code within a secure, scalable environment. They offer an expanding ecosystem of tools for agents to access enterprise data and systems. This platform-first strategy enables us to see substantial expansion opportunities by building AI solutions atop of the platforms we develop. Third, AI-first SDLC. As enterprises embrace AI-first mentality, the entire approach to the software development life cycle is shifting. Last month, we introduced our proprietary AI-centric Grid Dynamics AI-Native or GAIN engagement model, and we're driving strong adoption of AI-first SDLC methodologies across the dynamics. What is particularly exciting is that this enables our expansion into previously inaccessible market segments. Labor-intensive legacy modernization projects that additionally require large volume of relatively low-skilled labor are now within our reach. This represents a significant market expansion opportunity as we can now compete for projects that were previously economically unfeasible. For example, we are migrating 16,000 data processing jobs for a global technology leader using a small specialized team equipped with AI-first SDLC tooling. AI-first SDLC has dramatically improved our presales and client acquisition. We now create high-quality proof of concepts and prototypes in hours, not weeks, significantly boosting conversion rates and shortening sales cycles. For example, when a leading specialty pet retailer requested a computer digital solution to automate fish counting in aquariums, previously requiring manual fish transfer between tanks, our AI-first development team delivered a working prototype the next day. And finally, fourth, Grid Dynamics process efficiency. Beyond client-facing applications, we are leveraging AI to transform our internal operations. Our in-house Agentic AI platform is transforming and automating every aspect of our operations, including knowledge management, talent sourcing, project management, contract reviews and HR functions. AI is fundamental to driving our client business forward. Our continued commitment to the AI-first future is unwavering, and I am excited about the road ahead. I will now turn the call over to Vasily Sizov, our SVP of Americas, to discuss some notable project highlights from the quarter.

Thank you, Eugene. Good afternoon, everyone. I am pleased to highlight some important accomplishments from the quarter that illustrate the value of our work. For a leading global technology company, we modernized their data processing infrastructure by migrating Spark and Scala workflows from a legacy scheduling system to a next-generation cloud platform. We developed a comprehensive data validation framework to ensure data consistency, optimize compute resource usage and created reusable templates that accelerate future migrations to containerized environments. This initiative significantly improves platform stability and performance, reduced operational risks and established the foundation for scalable, efficient development of future data-driven capabilities. Another example, we partnered with a leading multinational technology company to develop hermetic C++ toolchains for their ML portfolio. This foundational initiative established a highly reproducible, reliable and efficient C++ build environment across their machine learning programs. Our team led the strategic architectural shift to a fully hermetic C++ build system, delivering a tenfold improvement in build reliability, a 25% reduction in operational costs, and significant developer velocity gains for complex CPU and GPU accelerated workloads. We are developing an AI platform for a leading home improvement retailer, serving as the foundation for generative AI tools that assist customers with how-to guidance and product inquiries already in production. This virtual assistant offers project inspiration, design concepts, product comparisons and expert recommendations for both do-it-yourself and professional users. The solution is expected to drive significant improvements in conversion rates and average order value, particularly in maintenance and repair and aesthetic upgrades. For one of the top fintech companies, we developed a spectrum of AI initiatives to showcase advancements across domains. A multi-agent marketplace validates temporal as a scalable execution platform for complex multi-agent interactions, offering robust observability and reliability. The travel desk agent creates stateful agents with advanced memory components that generates personalized long-term itineraries overcoming context limitations through self-task execution. Another AI-based solution leverages public reviews to accurately categorize miscoded merchants, identifying system misuse and potentially increasing revenue through corrected interchange fees. Thank you. With that, let me turn the call to Anil, who will talk about our financials.

