Grid Dynamics Holdings, Inc.

At this time, our participants are in listen-only mode. Joining us on the call today are CEO Leonard Lifshitz, CFO Anil Dharadla, CTO Eugene Steinberg, COO Yuri Grislov, 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 in a financial outlook and the answers to some of your questions. Such statements are subject to the risks and uncertainty 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 now turn the call over to Leonard, our CEO.

Thank you, Kerry. 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 building 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 offering, delivery, and talent management. We're doing that while preserving and expanding our core essence 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 structure 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 Green Dynamics plays a crucial role empowering organizations to accelerate AI adoption and 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 revenue. The AI and data practice is growing almost three times faster than our overall organic business. I'm excited to see the growth in pipeline of opportunities as we enter the quarter with accelerated business momentum. This is the basis for our positive business outlook, even though microeconomic uncertainties persist. I am also pleased to report on the progress with our recent acquisitions. JAXT 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-ten customer, and that was the reason the financial services vertical remained our second largest. Mobile computing has enhanced our follow-the-sum capabilities and telequisition effort, successfully integrating engineering teams to support our U.S. enterprise accounts. Our partnership influence revenues reached 17.9% of the total revenue in Q2 2025. And we continue to experience increased traction with all hyperscalers, notably with Google. In our European business, we begin implementing a module 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 lifecycle. Our India expansion continues to be a strategic highlight. India is now among our two top countries by the headcount. and has emerged as a hub for multi-agent, multi-model platform engineering, demonstrating strong talent attraction and upskilling. Our internship program also saw strong momentum with over 16,000 applicants and high placement rates into the 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 of their service offerings, even traditional ones. We firmly believe the workforce pyramid of the IT industry space is shifting towards senior talent and AI-centric agents. As you know, Green 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 into 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 AI-first software delivery lifecycle. The investments we made are yielding positive results, many of which I'll discuss today. Grid Dynamics whole AI framework is based on four 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 engagements 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 2-3x 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 within existing accounts while delivering measurable business impacts. Adjantic AI significantly enhanced efficiency for a major financial services company by automating intelligent processes and facilitating 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 a 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 Vandalbots, 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 seize substantial expansion opportunities by building AI solutions on top of the platforms we develop. Third, AI-first SDLC. As enterprises embrace AI-first mentality, the entire approach to the software development lifecycle, SDLC, is shifting. Last month, we introduced our proprietary AI-centric Grid Dynamics AI Native, or GAIN, engagement model, and we are driving strong adoption of AI-first SDLC methodologies across Grid Dynamics. What is particularly exciting is that this enables our expansion into previously unaccessible market segment. Labor-intensive legacy modernization projects that traditionally required 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 pre-sales 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 vision 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 complications, we are leveraging AI to transform our own 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 continuous 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, optimized compute resource usage, and created reusable templates that accelerate future migrations to containerized environments. This initiative significantly improved 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 improvements 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 DIY 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. A travel desk agent creates stateful agents with advanced memory components that generate personalized long-term itineraries overcoming context limitations through subtask 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, Vasili. 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 bps and 40 bps of FX related tailwinds, respectively. Non-GAAP EBITDA came in at 12.7 million within our guidance range of 12.5 to 13.5 million. In the second quarter of 2025, negative impacts on our cause from FX fluctuations, both on a quarterly and year-over-year basis. As you know, over the past months, the US dollar has weakened against most of the 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, along with contributions from our 2024 acquisitions that brought in global banking customers. TMT accounted for 24.9% of total revenues for the quarter with the growth of 6.7% quarter over quarter and 8.4% compared to the same period last year. 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 values sequentially, it increased 7.7% year over year, primarily due to contributions from our recent acquisition. Other vertical contributed 7.8% of total revenues, reflecting sequential growth of 10.1%. and 4.6% increase compared to the second quarter of 2024. The year-over-year increase primarily came from customers tied to agriculture, marketplace, and service provider sub-verticals. 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 of 2025 and up from 3,961 in the second quarter of 2024. At the end of the second quarter of 2025, our total US headcount was 359 or 7.2% of the company's total headcount versus 8.8% in the year-ago quarter. Our non-US headcount located in Europe Americas and India was 4,654 or 92.8%. In the second quarter, revenues from our top five and top 10 customers were 37.5% and 57.3% respectively versus 38.5% and 57% in the same period a year ago respectively. 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 non-strategic 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 and wins, increased engineering headcount to support future growth, and timing of costs related to some fixed price contracts. Non-GAAP EBITDA during the second quarter that excluded 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 of 2025 and up from 11.7 million or 14.1% in the year-over-quarter. Sequential decline in EBITDA was largely due to the decline in gross profit NFX headwinds. The increase on a year-over-year basis was largely due to higher revenues, partially offset by increase in operating expenses and NFX fluctuations. Our gap 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 one cent per share based on 76.6 million diluted shares in the year ago quarter on a non-gap basis in the second quarter our non-gap net income was 8.3 million or 10 cents per share based on 86.4 million diluted shares compared to the first quarter non-GAAP net income of 10 million or 11 cents per share based on 87.8 million diluted shares and 8.5 million or 11 cents per share based on 77.9 million diluted shares in the AERGO quarter. On June 30, 2025, our cash and cash equivalent totaled 336.8 million up from 325.5 million on March 31st, 2025. Now coming to the guidance, over the past couple of quarters, the majority of 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 to 105 million we expect our recent acquisitions contributing approximately 12 percent of the revenues we expect our third quarter non-gap EBITDA to be in the range of 12 million to 13 million dollars For the third quarter of 2025, we expect basic share count to be in the range of 84 to 85 million and our diluted share count to be in the range of 87 to 89 million. We are maintaining our full year revenue outlook of 415 to 435 million All of this despite an estimated low double-digit annual percentage reduced revenue from cautionary spending on traditional business, which we projected early in the year, and it was affected by uncertainty with the macro environment. In spite of these events, we continue winning innovation-led projects and grow 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. As we go into the Q&A session of this call, I will first announce your name. At that point, please unmute yourself and turn on your camera. First up is Mayank Tandon of Needham. Go ahead, Mayank.

