GDYN - NASDAQ

Good afternoon, everyone. Welcome to Grid Dynamics Fourth Quarter 2025 Earnings Conference Call. I'm Cary Savas, Director of Branding and Communications. [Operator Instructions] Joining us on the call today are CEO, Leonard Livschitz; CFO, Anil Doradla; CTO, Eugene Steinberg, COO, Yury Gryzlov; and SVP, Head of 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 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'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 share that Grid Dynamics closed 2025 with another landmark performance. In the fourth quarter, we beat Wall Street expectations on both revenue and EBITDA delivering record revenue of $106.2 million and a strong $13.7 million in non-GAAP EBITDA. Remarkably, we finished the full year with a record revenue of $411.8 million, which is 17.5% growth year-over-year. 2025 non-GAAP EBITDA was $53.8 million. In Q4, our top 3 customers included two global technology companies and the largest payment technology company. All of them are leaders in the AI space. Our performance is a result of our AI expertise, the strength of our accelerators and keen domain knowledge. In Q4, our AI revenue grew 9% over Q3 and now represents 25% of our overall revenue. For the full 2025, our AI revenue reached over $90 million, representing 30% year-over-year growth. In 2026, we anticipate continued AI revenue growth. There are three key factors driving our bullish outlook on AI. First, AI coding agents and automation, significant enterprises build versus buy calculus that were built at a lower cost. The shift aligns with Grid Dynamics core strengths in building solutions for Fortune 1000 companies, leveraging specialized talent and intellectual property. Second, our efforts with GAIN are resulting in a richer blend of outcome and output-based engagements. Crucially, these new engagements enable us to decouple pricing from effort. We have successfully deployed software platforms across multiple industry verticals. Our AI engagements now strategically combine the strength of our human capital with the value of our platform assets. The market reception for these software platforms has been strong, with customer demonstrating a clear willingness to pay. This positions us well to grow recurring revenue, deepen customer retention and extend the duration of our engagements. Grid Dynamics engagement structure will contribute to our 2026 margin expansion. Third, the speed of AI transformation is not uniform across industry verticals. While we continue to generate revenue from the retail and CPG verticals, we prioritize investments in the area of technology, financial services and manufacturing, where we see significant opportunities for customized auditable product-grade agentic AI platform. Let me talk about Grid Dynamics vertical strengths. Enterprise are learning that deploying AI at scale requires deep domain expertise. We cannot build an effective Agentic system for a production floor without understanding manufacturer. You cannot build one for a global permit network without understanding the compliance architecture. Such expertise is what we have been building vertical by vertical for nearly 2 decades. Now we're codifying it into platforms. Our Merchandising Experience Platform, MXP, brings our expertise to marketplaces and digital commerce. XTDB, our bitemporal Data Platform helps financial clients, specifically in capital markets with auditability and other compliance challenges. Platforms unlock IP-driven outcome-based engagements, and that's how Grid Dynamics moves from billing for effort to billing for value. Now let's talk about partnerships. Our partner influence revenue reached a significant milestone in 2025, exceeding 19% of our total revenue. So significant growth underscores our mission to keep Grid Dynamics at the forefront of modern enterprise infrastructure. We have strengthened our relationship with all hyperscalers through targeted investments in Agentic platform capabilities, earning specialized badges and building new joint solutions. Notably, in December, we signed a strategic collaboration agreement with AWS for data foundations in AI. Our premier partnership enables Grid Dynamics to receive funding from AWS to support AI enterprise initiatives. Our collaboration with NVIDIA on Omniverse based solutions is enabling us to deliver high fidelity industrial-grade digital twins that are essential for our physical AI expansion. In the fourth quarter, our vertical execution is best illustrated by several notable projects. Fintech transformation. We partner with a global financial leader to launch a proprietary generative AI agent supporting more than 10,000 financial advisers. This interactive experience replaces static policies with personalized guidance as is projected to increase productivity by about 20%. TMT Analytics. For a global technology enterprise, we modernized a legacy mobility application into a scalable analytics platform providing centralized visibility into global travel activity and spend. The platform has materially improved usability, increased feature velocity and reduced stakeholder coordination overhead. Dispute management. We developed a comprehensive dispute management solution for a leading financial services firm. By integrating Generative AI, the platform streamlines charge-back challenges, increasing win rate and reducing operational overhead. Financial governance. At a leading U.S.-based global bank, we're building a global agent runtime and AI orchestration platform, enabling business-focused agent to automate complex workforce starting with successful automation in internal compliance. We also deployed the AI-driven executive insight capabilities that provide leadership with consolidated global operational summaries. With that, let me turn the call over to Eugene Steinberg, our CTO, who will talk about our AI capabilities, how we are upskilling our engineering workforce and how we're using it to improve our internal operations. Eugene?