Thanks, Vasily. Good afternoon, everyone. We recorded the second quarter revenue of $101.1 million, slightly higher than the midpoint of our $100 million to $102 million guidance. On a year-over-year basis, this represents a growth of 21.7%. Excluding the impact of our recent acquisitions, the year-over-year growth was 6.3%. Both on a quarter-over-quarter and year-over-year basis, there were roughly 73 basis points and 40 basis points of FX-related tailwinds, respectively. Non-GAAP EBITDA came in at $12.7 million, within our guidance range of $12.5 million to $13.5 million. In the second quarter of 2025, negative impacts on our costs from FX fluctuations both on a quarterly and year-over-year basis. As you know, over the past months, the U.S. dollar has weakened against most currencies. Grid Dynamics is exposed to a currency basket across Europe, Latin America and India. We have a natural hedge against some of these currencies and the net impact of it was approximately $1.4 million. Looking at the performance of our verticals, retail remained our largest vertical, contributing 29.2% of total revenues for the second quarter of 2025. Revenues in this vertical grew 10.4% year-over-year, primarily driven by demand from our existing specialty retail customers and new customer engagements. On a sequential basis, however, revenues declined by 6.2%, largely from home improvement customers. The finance vertical accounted for 25.1% of total revenues in the quarter and remained our second largest vertical. Revenues grew 1.4% sequentially and doubled year-over-year. The substantial year-over-year growth was primarily driven by increased demand from our fintech customers, a lot of which contributed to our 2024 acquisitions that brought in global banking customers. TMT accounted for 24.9% of total revenues for the quarter, with a growth of 6.7% quarter-over-quarter and 8.4% compared to the same period last year. The largest growth driver was increased demand from our technology customers. Turning to the remaining verticals, CPG and manufacturing represented 10.5% of quarterly revenues while revenues remained flat in absolute value sequentially, but increased 7.7% year-over-year, primarily due to contributions from our recent acquisition. Other verticals contributed 7.8% of total revenues, reflecting sequential growth of 10.1% and a 4.6% increase compared to the second quarter of 2024. The year-on-year increase primarily came from customers tied to agriculture, marketplace and service provider subverticals. And finally, the healthcare and pharma made up 2.5% of our revenues for the quarter. We ended the second quarter with a total headcount of 5,013, up from 4,926 employees in the first quarter 2025 and up from 3,961 in the second quarter of 2024. At the end of the second quarter of 2025, our total U.S. headcount was 359 or 7.2% of the company's total headcount versus 8.8% in the year-ago quarter. Our non-U.S. headcount located in Europe, Americas and India was 4,654 or 92.8%. In the second quarter, revenues from our top 5 and top 10 customers were 37.5% and 57.3%, respectively, versus 38.5% and 57% in the same period a year ago. During the second quarter, we had a total of 194 customers down from 204 in the first quarter of 2025 and 208 in the year-ago quarter. The decline in the number of customers was primarily driven by our continued efforts to rationalize our portfolio of nonstrategic customers. Moving to the income statement, our GAAP gross profit during the quarter was $34.5 million, or 34.1% compared to $37 million or 36.8% in the first quarter of 2025 and $29.6 million or 35.6% in the year-ago quarter. On a non-GAAP basis, our gross profit was $35.1 million or 34.7% compared to $37.6 million or 37.4% in the first quarter of 2025, and up from $30.1 million or 36.2% in the year-ago quarter. On a sequential basis, the decline in the gross margin was largely from FX headwinds, increased engineering headcount to support future growth and timing of costs related to some fixed-price contracts. Non-GAAP EBITDA during the second quarter excluding interest income, expense provision from income taxes, depreciation and amortization, stock-based compensation, restructuring, expenses related to geographic reorganization and transaction and other related costs was $12.7 million or 12.6% of revenues, down from $14.6 million or 14.5% of revenues in the first quarter 2025 and up from $11.7 million or 14.1% in the year-ago quarter. The sequential decline in EBITDA was largely due to the decline in gross profit and FX segments. The increase on a year-over-year basis was largely due to higher revenues, partially offset by an increase in operating expenses and FX fluctuations. Our GAAP net income in the second quarter was $5.3 million or $0.06 per share based on a diluted share count of 86.4 million shares compared to the first quarter net income of $2.9 million or $0.03 per share based on a diluted share count of 87.8 million and a net loss of $0.8 million or $0.01 per share based on 76.6 million diluted shares in the year-ago quarter. On a non-GAAP basis, in the second quarter, our non-GAAP net income was $8.3 million or $0.10 per share based on 86.4 million diluted shares compared to the first quarter non-GAAP net income of $10 million or $0.11 per share based on 87.8 million diluted shares and $8.5 million or $0.11 per share based on 77.9 million diluted shares in the year-ago quarter. On June 30, 2025, our cash and cash equivalents totaled $336.8 million, up from $325.5 million on March 31, 2025. Now coming to the guidance, over the past couple of quarters, the majority of our enterprise clients across industry verticals have taken a certain degree of caution with traditional digital transformation spending. This is something we've seen across our customer base. That said, innovation-led projects are client priorities from a spending point of view and Grid Dynamics has been one of the key beneficiaries of this trend. Coming to the third quarter guidance, we expect revenues to be in the range of $103 million to $105 million. We expect our recent acquisitions to contribute approximately 12% of the revenues. We expect our third quarter non-GAAP EBITDA to be in the range of $12 million to $13 million. For the third quarter of 2025, we expect basic share count to be in the range of 84 million to 85 million and our diluted share count to be in the range of 87 million to 89 million. We are maintaining our full year revenue outlook of $415 million to $435 million, all of this despite an estimated low double-digit annual percentage reduction in revenue from cautionary spending on traditional business, which we projected early in the year and which was affected by uncertainty with the macro environment. In spite of these events, we continue winning innovation-led projects and growing overall revenue. As Leonard pointed out, roughly 23% of our business is tied to AI and data. This momentum around AI business is growing, and we expect this to be higher in the quarters to come. That concludes my prepared remarks. We are ready to take questions.