Thank you. Can you guys hear me okay? Yes, we can, Mayank. Great. I wanted to just maybe focus a little bit more on the pipeline and the pace of deal conversion. And if you could just talk about, you know, as you look at the guidance for the rest of the year and let's take the midpoint, for example, you know, how much of the revenue would you say is in the bag under contract and how much do you actually still have to go out and win? Just kind of give us a sense of your confidence level in terms of getting to your guidance range.

So maybe, Leonard, if you want, I can kick off and then we can add. Absolutely. Yeah. So, Mike, look, last quarter there was this question, right, when we talked about 415 to 435. 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 a high single digit 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 of business, which I'm sure Leonard and the team will talk about, but there's 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.

Great, should I continue or?

Yeah, 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 take it, because Anil is not in the room, so I'm doing a little bit of connection itself. So first of all, let me finish the first part of your question. So the pipeline is very robust. We have a little bit of a conservative point of view, because if you remember when we were last time at an earnings call, we were talking about a very good April. And indeed, that was a very optimistic part of the growth, but we want to be cautious because you don't know. Then, you know, a lot of macro impact happened in the next couple of months. And even though we finished a quarter at a solid record number, still it was not to the full expectation where it would be. The pipeline, which was created in Q2, is extremely good. Again, jumping forward, the July numbers look positive again, but I don't want to jinx it. If I jinx it again, but we look optimistic for the second half of the year quite a bit because the convergence of the projects, especially related to any kind of data and AI platforms, is growing fast. We're talking about three times more than a regular business, but reality is almost all the customers across our universe are taking on the business associated either with innovative projects or with substantial migrations. And we're talking about not just POCs or quite big projects. Some hyperscalers help us with that as well. So when we look at how much in the back versus how much is a bit of a stretch. Anil mentioned to you about the low end, getting from low end to the mid range require quite a bit of effort. And at this point, we just stay on the range. I think we'll have much better view by the end of the quarter. But right now, we're very optimistic on the new big deals. At the same time, coming back to your second part, how we structure it, the pricing around it, the business associated with it, there are several aspects. So first of all, we'll talk about our game model. So when we are engaged with the technology innovative projects, as you can imagine, the price point are favorable because clients are trying to reach customers the goal of their internal value add to the business and to also the cost system. So there's a little bit of a competition for the talent. And as you know, Green Dynamics is quite well positioned. Now, on the traditional business, there are various factors. We see a lot more pressure right now from the clients to scale the business with Green Dynamics, particularly in India. You know, the cost structure, the price structure in India is different. So, as you see, we continue to grow our headcount, but it's not any more proportional, at least at this point, to where we were, where we were purely driven by European engineering. Also, with the global follow the sun model, we're signing the deals across various regions. particularly in Europe and in Latam, which again has a different pricing model. So it's very hard to kind of create a common denominator for all these factors, but we see the vector is solid. We went through negotiations most of all for this year, But, you know, very soon we'll start negotiations for 2026. What's very important, we also addressed that with the weakening US dollar, some of the value factors for the European engineering cannot be addressed by purely time and material. So the fixed bid, the, you know, our pods, and now with the gain work, it becoming very, very, you know, very much into the solution base. And that's kind of gives us more positive attributes, how we build the business. But overall to summarize it, uh we bet heavily on our ai data business to grow and it's a fantastic uh positioning where we are today with our technology capability if you want a clarification i'll do more but i try to cover a very broad base in one answer that's great i'll pass it on thank you so much for that appreciate it thank you man next up is punit jane of jp morgan go ahead punit