Thank you, Leonard. Good afternoon, everyone. We are actively executing across three horizons. AI first engineering, Agentic Enterprise and Physical AI. In Q4, we shipped across all three, and these foundations position our AI business for 2026. Horizon 1, AI first engineering. Horizon 1 is the core of our current business. The engineering work that source the majority of our clients today. We are accelerating productivity across the organization through AI first native tooling and investing decisively in the continuous upskilling of our engineers. Enterprises are no longer debating the merits of adopting AI for software development. But rather how to do it without losing control of quality, security and institutional knowledge. It is in this context that we launched Rosetta, our AI native software development framework. Rosetta is part of our GAIN initiative and provides a governance layer for AI coding agents. Rosetta automates contract setup, enforces consistent workflows and manage his engineering knowledge at both the engineering and organization level. It operates within the client's own security perimeter and works across all major coding platforms. Developers get consistent project aware agent behavior from day 1. Engineering colleagues get centralized governance and visibility across the entire agent footprint. With Rosetta clients benefit from decades of institutional expertise seamlessly embedded in the way engineering workflows. We have several engagements underway and a scaling gain as the standard delivery backbone across all engagements in 2026. Grid Dynamics separations is client 0 for our AI solutions. Cerebra, our internally developed Agentic platform launched in Q3. It is built on Google AI stack, Gemini enterprise, ADK and A2A. Within Grid Dynamics, Cerebra is being used by our sales recruitment and knowledge management organizations, automating proposal development, technical prescreening and research at scale. Clients adopt faster than the platform has already been stress tested in production. As AI revenues ramp, we expect this model to drive both revenue growth and margin expansion. Horizon 2, Agentic Enterprise. Horizon 2 is where we are expanding and investing by leveraging our engineering debt to enterprise transformation at scale. The Agentic era is reshaping the economics of software delivery. AI native development tools are allowing the overall cost of building and deploying software, placing pressure on systems integration and configuration programs. At the same time, client expectations are rising. Programs previously too expensive or too slow to justify are becoming feasible. Enterprises are thinking bigger and moving faster taken on significantly larger mandates. That means moving away from SI-heavy engagements and toward a regional in-house engineering. That rotation plays directly to our strength. In the past decade, enterprises have increasingly became dependent on system integration, assembling Software-as-a-Service ecosystems, configuring cloud services, and stitching together vendors products. In the Agentic era, this changes fundamentally. Production deployments require bespoke engineering. Purpose-built agent workflows the main specific data and knowledge layers, distributed system and platform engineering. Grid Dynamics is well known for its engineering capabilities and proprietary IP at leading global enterprises. The agentic era rewards builders, and that is where we have invested. Our go-to-market runs two tracks. For Tier 1 enterprise clients, we architect and co-develop custom verticalized AI platforms built around the specific architecture, governance and compliance requirements. For Tier 2 mid-market clients, we integrate hyperscaler platforms with Grid Dynamics verticalized components on top, optimizing time to value and overall cost. Both tracks are expanding. We have also established a partnership with Temporal through the JumpStart program. This initiative positions us as a technology consultants for Temporal's customers. embedded in crucial architectural decisions from the outset. This partnership has generated multiple new engagements across financial services, enterprise software and industrial sectors. The proof points are concrete. A notable example is our work with one of the world's largest payment networks, where we are leading a broad Agentic AI program. We have developed a recurring service across 17 applications, a universal enterprise assistant with agent to agent communication and centralized governance and evaluation. Our efforts have led to an approximate 40% reduction in build time and 60% reduction in ongoing maintenance efforts. This platform deployed across 30,000 employees. The impact has been measurable. Specialized groups are seeing up to 15% productivity improvement, driven by faster information access and reduced manual research. As a leading global CPG company, we developed over 20 enterprise-ready AI agents through a unified agent factory platform. This delivered 15% productivity improvement across enterprise users. These deployments confirm a pattern we see consistently. Once AI capabilities move fully in production, clients realize approximately 15% productivity gains, tangible operating leverage at enterprise scale. We are leveraging our deep domain expertise to build vertical AI platforms, co-defining patterns in the structured productized offerings. Our initial solutions have real traction and are generating revenue with enterprise clients. MXP, our merchandising and product discovery platform illustrates its progression most clearly. It began as search engineering expertise, evolved into reusable accelerator. And in 2025, gross intel license revenue with a growing customer base across North America, Europe and Latin America. Its deployment for a leading European luxury retailer delivered a 7% total revenue uplift, and a 50% reduction in merchandising workload, while handling a 25% year-over-year surge in peak holiday traffic without disruption. XTDB is our platform designed for the financial industry, a bitemporal database built specifically for regulated financial environments. As financial institutions deploy AI agents, the regulators require full point and time reconstruction of any decision. Banks deploying agents for trade processing, compliance or investigations, need systems that can capture precise information related to trading activities. XTDB addresses that with full auditability across both business time and system time. The platform has been adopted in several global banks and in Q4, we shipped a significant new version extending its capabilities for multi-entity data mesh environments. It is this kind of deep infrastructure IP that differentiates our financial services practice from generic AI Consulting. Our engineers no longer arrive as individual contributors. The if backed by codified IP, Rosetta, MXP, XTDB and documented patterns from dozens of deployments. The client gets immediate expert deployment, not a learning curve. Horizon 3, Physical AI. Horizon 3 is our forward-looking investment in Physical AI, bringing the same AI engineering depth they apply in software to industrial and manufacturing environment. Our flagship platform here is Incarna, a software platform that supports the robotics industry. Incarna dramatically compresses with time required to program robots for complex manufacturing tasks, enabling robots to handle high variability physically demanding work that conventional automation cannot address. In partnership with Smart Ray, a leader in industrial 3D vision sensors we developed and deployed the Incarna AI model for robotic weld inspection. Weld inspection is demanding. Commodity requirements are stringent and variability in materials and geometry makes rule-based automation unreliable. The result, high inspection consistency, improved quality assurance and scalable automation in environments where precision is nonnegotiable. As a Fortune 10 manufacturer, we automated the conversion of CAD files to CNC machine instructions, a workflow that previously took 5 days now completes in hours, greater than 90% cycle time reduction, validated in production. We will have more to share as this program scale. As we look ahead, we will build on our foundations. We are rapidly and deliberately scaling towards a multi-industry AI-led business transformation. GAIN and Rosetta codify our engineering judgment, so its scales beyond individual engineers. MXP shows that our IP can generate revenue as software, not just as a service. XTDB gives us a technically differentiated entry into finance. Incarna, opens doors in manufacturing. And our Agentic practice is shifting from the bespoke delivery to structured vertical offerings where our accelerators compress time to value and our contracts increasingly capture outcomes. We are moving from labor scale growth to IP scale growth, and that transition defines our 2026 execution. With that, let me turn over to Anil.