Thank you, Anil. First up is Mayank Tandon of Needham.

I wanted to focus a little more on the pipeline and the pace of deal conversion. Could you discuss, as you consider the guidance for the remainder of the year, how much of the revenue you estimate is secured under contract? Additionally, how much do you still need to pursue? Please share your confidence level regarding reaching your guidance range.

So maybe, Leonard, if you want, I can kick off and then we can add. Yes. So Mayank, look, last quarter, there was this question, when we talked about $415 million to $435 million. And what we talked about is when you look at the low end of our guidance, that will be reached by some of the working time benefits that we see. And we still maintain that. There is obviously organic growth. So if you look at the low end of our guidance, for example, if you model something to the effect of high single digits for the full year in organic growth and we maintain this momentum of about 12% from our acquisitions, that gets you to the low end of the guidance, which is a good place to be. Now we also said that there are two things that are happening. There are other new pipeline business, which I'm sure Leonard and the team will talk about, but there are other opportunities that are there. As you go from the low end of the guidance to the high end of the guidance, obviously, there is a little bit more on expectations on the acquisitions. So with that, I'll pass it on.

Should I continue? Or...

Yes, yes, go ahead, continue on.

Okay. I guess my follow-up question would be around just some of the key underlying drivers of the model. So how should we think about the pricing climate? How much more leverage do you have on utilization and what are your hiring plans just given some of the demand trends you talked about? So if you could just touch on those three metrics, that would be helpful from a modeling standpoint.

Let me address this since Anil is not present. First, regarding your question about the pipeline, it's quite strong, though we maintain a cautious outlook. After our last earnings call, we experienced some unexpected macroeconomic impacts, despite achieving solid quarterly results. The pipeline generated in Q2 is very promising. Looking ahead, the July numbers appear positive, but I prefer not to make any assumptions too soon. We are optimistic about the second half of the year, especially due to the rapid growth in projects related to data and AI platforms, which are significantly outpacing regular business. Most clients are engaging in substantial projects, not just proofs of concept. Some hyperscalers are also supporting us in this area. As for the balance of secured business versus what remains to be pursued, Anil mentioned the challenges in moving from the lower end to the midrange, which will require effort. We anticipate a clearer picture by the end of the quarter, but currently, we are hopeful about securing new large deals. Now, regarding your second question about pricing structures, there are several factors to consider. When we engage in innovative technology projects, pricing is generally favorable as clients aim to enhance their internal value and reduce costs. There's a competitive environment for talent, and Grid Dynamics is well-positioned to capitalize on this. However, in traditional business, we face increased pressure from clients to scale with Grid Dynamics, especially in India, where pricing structures differ. Our headcount continues to grow but is now more in line with our global operations rather than previously being dominated by European engineering. Our global follow-the-sun model allows us to sign deals in various regions, including Europe and Latin America, each with its unique pricing approach. Overall, it’s complex to establish a common pricing strategy across all these factors, but the trajectory looks good. We've successfully completed most negotiations for this year and will soon begin talks for 2026. With the U.S. dollar weakening, we can no longer solely rely on time and materials for European engineering. Instead, we are shifting towards fixed bids and solution-based projects, which enhances our growth prospects. In summary, we are heavily focused on expanding our AI and data-related business, and we're in a strong position with our technological capabilities. If you need further clarification, I'm happy to elaborate more.

Next up is Puneet Jain of JPMorgan.