Thanks for taking my question. I wanted to ask about how, like, Eugene, I think you talked about how AI is changing the nature of work, specifically in this traditional SPLC cycle. So can you talk about need for training or hiring employees differently. And it feels like your high experience within your workforce should be helpful, but I'd like to know your thoughts. Like I'd like to hear like how you think you might have to hire or train employees differently as you prepare Grid Dynamics for this changes to a traditional SDLC.

Yes, thank you, Punit. Great question. And this is not something which we started to do just today, right? We started to do it quite some time ago, preparing for AI First future. And as we already said, we've always been a little bit top heavy 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 life cycle, The engineers who are working on the actual projects supported by the AI agents, which are actually writing code and making modification to the code base, they are acting as the judges, right? And the deep experience of engineers helps to define, to determine whenever the suggestions which are made by the agent is 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 the, I would say, AI native engineers who grown with those AI agents from the very beginning of their careers and very natively 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 the technology It's not only about coding, right? It's all through the whole cycle of development, starting from requirement understanding and governing and ending with deployment and testing for the solution and 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 GridU training program is preparing those engineers with Like we traditionally said prompt engineering, but right now it's more like a context engineering, like a little bit new term in the industry, which everybody's using to help those agents to be successful and to drive them further. So that's a shorter video.

No, that's great. Like context engineering, we've been hearing that term a lot these days. No, I appreciate the response. And obviously, like from investor standpoint, like we get a lot of questions on the reasons for slower growth in broader IT services, like whether it's macro, whether it's AI. Let me ask that question again. Like you have like say vertical, 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 adoptions across these verticals? Or would you say like that growth difference across those verticals is purely like a function of macro or sector-specific challenges?

So Puneet, and I'll let other people talk about more specific. I think it's a very fundamental question. There's no slowdown on AI adaption across all the verticals. What happened is in certain verticals, we're gaining a momentum because the existing business, the traditional business, the cloud migration, the new platforms and software development continues to expand while they adapt AI. An AI platform. We have our own homegrown platform. We use our partnership. There's a lot of stuff that's going on. You know, we even started getting some press from participation and 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 and there are some traditional large legacy business which has participation in brick and mortar. Not mentioning all this emotions around the terror strategies, they're slowing down on a traditional software development, infrastructure, expenses, all this stuff. They continue to invest into AI projects. But if you noticed, Anil brought in some flavor, talking about what could have been if that business would be slowed down. It would be way above the upper limit. range of the guidance, but it wasn't. And what we see right now is there's a redeployment of resources in a more traditional conservative fields, which I would say potential expansion is limited, where the other more aggressive expansion combined with the traditional spending happened in other industries. So the bottom line conclusion, AI growth supports great dynamic growth wholeheartedly. We have more than one platform. We have internal platform, we have external platform, we participate in many activities which actually pay decent dollars. But that's muted current business in some of the more traditional areas start dragging a little bit down and is driven by those macros.