Thanks, Eugene. Good afternoon, everyone. We recorded fourth quarter revenues of $106.2 million, slightly above the midpoint of our guidance range of $105 million to $107 million. This represents a sequential growth rate of 1.9% and a year-over-year growth rate of 5.9%. There were 30 bps and 22 bps of FX headwinds on a sequential and year-over-year basis, respectively. Non-GAAP EBITDA was $13.7 million or 12.9% of revenue and was at the higher end of our $13 million to $14 million guidance range. In the fourth quarter, there was a negative impact from FX fluctuations on a year-over-year basis. We are exposed to a currency basket across Europe, Latin America and India. While we utilize both natural hedges and an active hedging program, the net year-over-year impact on our EBITDA was a headwind of approximately $1.5 million. On a sequential basis, there was a tailwind of approximately $160,000 to our EBITDA as the dollar strengthened relative to the British pound and euro. Looking at performance of our verticals. Retail remained our largest vertical, contributing 28.7% of total revenues in the fourth quarter of 2025. While revenues in this vertical increased by 5.3% on a sequential basis, there was a decline of 6.9% on a year-over-year basis. The sequential increase was broad-based across our retail customer base. TMT, our second largest vertical accounted for 28.3% of total revenues for the quarter. The vertical delivered strong results with growth of 5.3% on a sequential basis and a 27.5% increase on a year-over-year basis. The strong year-over-year growth was primarily driven by our top 2 technology customers. The finance vertical accounted for 22.9% of total revenues in the quarter, growing 5% on a year-over-year basis. This growth was primarily driven by increased demand from our large fintech customer and large banks. Turning to the remaining verticals. CPG and manufacturing represented 10.2% of our fourth quarter revenues. This vertical remains stable in absolute dollars sequentially but declined 4.3% on a year-over-year basis. The year-over-year decline was largely due to a decline at some of our automotive customers. And this was partially offset by our CPG customers. The other vertical contributed 7.3% of fourth quarter revenues. This remained flat on a dollar basis relative to the third quarter and grew by 8.4% on a year-over-year basis. The year-over-year growth was primarily from our meal kit client. And finally, health care and pharma contributed to 2.6% of our fourth quarter revenues. We ended the fourth quarter with a total headcount of 4,961 slightly down from 4,971 employees in the third quarter of 2025 and that from 4,730 in the fourth quarter of 2024. Although our total headcount was down on a sequential basis, our billable headcount increased meaningfully. We continue to rationalize our overall headcount as we align our skill sets and geographic mix. At the end of the fourth quarter of 2025, our total U.S. headcount was 357 or 7.2% of the company's total headcount versus 7.4% in the year ago quarter. Our non-U.S. headcount located in Europe, Americas and India was 4,604 or 92.8%. In the fourth quarter, revenues from our top 5 and top 10 customers were 39.7% and 58.5%, respectively, versus 35.6% and 55.8% in the same period a year ago, respectively. Moving to the income statement. Our GAAP gross profit during the quarter was $36.1 million or 34% compared to $34.7 million or 33.3% in the third quarter of 2025 and $37 million or 36.9% in the year ago quarter. On a non-GAAP basis, our gross profit was $36.6 million or 34.5% compared to $35.2 million or 33.8% in the third quarter of 2025 and $37.6 million or 37.5% in the year-ago quarter. On a year-over-year basis, the decline in gross margin was from a combination of FX headwinds and greater mix of U.K.-based headcount from our acquisition of JUXT. Non-GAAP EBITDA during the fourth quarter that excluded interest income expense, provision for income taxes, depreciation and amortization, stock-based compensation, restructuring, expenses related to geographic reorganization and transaction and other related costs was $13.7 million or 12.9% of revenues versus $12.7 million or 12.2% of revenues in the third quarter of 2025 and was down from $15.6 million or 15.6% in the year ago quarter. The sequential increase in EBITDA margin was from a combination of higher gross margins and FX tailwinds. On a year-over-year basis, the decline in EBITDA margins was largely due to a combination of lower gross margins and FX headwinds. Our GAAP net income in the fourth quarter was $0.3 million or breakeven per share based on a diluted share count of 86.4 million shares compared to the third quarter net income of $1.2 million or $0.01 per share based on a diluted share count of 85.8 million and net income of $4.5 million or $0.05 per share based on 83.8 million diluted shares in the year ago quarter. On a non-GAAP basis, in the fourth quarter, our non-GAAP net income was $8.7 million or $0.10 per share based on 86.4 million diluted shares compared to the third quarter non-GAAP net income of $8.2 million or $0.09 per share based on 85.8 million diluted shares and $10.3 million or $0.12 per share based on 83.8 million diluted shares in the year ago quarter. On December 31, 2025, our cash and cash equivalents totaled $341.1 million, up from $338.6 million on September 30, 2025. M&A continues to take priority in our capital allocation strategy. We're committed to augmenting our organic business with acquisitions that strategically enhanced our capabilities, geographic presence and industry verticals. Coming to the first quarter guidance, we expect revenues to be in the range of $103 million to $104 million. We expect our first quarter non-GAAP EBITDA to be in the range of $12 million to $13 million. For the first quarter of 2026, we expect our basic share count to be in the range of 85 million to 86 million and our diluted share count to be in the range of 87 million to 88 million. For the full year 2026, we are bullish in our outlook. We expect revenues to be in the range of $435 million to $465 million. That concludes my prepared remarks. We're now ready to take questions.