I wanted to ask about how AI is impacting the nature of work, particularly in the traditional software development lifecycle. Can you discuss the need for training or hiring employees differently? It seems that having a highly experienced workforce could be advantageous, but I'm interested in your views on how you might need to adjust your hiring or training approaches as you prepare Grid Dynamics for these changes in the traditional SDLC.

Yes. Thank you, Puneet. Great question. And this is not something which we started to do just today; we started to do it quite some time ago preparing for an AI-first future. And as we already said, we've always been a little bit of hiring on our talent, making a strong preference to the more senior, more capable, more, I would say, broad-view engineers. And in the new AI-first software development lifecycle, the engineers who are working on the actual projects supported by the AI agents, which are actually writing code and making modifications to the code base, they are acting as the judges. Their deep experience as engineers helps to determine whenever the suggestions which are made by their agent is a good or bad suggestion. And this is where we see a lot of value, which is coming from more senior engineers. And at the same time, we invested quite a bit into AI-native engineers who've grown with those AI agents from the very beginning of their careers, and they very natively are coming out of our internship, already armed with the understanding of those solutions. Our platform, which we are developing right now, which we call GAIN, it's a combination of technology. It's not only about coding; it's all through the whole cycle of development, starting from requirement understanding and gathering and ending with deployment and testing of the solution in production. It's all supported by the different kinds of AI agents. Engineers, senior engineers and AI engineers are supervising those agents and correcting them and guiding them through this process. And of course, our review training program is preparing those engineers with like, we traditionally said prompt engineering, but right now, it's more like context engineering, a little bit new term in the industry, which everybody is using, to help those agents to be successful and to drive on further. So that's a shorter vision.

No, that's great, like context engineering. We've been hearing that term a lot these days. No, I appreciate the response. And obviously, from an investor standpoint, we take a lot of questions on the reasons for slower growth in broader IT services, whether it's macro, whether it's AI. Let me ask that question this way: you have, say, verticals, say, for example, financial services, which has been doing great, and then verticals like retail, healthcare, CPG, not as great. So are there any differences in AI adoption across these verticals? Or would you say that growth difference across those verticals is purely a function of macro or sector-specific challenges?

So Puneet, I'll let other people talk about more specifically. I think it's a very fundamental question. There's no slowdown on AI adoption across all the verticals. What happened is in certain verticals, we're gaining momentum because the existing business, the traditional business, the cloud migration, and new platforms and software development continue to expand while they adopt AI. The AI platform, we have our own homegrown platform, we use our partnerships. There's a lot of stuff that's going on. We even started getting some press from our participation in the adoption of physical AI. So we're really at the cutting edge of all this technology. There are some other verticals where the traditional business has been somewhat muted. And obviously, because the retail and CPG was a substantial part of our business, there are some traditional large legacy businesses which have participation in brick and mortar - not mentioning all these promotions around the tariff strategies. They are slowing down on traditional software development, infrastructure and expenses. They continue to invest into AI front. But if you noticed, Anil brought in some flavor talking about what could have been if that business would be slowed down; it will be way above the upper range of the guidance. But it wasn't. And what we see right now is the redeployment of resources into a more traditional conservative field, in which the, I would say, potential expansion is a little bit limited, where other, more aggressive expansion combined with the traditional spending in other industries. So the bottom line conclusion, AI growth supports very dynamic growth wholeheartedly. We have more than one platform. We have an internal platform, we have external, we participate in many activities which actually pay decent dollars. But that's muted current business in some of the more traditional areas started dragging a little bit down and is driven by those macros.

Next up is Brian Bergin of TD Cowen.

I wanted to ask on the AI-powered engagement model. Can you talk about the early client testing and reception to that model? And how are you thinking about how fast this ultimately gets adopted in your business? So what I'm specifically curious about is as it gets adopted by more, what's the impact going to be on the financial profile of the business as we think about growth and gross margin?