Okay. Thank you. Thank you, Puneet.

Thank you, Puneet, for your questions. Next up is Brian Bergen of TD Cowen. Go ahead, Brian.

Hey, guys, thanks for taking the question. Wanted to ask on the AI powered engagement model, can you talk about the early client testing 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, let me address this question. Thank you, Brian, 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 software development lifecycle by embracing both processes, technical tools, team composition, and also the new commercial model. And 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 process 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 reducing the timelines which allows us to be more competitive also on the pricing side right um As for the full-fledged GAIN implementation, including the commercial, we are in the phase of fine-tuning this whole model because it's a truly 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 are starting piloting this model as soon as we make the process as smooth as possible to go into production.

It's a margin question, Brian. I think what Vasily is, Vasily is a kind of a foundational father of the model. So, you know, and running Americas gives him a bit of a upper, you know, upper hand with others. And when I was in Chicago at the conference, first time I briefly mentioned the, you know, ideas and turns out, obviously we're not alone, but what's important is approval and approval. How much business we generate, but what's more important, how beneficial it becomes to the client and Green Dynamics. I would not talk about directly Gross margin. I was talking, I would refer to the profit margin as we grow. And you can retranslate it back because it includes the partial ownership of the people and platforms as 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 point, which you guys were torturing us from the beginning of AI. Well, the engineers will disappear and how the new world is going to work. What it's 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, right? I mean, you see some of the notable big companies throwing this eight-digit, nine-digit numbers, right, into the people. Now, for us, since we have such a good pyramid growing 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 Green Dynamics, which makes measurable results. And those two clients, which Vasily mentioned, they're far along the way. And the reason they realize why it's important is because the pace of innovation substantially increases with the time and surpass their ability internally to even 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 a 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 purely margin, which obviously would be addressed by increasing margin as well.

Okay. Okay. Makes sense. I get that. I guess I'll follow up. Just in the near term, we'll talk about near term margin and just understanding demand is choppy. You've increased headcount again. So how are you balancing keeping quality bench for a growth recovery and potentially investing around kind of non-billable R&D right now versus kind of optimizing cost structure? Can you just talk about that dynamic in the near term specific to 25? I'm you, you're the numbers.

As you would expect, I'm laughing, Brian, because this is exactly what we're doing day in and day out right now. So it's something very interesting that we're doing within the company. There are two very important things that I'm working on. One is, as you pointed out, is there is a certain degree of financial discipline that we have to embark upon. Right. In the short term to ensure that, you know, as a public company, we have to just work on. But there's another mandate that Leonard has given me, which is we have to double down and invest into future technologies, into future platforms and future personnel. So there are two parts of my whole kind of balancing act, so to speak. The focus that we're looking at is we are creating specialized pools of labor that are targeting certain specific technologies. And I'm sure the group here, they can talk a lot more, whether it is a hyperscaler, whether there's some AI specific things. We've developed internal platforms. So there's a lot of activity going on on our tooling side to build these accelerators and platforms on the AI side. While we're doing that, we're taking a very closer look at our utilization bench on our more traditional side of the business. And from that point of view, obviously, we're ensuring that we are a little bit more cost optimized. So that's how we're working on it. And actually, if you look at from my Q2 to Q3, some of my increased costs is because of investments in some of this engineering talent, too.