[Operator Instructions] The first question comes from Maggie Nolan of William Blair.

So you've had impressive growth in AI revenue and you're above $90 million for 2025. So I'm wondering if projects are moving into production at scale and then what is the nature of these projects? And how is the demand among customers?

Thank you, Maggie. Thank you for kind words. Look, we extensively discussed in various forms what AI represents to Grid Dynamics and what is the opportunity for us going forward. Fundamentally, what makes a big difference for Grid Dynamics for 2026 on is that we're not only moving from the small development project to full scale implementation, but also we introduced our platforms, which has been noted during this particular time. And that kind of scales the confidence with the clients to give us more of the solutions where we represent our engineers combined with their own tools as a new way to building the solution faster and more affordable for the clients. Perhaps some words from Eugene.

Yes. It's a great question. And there are two main zones, which are most exciting for me. One is AI-powered customer experience. The reason behind that is that this is the zone where the impact from source personalization, Agentic commerce is very obvious and memorable by our clients. And this is where clients see ROIs in weeks, not in months or years. And that allows us to expand those accounts very, very quickly based on this successes which we see in this domain. Second is enterprise AI platforms, not as visible as front end work or AI-powered customer experiences. But this is a foundational layer, which helps our companies to organize their data, build AI agent factories on top of this data and then go into developing business agents on top of those platforms. And what we see in our projects is as those platforms mature and go to production clients start to scale very, very quickly building AI agents, and we are helping them to develop the AI agents. And we are going from 1 to 10 to 20 of those specific customer facing, which will collect agents very, very quickly. So this expands our work and allows us to move very, very quickly.

Great. And then anything else you would comment on as you move into 2026, kind of how you expect the trend to evolve any way that you can maybe tie that back to the numbers or maybe some of your margin expansion goals you've mentioned.

Yes. So we bombarded you, Maggie, with a bunch of names during this press release, right? So we were talking about merchandise experienced platform, we were talking about bitemporal database, we're talking about Incarna robotics AI platform, subsequent growth of the Rosetta, it's automation within GAIN model, the platform against Cerebra, which picks up our internal process, bringing Grid Dynamics as a client 0 for implementations. What is it all about? Those are not just buzzwords. It's just a way to understand for our clients that there may be a little bit more scarcity in the market of clarity what to do. But when you work with Grid Dynamics, we represent basically three key functions. First, we are domain consultants. So we understand what the customer problems are, and we are tailoring the solutions with that as a important contribution for Grid Dynamics as a mix between Grid Dynamics trained engineers, the standard tools and platform from the market and customized tools, which will bring based on our platform and development. The combination of three leads to a few things. First of all, it's a shorter time to implementation for our clients. And second, it moves away from our traditional talent material offering where we're putting together contribution based on the planned outcomes, which ultimately leads not only for them to gain momentum and have a better financial return but a high value add for the margin expansion for Grid Dynamics. Those are three elements.

The next question comes from Bryan Bergin of TD Cowen.

The first one I'll just get a high level. So just with everything that's going on in the market, services, software-based pressure, the whole kind of SaaS apocalypse fears that are out there. I want to kind of sanity check it with you first. Based on what you're seeing in your client conversations and what they're doing in contracting, what's your perspective as it relates to enterprises increasing their custom build preference versus buy the platform solutions. And if your clients are demonstrating a rising preference for custom builds, what are like the implications for your dynamics?