All right. Maybe let me address these questions. Thank you, Bryan, for the question. So I would say first that we definitely see increasing demand for new types of engagements and AI-powered engagements. So this definitely should fuel future growth. So that's the first statement. As for the particularly GAIN implementation, so as Eugene mentioned, it's a very comprehensive, I would say, holistic approach on how you approach the software development lifecycle by embracing those processes, technical tools, team composition and also the new commercial model. As a matter of fact, right now, we already apply certain aspects of this new platform at selected customers. Primarily the easiest thing for us is basically to bring this platform and processes into fixed-price engagements, which basically doesn't require the customer to rethink the VMO process on how they engage us. So from that perspective, we already see benefits by reducing primarily the timelines, which allows us to be more competitive also on the pricing side. As for the full-fledged GAIN implementation, including the commercial, we are in the phase of fine-tuning this whole model because it's truly an innovative thing. So VMOs are not ready yet, it will be a learning curve for them and it will be a learning experience for us to fine-tune that. But the good thing is that we are talking to actually, two out of our top 15 customers right now about starting piloting this model as soon as we make the process as smooth as possible to go into production.

Margin portion, Bryan. I think what Vasily is - Vasily is kind of a foundational father of the model and running Americas, gives him a bit of an upper hand with others. And when I was in Chicago at the conference, first time I briefly mentioned the ideas and turns out obviously we're not alone, but what's important is the proof is in the pudding. How much business we generate but what's more important, how beneficial it becomes to the client and Grid Dynamics. I would not talk about directly gross margin. I would refer to the profit margin as we grow. And you can really translate it back because it includes the partial ownership of the people, the platforms are proving the conceptual business basically become a technology consultant to the client, understanding their business flavor of those verticals. So we're trying to prove very interesting points which you guys have been torturing us from the beginning of AI. Well, the engineers will disappear and how the new world is going to work. What is going to do to us, and this is going to be very important, if we scale this program properly, it will substantially increase revenue per person. And why would it be is because we can use our top talent, which is growing, but obviously never enough. I mean, you see some of the notable big companies growing with 8-digit, 9-digit numbers, into the people. Now for us, since they have such a good pyramid going up, we force the clients to think what's important to them. And what's important to them is not only individual talent but having a partnership with Grid Dynamics which makes measurable results. And those two clients, which Vasily mentioned, they are far along the way. And the reason they realize why it's important is because the pace of innovation substantially increases for the time and surpass their ability internally to conceptualize the business. So we're innovating, deploying and analyzing business at the same time. And the key point of that today, actually, if you look at the crux of the GAIN offering and value is the data platforms because without a reliable and logical dedicated data platform on the client side, the business will be risky because the conversion may not be as valuable for the business. So I would look at the revenue per person as we scale our company rather than fuel the margin, which obviously will be addressed by increasing margin as well.

Okay, that makes sense. I want to follow up on the near-term margin and the understanding that demand is inconsistent. You've increased headcount again, so how are you balancing the need for quality talent in preparation for a recovery while also considering investments in nonbillable R&D versus optimizing the cost structure? Can you discuss that dynamic in the near term, particularly regarding 2025?

I'm laughing, Bryan, because this is exactly what we're doing every day right now. It's quite interesting what we have going on within the company. There are two key areas I'm focusing on. First, as you've mentioned, we need to maintain a certain level of financial discipline in the short term to ensure, as a public company, we are meeting our responsibilities. The second priority, as Leonard has directed, is to increase our investments in future technologies, platforms, and personnel. So, it's a balancing act for me. We are creating specialized teams that focus on specific technologies, whether that's related to hyperscalers or AI-specific projects. We have developed internal platforms, and there’s a lot of work happening on the tools we are building for AI. At the same time, we're closely examining our traditional business side to ensure we're being more cost-optimized. This balancing approach is reflected in the increased costs I've seen from Q2 to Q3 due to investments in engineering talent.

So Bryan, let me be very blunt because Anil was trying to be a little bit elusive. This is my absolute concrete determination: we will need to be the top leaders in AI implementation offering to the clients. I know as Anil mentioned about a company needing to do a certain cleanup, and we're doing the cleanup. But we're doing the cleanup only to open up more capabilities. As far as I'm concerned, as you know, how Grid Dynamics' stock has deteriorated for whatever reason you guys decided to, so to me, it's like, I don't want to go back to where I was 3 months ago. I want to go 5 times more than I was 3 months ago. And the reason being is the value we're going to add to the system is going to be disproportional to everything we've done until the digital transformation with the cloud migration and public clouds took off. And we're actively participating by co-developing the key products with our major partners. So to answer your question, we will do the housekeeping, and Anil will have to make sure that we don't do it randomly. But I have a hugely aligned strategy with the technology organization. The development of the delivery capabilities, following the sun, we have here on the table, next time we'll hear also from some Indian representative, Rajeev was there. But we have Yuri and Vasily to make sure that in the U.S. and Europe, we're going to have a bespoke application AI platform. And as of today, we won a major program actually in LatAm as well. So you will not hear from me for a quarter or two that we're going to be cautious. We're going to be aggressive, intelligent; Anil will hold us back when things have become a little bit newer but the way how we've been doing it for the last 18 months, even going through the Liberation Day and all the other macro parts and run through ups and downs, it would not deflect our determination in modern AI, Agentic AI, physical AI, and the solution practices; we're going to be at the leadership goal.