So, Brian, let me be very blunt because Anil is trying to be a little bit elusive. And, you know, 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, as a public company, we need 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 Green Dynamics stock has deteriorated for whatever reason you guys decided to. So to me, it's like, look, I don't want to go back to where I was three months ago. I want to go five times more than I was three 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 till 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 answer your question. We will do the housekeeping and Anil will answer. We'll have to make sure that we don't do it randomly, but I have a hugely aligned strategy with 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, Rajiv is there, but We have Yuri and Vasily to make sure that in the US and Europe, we're going to have a bespoke application of AI platforms. And as of today, we want 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, and you will hold us back when things have become a little bit more aggressive. But the way how we've been doing it for the last 18 months, even going through the Liberation Day and all of the macro parts and going through ups and downs, it would not deflect a determination than in a modern AI, gendered AI, physical AI, the solution practices, we're going to be at the leadership role.

Thanks, Brian.

Thank you for your questions, Brian. Next up is Maggie Nolan of William Blair. Go ahead, Maggie.

Hi team. 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, you know, those hypers?

All right. So you kind of. Accelerated meant the question. So that was my agenda for the next quarter. We're going to bring you ahead of the global partnerships to get you very specific details on that partnership program because the mode of operating, models of operating today for Green Dynamics is the focus on innovation, customer partnerships, and wide distribution of the game model. So regions, AI technology, internal platforms, and a scaling partnership. So you ask the question, where are we behind, beyond hyperscale? First of all, hyperscale is also partition. There are no longer hyperscalers traditionally fighting for the space on the spending dollars on the cloud platforms only. They're very actively participating on merging the platforms they built with the AI tools they offer. Second part is we are also partnering with the Colossus guys, the major players, which enable the foundational capabilities, like, you know, like in NVIDIA of the world, because you need to have another layer, you know, without the physical layers, without capabilities. It's hard to scale. We are partnering with the robotics companies. We are participating in a revolutionary way of changing the industrialization. And again, industrialization is very important. We're building agent tools and agent factories within the clients and partnering with their own teams as well with the third parties which are bringing AI tools. Not to forget the fact that there are some of the very, very innovative, creative ideas come from this myriad of the new formed AI, I would call them startups. Some of those startups getting capitalization, we have our greatest today. This is where I love the VC world, right? People throw money and then something works, right? But these guys are brilliant. And our job, Eugene's job, and some other key people on the team job is to select the ones who actually will make sense. Now, I don't want to offend any DCs. It's great you guys have so much money. But for us, we need to select the winners. So it's the three ways. The hyperscales into new models. The big players. who are bringing their own homegrown models. And it's our customers who are joining efforts with the partners and their own staff. We're helping them to build this solution. And the fourth one, which is kind of, you know, exploding, it's the industrialization part of the world with the physical aircraft.

I just want to add that on the more traditional hyperscalers world, I'm talking from the European perspective, we definitely see traction, for example, with Google. We are a little bit later compared to the US, but definitely I see the traction right now. And even with Google, it's tied to both our more traditional search capabilities and collaboration around about around that and on the other side that's uh agentic ai platforms as well so that's definitely a big portion of what we're doing right now and i knew also reported the numbers right that we that we got from the partnerships in terms of the revenue great color thank you guys can can i follow up with the 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 a Neil? 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. You know, we've had six acquisitions over 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're an enterprise customer or commercial customer. Our focus tends to be more on the enterprise, which is where we manage the program. We have more focus, whereas a 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 even 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 structure approach towards define what a client is. If I do not get a dollar revenue in the quarter, And I just don't call them a client, although there might be an MSA, there might be something out there. And within a 12 month period, if they come back again, they're not a new client, so to speak. So a client can go now three quarters later, they come back, they're not a new client for me, they're within that 12 months, right? So we have a little bit of a strict approach towards this. So I think you will continue seeing some of these things. At the end of the day, when you look at our top 30, top 40 customers, that's 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 just conclude that part with a very important message. As you go see Green Dynamics, we believe that AI implementation in various forms will remain to be the key business. And there will be a huge value for the proper combination of the platform and the service providers. And I would say in a classical form, service consultants with very strong technology flavor. Remember, Brian mentioned about what is rationalization, how you manage it. We look at some of the clients from the tail, And we just don't invest into that relationship, too, because we see they don't have capabilities to become a viable player in the near future. It doesn't mean we just tell them goodbye. But if they don't fit in a model of the new AI era, and we try very hard to convince them there. They just don't have that type priority from our folks. So you will see that some of the clients will grow exponentially because it's a meeting of the minds and some of the clients either stagnate or may fade as we go forward. Yes.