Very good. So I will start, and then I'll have Vasily to give you a few examples because there's nothing better than to show what exactly happened. So from the high-level perspective, obviously, we recognize that there is a very strong expectation that the cost of implementation will go down. Then people start throwing some comments. There is a decline of SaaS software companies or offerings. There is a decline of IT services needs because everything is going to magically appear. Well, all these statements are not false. I mean there are more and more tools available in the market. But what's the custom part is, is that creation of the tools and solutions, having our internal platforms makes Grid Dynamics much more efficient to really customize solutions for the individual clients and tests. And the reason we're doing this because it's very nice from the high-level perspective to look at these all wonderful models, but it's experimentation going to production is quite pricy. And many of the clients are hesitant to throw a lot of money without a clear outcome. And that's where Grid Dynamics comes in with the combination of people, processes and tools. And that's how we believe that even though there is an overall look that overreaching look that there are potential some decline of the needs, the company will agree dynamic needs is actually growing, and I'll have Vasily to bring some examples.

Sure. Thank you for the question, Bryan. You are right on point, we definitely see increased demand of our custom-built software. And if in the past, the customers were looking into improvements or enhancing their core platforms, core applications right now, given the overall kind of cost of development is getting reduced by utilizing AI native environment and SDLC. Companies like Grid Dynamics definitely benefit from this trend by getting involved into implementations and rebuilding of the typically SaaS, I would say, applications as a custom built and more custom-tailored solutions for end customers, things like HR systems or travel dashboards and et cetera, which were traditionally outside the investment areas for the companies -- for the clients.

Okay. Okay. That's helpful. And then a follow-up. I'll kind of -- I want to dig in on the growth outlook for the year and unpack it a bit. Anil, you made a comment, you're bullish in your outlook. Just to clarify that comment, are you assuming anything meaningfully changes in the underlying demand backdrop to hit any of these targets? And help us just kind of bridge the 1Q performance here. Is there a billed day dynamics or anything seasonal in the first quarter as you think about that first quarter implied growth rate relative to what you're talking about for the year?

Yes, Bryan. Q1 is a very simple story here. It's the seasonality and also in our time and materials business, T&M, there was fewer working days relative to Q4. So that's -- it's very simple. Now you're absolutely right. We are positive on how we're looking at the full year. There are two components of it. One is that some of the recent trends in our pipeline growth. Second thing is all the gentlemen that have spoken about on our AI trends, right? I'll let them build up on that. But where we are today, how we look at the year we feel more positive. And the final thing is that if you look at the range I provided, it's a little wider, right, relative to last year, we made it a little wider because we understand that during the course of the year, there's some positives, there's not so positive. So we kept it a healthy range.

So let me be more specific, right? So I think Anil answered a very simple question about Q1, and it's a very substantial reduction of the working days. So it's not something like normally happens traditionally here. But there is a bullish outlook for very simple reason. The pace of adoption of AI solutions and AI applications by Grid Dynamics customers, clearly outpaces the decline of maybe a little bit more hedged retail business. It happens simultaneously and this is no secret because if you look at the rate of growth of our client verticals, you can see to notable changes. It's a tack and more important, the financial vertical, which goes specifically into the fintech and capital markets, which is quite new and growing for us. So when we look at the total equation, the rate of growth and AI-related businesses. The contribution from our partnerships. Our improved performance in terms of the new type of agreements, fixed bids, performance base, other elements. And on the back side, some of the depreciation of more of traditional paged business, we've been there for years, we came up with bullish but conservative approach. And what's the conservative part of that? I think it's very important to understand. We've learned a little bit our lesson from 2025, right? I mean we actually believe we're going to be better than midpoint. But what it means for us? It means for us that in addition to all the facts, we need to understand the revenue dollars which are coming with the customers. And as the business grows, as you know very well, we also deploy our engineering talent across the globe, follow-the-sun strategy. And different regions have different price points and different elements of the business. So as we continue to scale our business, we want to make sure that early on, especially when we're introducing this a little bit variability of Q1, we do not get you guys question, are we safe or not? We are very safe.

The next question comes from Puneet Jain of JPMorgan.

So given like the recent news flow around Entropic Claude, are you seeing like any changes in your client behavior, increased urgency among your clients to embrace AI? And second, I know like you talked about the GAIN framework. I know it's built on proprietary as well as third-party tools. So to -- like all these developments like the evolution of AI ecosystem. Does that raise the bar on what GAIN can do for your clients in terms of productivity savings?

Very good. Let's start with, again, Vasily as the last time to give a little bit more of the multilayer approach. And then from the technology perspective, I think Eugene can comment as well. So, Vasily, please.

Yes. Maybe let me start with GAIN framework. So as you know, we announced it in the middle of 2025. And during the 6 months of 2025, we were rapidly developing this framework and running pilot implementations with our customers. As you heard in the prepared remarks, we implemented a series of software assets, which became now the part of this platform, which we are offering to our customers. So I would say in 2026, we see this will be the year of rapid adoption of the GAIN platform across our customers. And in fact, it became the de facto standard approach, which we use for the outcome and output-based engagements. Essentially decoupling billable headcount from the revenue growth. So we definitely see performance improvements. We transfer some of that to our customers, and some of that contributes to our improved profitability.