Next up is Maggie Nolan of William Blair.

This is Matt on for Maggie. Congrats on the quarter. I wanted to ask about the partner program and the impressive growth there. What's your outlook for partner growth into the second half of the year? Can that continue to accelerate? And I guess where are you seeing the most new traction today amongst partners outside of Google and the hyperscalers? Or is it primarily those hypers?

All right. You brought up a key point, Matt. My agenda for the next quarter involves updating you on our global partnerships and providing specific details about our partnership program. Currently, Grid Dynamics is focused on innovation, customer partnerships, and broadly distributing the GAIN model through AI technology, internal platforms, and scaling partnerships. To address your question about what exists beyond the hyperscalers, it's important to note that hyperscalers are no longer just competing for cloud platform spending. They are actively integrating the platforms they have developed with the AI tools they offer. Additionally, we are partnering with major players that provide foundational capabilities, such as NVIDIA, because scaling requires more than just physical infrastructure. We are also collaborating with robotics companies to drive significant changes in industrialization, which is a critical focus. We are developing agent tools and factories in cooperation with our clients and their teams, as well as third parties that offer AI tools. We shouldn’t overlook the innovative ideas emerging from numerous newly established AI startups, some of which have received significant funding beyond where Grid Dynamics currently stands. Our job, and specifically Eugene's role among others, is to identify those with real potential. While I appreciate the VC world and the funding available, we need to choose the winners carefully. In summary, we see three avenues for growth: hyperscalers transitioning into new models, large players developing their own models, and engaging with our customers. We are collaborating with partners and supporting their initiatives, and on top of that, there is a rapid expansion in industrialization driven by physical AI.

I want to highlight that from a European perspective, we are seeing traction with traditional hyperscalers, particularly with Google. Although we may be a bit behind the U.S., the momentum is definitely there. This growth is connected to our core search capabilities and collaboration as well as with the Agentic AI platforms. This is a significant part of our current efforts. Additionally, Anil has shared the revenue figures we received from our partnerships.

Great color. Can I follow-up with a question on client count? I think obviously declined quarter-over-quarter and year-over-year, I think, primarily due to the rationalization of your portfolio. How long is that going to take Anil? And when do you expect we can see stabilization in that line item?

So Matt, very good question. If you see over a pattern of several quarters, this has been kind of marginally going down. So if you look at it, there are a couple of parts to it. The first part is that most of the decline comes from our acquisition-related clients. We've had 6 acquisitions in the past several years. And many of them have smaller clients. And our whole focus is to look at the world through the lens of whether they are an enterprise customer or commercial customers. Our focus tends to be more on the enterprise, which is where we manage the program. We have more focus, whereas the commercial side of it could be just a cost-plus as we had through some of our acquisitions or some of the smaller ones. So at this stage, what we do is that as those projects roll off, many at times, we don't invest back in; there are some cases from quarter-to-quarter, some of our enterprise customers are also falling off, but that's not a very big portion of it. And we do have a little bit of a flavor of when we come through the partnerships. There are some clients that try out, work with us through the hyperscalers, and there's a little bit of an infant mortality there, as they're pausing into the next round. So the way we define, we have a little bit of a structured approach towards defining what a client is: if I do not get a dollar revenue in the quarter, I just don't call them a client. Although there might be an MSA, there might be something out there. And within the 12-week month period, if they come back again, they're not a new client. So we have a little bit of a strict approach towards this. So I think you will continue to see some of these things. At the end of the day, we can look at our top 30, top 40 customers that are going to draw most of the value. Some of these smaller clients over time have come in the top 30 for us, but do expect at least in the near term, to see a trend like that.