Thank you very much. Thank you, Matt, for your questions. Next up is Surinder Thind of Jefferies. Go ahead, Surinder.

I'm trying to get the video here, guys. Yeah. Not sure whether... There we go. Okay. Big picture question here. Leonard, 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. What are the kind of the framework of what you're moving towards?

Well, first of all, social development is not the only area of AI.

Well, just as an example, right? That's a conceptual idea of the environment that... Because one of the things that's happening is change is happening very rapidly, right? And so if you're solving for something here in X, but by the time you get to X, we're at Y, you're going to be faced with a constant evolution. So how are you thinking about the evolution of the firm over the next three to five years?

Yeah, so the evolution will take more than three quarters. This is going to, you know, it's a combination of adoption of the technologies, capabilities of the distributed systems, and ability to generate value on each individual, in each individual case. 50%. It's just a number, 30, 50, 80. And I've used software development, but please, in my opinion, again, it's a small percentage of the change. There's a change of creating the value for the business than just trying to improve the code. I think that human touch will continue to be a big part of all the key decisions, but it's gonna be in a different forms. you know, writing the code is always level. And I think, you know, Eugene can comment more on that. There is ability to understand the deployment of the systems, reverse compatibility of the systems, security to manage and control the future, you know, expansion of the systems. And we will have to nail on each of them separately. On a low level, it's gonna take way more. It will take way over than 50%. It's gonna go substantially large percentage of the code development. As we continue to monitor and expand on the capabilities, the progression will take a much longer time than some of those people want to make sure they have instant conversion. So the people, the humans, who are properly trained in the systems will have to define with ability to what is the future. Otherwise, we're going to... We will have to face the moving target, which is not a good solution because you continuously invest in something which is going to be aged in six months. So to summarize that, on the basic coding level, it's going to be way more than 50%. On that system management integration, data compliance is going to be lower, but the effect has to be proven. On the analytical part of the systems, it's going to be always a combination of people and projects. And just another point, when people talk about tasks, some of them will be 100% tasks by the agents. But when we talk about the total system implementation, the percentage would be lower. So I think it would be a good segue that, you know, Eugene, you can make comment of the experience.

Yes, of course. And I understand that currently internet is full of examples of wipe coding and creating full-fledged Facebook clones in 15 minutes. Anybody who really kind of perform production-bound projects understands that building a prototype and putting something in production under load for mission critical systems is very different things. And what we observe in our business is that I'm in charge of pre-sales, for example, in the company. And our pre-sales is completely transformed by AI first developed. We are able to turn really very good prototypes and pilots very, very quickly to the customers. But then we are going into the real thing in implementation of the scalable system, implementation of the system under load, in secure environment with deployment and scaling requirements, which are needed for production. It's completely different ballgame. And even the most sophisticated AI agents are very quickly losing their context and starting to float flow to the sides. And they still need a lot of human supervision and human design and thinking and creativity behind them to steer them. Very simple, like we are savants, right? We are smart, but aimless. And this is why we are still kind of belief in this.

Vasily wants to add something. You opened the Pandora box. This is our strive for excellence.

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

Okay. Okay. I appreciate the time, guys. So that was my main question.

Thank you so much. Thank you. You're welcome. Ladies and gentlemen, this concludes the Q&A session of our call today. I'll now turn it over to Leonard Lifshitz for closing comments.

As we conclude our second quarter earnings call, I want to leave you with three key takeaways. Number one, Green Dynamics AI for Strategy is driving our growth. The AI and data initiatives now account for a quarter organic revenue in the first half of 2025, growing nearly three 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 Green Dynamics strengths. Our expanding pipeline aligns with enterprise investments. And finally, Green Dynamics is built for sustained differentiation. We have a proven track record of emerging stronger through industry transitions. Based on re-accelerating client demand, we're confident in our outlook and our ability to empower Fortune 1000 enterprises and 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.