Eugene?

Yes. And when it comes to the actual improvements which we are seeing from Agentic coding systems and Claude and of course Entropic kind of others, of course, many of our customers are embracing it, and we are bringing those capabilities with them together with Rosetta, which is a layer on top of if. They are not competing with those Agentic Assistance on the foundation layer, but we are making them better, stronger and embed our own institutional knowledge in those systems with every engagement. And of course, impact of that very much depends on the actual nature of the project. So if you are going into greenfield POC kind of solution, your gains are immense, like 10, 15x compared to traditional ways because you are creating in an unconstrained environment doing whatever you want. If you are working in a brownfield project with still well-defined goals, technology modernization and migration, you still have a very strong improvement because the agents are tools. They are doing things much faster for you. And you see maybe 2, 3x improvements in the performance of the teams. However, when you are coming to the engagement and environments where the majority of the complexity is in the communication or orchestration. This has been -- it's much more challenging to realize the improvements from pure coding and creation of artifact. So it all varies very much depending on the portfolio of your solutions.

Just quickly to add to what Eugene and Vasily mentioned, I think it's very important. We mentioned several times in our prepared remarks as well. I think this transition from T&M based approach to outcome-based and output based. That's -- it's very important to emphasize because this is definitely real. We see that a lot. It happened during the 2025 in transition to 2026. And we see that this year, we will see much more of those -- many more of those engagements going forward. And that's why, as Vasily and Eugene mentioned, our GAIN framework together with verticalized solutions and the platforms that we are leveraging that will be very, very important this year.

Okay. Got it. And let me ask like follow-up to Bryan's question on the rest of the year beyond Q1. So based on our math, like it seems like the full year guidance at its midpoint implies like 5%, 5.5% sequential growth beyond Q1. So can you disaggregate that? Like what drives that growth like in terms of like whether it's like you talked about like earlier like the pipeline, billing days and all that. Can you talk about like what drives that 5%, 5.5% sequential growth beyond Q1 to get to the midpoint of full year numbers?

Puneet, make a few comments and, of course, we'll have Anil to back it up with the numbers. As I mentioned to Bryan, we do very seriously to make sure that we are reasonable but conservative in our forecasting. Okay. The pipeline is very robust. And the pipeline which we have right now, not only robust, but it shows a great opportunity with AI-related products and projects across multiple verticals and multiple clients. There is always a seasonality, right? So Q2 is better than Q1, and Q3 is better Q2 and then Q4 may have some additional flows like what happens in Q4 last year and all the stuff. But we kind of disaggregate the seasonality and behavior from adoption of AI. And we look at our pipeline as it stands today. So there is a very little assumption, Puneet, that there is going to be some enormous number of white swans or some Hail Mary or something extraordinarily great happens during the course of the year. Obviously, not everything on our books today, but majority is and we have a very nice number of our own tools, accelerators and platforms, which are going to continue to roll out during the year. So to summarize it, we are not hoping for the numbers. We have a strong pipeline to AI-related projects, particularly in the technology and fintech space. There is a growth in manufacturing, which is cutting quite robustly as well. And we see that adoption, as again, Bryan asked before, of the custom-developed solution on a combination of the deployed engineers and train program and our internal tooling brings us much higher acceleration. So the same people, the same trade capacity of the people can have several terms on the execution during the year. That's kind of the high level, but very clear understanding what does that pipeline mean? But maybe Anil will back it up with some numbers.

Yes. Look, I think the key thing is what Leonard said, right, we look at the revenues from a bottoms-up and a top down. And what we have as we go from '25 to '26 transition is this AI factor. And when we looked at that AI revenue kind of bottoms up, top down and look at the trajectory, I wish I could give a number, but it's a very healthy number as we go into '26. That is our foundation for our modeling in '26. Now when you look at the variations we said, right, we have this wider variation this year. We understand in the course of the year, things can happen. So as you go from the high end to the low end, we bake in some level of conservativeness with some of our clients, especially on the larger side, depending upon how we look at the business today. But again, this is top-down, bottoms-up with some conservativeness, but in '26, the fundamental difference is that we've got this AI trajectory and look at -- as Leonard pointed out, look at the fastest-growing segments, TMT and financial verticals. That's the key.

So just again, to put another number, Puneet, because I think it's important. I'll give you a little bit of a prequel, right? So mathematically, it does look a little bit aggressive. But realistically, it's a very unusual quarter to report, right? It's the year-end. So we are in March. So you can suspect that we're probably know numbers in Q1 a little bit better than typically when we present our earnings data a few -- 2, 3 weeks earlier. So what happened is we see a healthy March. And the impact of this seasonality and less of the working days kind of behind us. So the rate of growth, which you see is based on the lower performance of the first, let's say, 2 months of the quarter. As I was joking, would be lovely to have a Q2 4 months then you can throw all these stuff in the first 2 months of the year, but really, really healthy quarter. So the rate of growth from March on is more, I would say, traditional, which makes us more comfortable with providing the guidance like we are.