Let me conclude by emphasizing an important message. As you look at Grid Dynamics, we believe that the implementation of AI in various forms will be central to our business. There is significant value in the right combination of platforms and service providers, especially in traditional service consulting with a strong technological focus. As Bryan mentioned, it's crucial to manage utilization effectively. We have assessed some of our less critical clients and decided not to invest in those relationships because we believe they lack the potential to become viable players in the near future. This doesn't mean we will cut ties with them entirely, but if they don't align with the new AI landscape, our team may prioritize other clients. Consequently, you will witness exceptional growth among certain clients due to a strong alignment of goals, while others may either stagnate or gradually decrease as we move forward.

Next up is Surinder Thind of Jefferies.

Big picture question here. As you look forward to all of the changes that you guys are making, the transformations, what is the scenario that you're actually solving for? Meaning what is the level of AI capability? Are you planning for a scenario where 50% of software development, 75% is done by AI? Like what are the kind of the framework of what you're moving towards?

Software development is just one aspect of AI. For instance, it's important to consider the changing environment because alterations need to happen quickly. If you're addressing an issue at point X, by the time you reach the goal at point Y, you will encounter continuous changes. How are you planning for the evolution of the company over the next 3 to 5 years? The evolution will take more than three quarters. It involves a combination of technology adoption, the capabilities of distributed systems, and the ability to generate value in each specific case. The percentages like 50%, 30%, or 80% mentioned in software development are just arbitrary figures and represent a small portion of the overall change. The focus should be on creating business value and improving output quality. I believe the human element will remain crucial in key decision-making, albeit in different forms. Writing code will always be important, and Eugene can elaborate on that. We need to understand system deployment, ensure compatibility, and manage security to control future system expansions, and each of these aspects must be addressed individually. It will take significantly less than 50% on a basic coding level, with a considerably larger portion related to co-development. As we monitor and enhance our capabilities, the progression will take longer than what some might expect for instant transformations. The trained individuals will need to define future paths; otherwise, we risk chasing a moving target, which can lead to investments in outdated solutions within six months. To summarize, on a coding level, it's going to exceed 50%. For system management, integration, and data compliance, it will be less, but the impact needs to be validated. In the analytical side of systems, it will always require a blend of people and projects. Also, while some tasks may be entirely handled by agents, the overall implementation percentage would be lower. This serves as a good transition for Eugene to share his insights based on his experience.

Yes, I understand that there are many examples online of quickly creating a full-fledged Facebook clone. However, anyone who has worked on production projects knows that building a prototype and launching something that can handle real-world demands for critical systems is very different. In our business, I'm responsible for presales, which has been entirely transformed by AI-first development. We can quickly produce excellent prototypes and pilots for our customers. But when we move to the actual implementation of scalable systems under load in a secure environment with the necessary deployment and scaling requirements for production, it's a completely different challenge. Even the most advanced AI agents can lose their effectiveness quickly and often need significant human oversight and thoughtful design to guide them. They may be intelligent but lack direction, which is why we continue to rely on human involvement.

Eugene, you opened the Pandora's box. This is our strive for excellence.

We had multiple conversations on the topic. And 1 color I wanted to add is that AI has different flavors that are in different stages of adoption because things like, for example, co-pilot, when still an engineer writes code, but AI suggests things, it will be widely adopted. Maybe if it's not 100%, maybe 95% or whatever, it's more kind of dependent actually on the security protocol within the customer, whether they want to be exposed to external LLMs. But this thing is, like it's a done. So what Eugene was and Leonard was talking about is more of agent-based AI coding, and that's kind of the more complex topic, which will hash through the adoption curve for sure.

Ladies and gentlemen, this concludes the Q&A session of our call today. I will now turn it over to Leonard Livschitz for closing comments.

As we conclude our second quarter earnings call, I want to leave you with 3 key takeaways. Number one, Grid Dynamics AI-first strategy is driving our growth. The AI and data initiatives now account for a quarter of organic revenue in the first half of 2025 growing nearly 3 times faster than our overall organic business. Number two, AI is fundamental to driving our clients' business forward. Enterprises are seeking AI-native partners with the expertise to lead AI adoption at scale. This is Grid Dynamics' strength. Our expanded pipeline aligns with enterprise investments. And finally, Grid Dynamics is built for sustained differentiation. We have a proven track record of emerging stronger through industry transitions. Based on reaccelerating client demand, we are confident in our outlook and our ability to empower Fortune 1000 enterprises in their AI journey. We're excited about the path ahead and the value we're creating. I look forward to giving you an update on the next earnings call.