The next questions come from Mayank Tandon of Needham.

Great. Anil, you gave guidance on EBITDA for the first quarter, but not for the full year. So I just wanted to check with you, should we expect the same sort of pattern as you mentioned on revenue growth in terms of margin expansion? And do you have any sort of framework on how to think about what the levers are for margins going forward?

Yes. Thanks for that question, Mayank. So as you know, last quarter, we talked about margin expansion in 2026, right? Q4 to Q4, we talked about 300 bps. Within the company, there's several efforts right from internal productivity, right from geographic optimization, where we're working very diligently on our margin expansion. And that's largely driven by the change of our workforce over the last 3, 4 years, which you all know about. Along with that, we have investments too. Eugene is talking -- Eugene is doing some amazing work in a number of platforms he's rolling out on AI. So it's the balance between the two. So if you look at our trajectory, margin expansion, margin continuation is what we are modeling. As the revenue picks up, obviously, you have a little bit more positive leverage there on the EBITDA margins. But the cadence at which these things will play out, you will see in the course of the year, I just don't want to give that level of specificity at this point. But the trajectory should be moving upwards and in line with what we had promised last quarter.

And of course, it's not constant currency situation. So you may want to comment.

So the other important thing everyone should understand is that in '25 versus '24, there was a big headwind on FX. So if I look at the cost and revenue on a net basis, that was close to $8 million overall for me, year-to-year. If I look at the last day of '24 and compare it with what happened on '25. So we're working through that. That's another thing that we're working through.

So to summarize it, I gave you guidance, direction of 3% improvement plus. It still stays. I hope we can do better than that. There's a lot of activities happening. But we're not going to pull the plug and show artificially some numbers related to less investment into Agentic AI or the Physical Robotics AI. These elements are vital for our business, but operational efficiency, the contract efficiency, which we discussed with AI and also distributing workforce more efficiently around the globe. All the three elements. But the driver is fundamentally AI efficiency. That's really the #1 of 3. And I think, Yury wanted to...

Yes, I just wanted to comment on the same -- pretty much along the same lines as I mentioned, right, about fixed-price engagements, right, and outcome-based engagements. That's obviously come typically, with a higher margin. So that's why it's also -- it's part of this program as well. And this year, again, it will be quite substantial.

Got it. And then just very quickly, I wanted to ask about your comments around M&A, Anil. You mentioned that obviously, you have a really good balance sheet and you have the work just to go out and do acquisitions. Are you finding that with the recent market volatility, multiples have come down? Are expectations a little bit more realistic on some of the potential targets that you might have had in mind?

Yes. Somehow the private companies, they received the memo a little later than the public companies. So the memo they finally got, but it took a little time. We are having a good pipeline. Look, we've said that, but I think the number of exclusivities that we have today is as high as it's ever been. It's not done until it's done. When it comes to valuation, things have come in, they're better than what it was 6 months or 10 months ago. But it's still back and forth. Again, Mayank, the most important thing, strategic focus, strategic fit to what we're doing, especially in the AI world that we're entering. That's our bar standards are very high, and we're just not going to buy because we have to buy. We're going to do it if it's strategically fitting.

Yes. I think what Anil didn't tell you it is very obvious we're not buying revenue. This is very, very clear. The relationship we got into the exclusivity with several of the targets, they are very specific in their fashion to address two things. One is the technology components, which we need to add. And the second one is the knowledge of the verticals we would like to be strong with that. So it's not about one size fits all. It's not about just going -- swallowing a big company and report a great number, because usually, it doesn't happen like this. But it's a very specific technology plus verticals. And it seems as the message you mentioned coming from somebody who tells them, okay, now has attained their expectations, I think we're going to be in a better shape because last year, it wasn't satisfactory.

The next question comes from Logan Schuh of Jefferies.

My question revolves around your discussion of kind of moving from labor scaled IP to -- or labor scaled growth to IP scaled growth and kind of the shift from time and materials to outcome based. I'm just wondering what kind of implications that have on your plans for hiring in 2026 and beyond? And then also, where do you think the business model evolves to over the longer term? I mean we have some competitors going all in on kind of subscription-based Agentic delivery, some different competitors saying, no, we don't see it fundamentally changing. I was just wondering where you guys kind of landed on that spectrum?

Okay. So Logan, I will just say a couple of words, but I think this is a good question for a round table. It's almost like I feel like as a fire chat, not the earnings call because there are a lot of elements, which is a very loaded question because you're right, we're kind of the last of the group to kind of present our earnings results and you have -- you're full from everyone telling you something. So it will not be very difficult to tell you what we think. So look, the model has changed already. There is no way back and people who will consistently say that, A, nothing changed, or we're going to continue to build the large size of team and more people you have as merrier, will probably face some challenges, especially on the large size. Now I've been saying that for a long time, and it actually works for Grid Dynamics benefit. We're not only a technology-driven company and an innovation-driven company, we're a nimble company. Our size is fairly optimized. Obviously, there is a place for growth. But we're not having any managed services. We're not having some very low-end contracts. And some contracts which were not as progressive or technology contribution, migration all this fashion, they are falling off. And that's why you see this kind of changing of the orders in both ways. But where we see our model, and I hope Vasily will give you again a few examples, is that it's going to be a combination. So it's not the perishable goods of quality engineering. It's a combination of capabilities, trained people and the solutions we have in advance of customer needs, understanding their marketability. We continue to play our role with the partnerships. We understand deeply several key areas, and it can be expert in everything. You try to be expert in everything then you have a very kind of a shallow knowledge and you're going to struggle because you have to fill them all. The bots need to be a bit concentrated even though diversified. So where I see it's kind of a -- it's a middle ground. One thing which I give you, again, as my input may be a little bit different from others, but it kind of resonates with our clients very well. The definition of the senior engineer has changed. So traditionally, the word senior engineer means the person with many years of experience, they do less here. But today, the definition of the senior engineer means relevancy of the technology competence and a foundational acumen around their own DNA being the moderate age of AI technology. So the age limit changes, but what really changes is the depth of the knowledge of people. So the focus of Grid Dynamics will continue to be supporting the intelligence of internship programs. Grid Dynamics University Training, Grid Labs Training, combination that these fellows also contribute to building our tools, so then they can become much more productive with the clients. So summarizing my part is that somewhere in the middle ground, we're bringing the new era of the senior engineering the talent, combined with a tooling and a modern world of solving customer problems faster, more efficient and combining three elements: people, industry tools and our own platforms. And with that, Vasily, maybe you'll add some comments.

Yes, just a few comments. Imagine if the customer has a project, let's say, which is provided as a bid for fixed price. And you come and bid for that, let's say, with the pricing 25% to 35% lower than otherwise it would be delivered with a traditional workforce in the T&M manner, let's say, we're like just regular fixed price for the regular engineers. But actually, you have the productivity of 35% to 45% higher. So that's the clear path for improvement of the profitability, but how do you do that? You implement certain SDLC new processes on how you develop the software. You deploy a special team, which is very well trained, you introduce certain artifacts and assets, which would understand or would fit their vertical we are working in, also understand the coding policies, all the existing code base, et cetera, which would help developers to work to deliver higher productivity. And that's essentially like on the high-level GAIN model and what the path Grid Dynamics is going with. Essentially verticalized solution, high-performance teams, very well-educated engineers on the modern technology and delivering outcome and output based engagement.

Great. That was very clear. And then I wanted to ask about the partnerships. I know they're -- 19% of revenues were partner influenced. I just wanted to kind of get a sense of how those partnerships have evolved over time, maybe how you see them evolving in the future?

Okay. So the person who is responsible for partnerships, we will bring him in next time, it's a Rahul Bindlish and he will say we're looking okay. Who is going to say on our partnerships, right? Thank you for asking this question last because it's actually a very wide part of our growth. When a few years ago, we started talking about one partnership. We're basically exploring what it means to read the next. And starting with Google, it was great. I mean we have a great experience. We have a great partnership. We have a great positioning of understanding of the modern tools, collaboration. We have matured significantly ever since. So when we talk about the influence revenue, we're talking about our positioning where we not only contribute to the value of the clients which utilize solutions from our clients and solutions talk about cloud solutions or their modern, large language models or other features. But the elements associated how we are adding our layers, our technology know-how, our technology platforms on the top of their offering, which helps them to penetrate customers faster and helps us to understand earlier what their growth is going to be. Saying that, we also started to contribute more efficiently to their own developments, on their own products, which is very critical because that's how it drives our business, not only having our partners our vehicle for growth within industry, but is the growing clients themselves. So from there, we pretty much cover all the hyperscalers. And that's great because it means the customer has a value with Grid Dynamics to get a bespoke solution for the best fit for everyone. And this is good because ultimately, not every offering fits all, and we are very comfortable to be really good friends with the clients and fair partners with our major hyperscalers. On the top of it, we're adding more meaningful partnerships and perhaps Eugene can make one of the notable ones because I think it usually gives us a little bit more advantage to fill the gaps on the fast-growing AI implementation where the big guys allow a bit more flexibility for some specialized programs to step in. And since it's going to be probably the last time I speak where Eugene will wrap it up for you, I just want to say one thing which is important, I think, for everyone. It's going to be a good year. We believe in Grid Dynamics. We are having a strong and growing team and I really count on you guys believe in us as we do it ourselves. So thank you with that, and Eugene, please wrap it up.

Yes. Thank you, and this is a great question. And indeed, we -- as Leonard said, we are helping many of our partners to build the value-add components and penetrate new customers and new industries. One notable example is, for example, our partnership with Temporal, which is our workflow management system at its core, very robust, very scalable and very powerful. And we apply this system at scale while building enterprise agentic AI platforms, which opened quite a lot of interesting opportunities for Temporal to grow into this sector, and we help them to go into major accounts together. And now we enjoy -- it's a good partnership as well.

Thank you, Logan. Ladies and gentlemen, this concludes the Q&A session for today. I will now pass it over to Leonard for closing comments.