GDYN 2025Q4

Good afternoon, everyone. Welcome to Grid Dynamics Fourth Quarter 2025 Earnings Conference Call. I'm Cary Savas, Director of Branding and Communications. Joining us on the call today are CEO, Leonard Livschitz; CFO, Anil Doradla; CTO, Eugene Steinberg; COO, Yury Gryzlov; and SVP, 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 risks and uncertainties as described in the company's earnings release and other filings with the SEC. During this call, we will discuss certain non-GAAP measures of our performance. GAAP to non-GAAP financial reconciliations and supplemental financial information are provided in the earnings press release and the 8-K filed with the SEC. You can find all the information I just described in the Investor Relations section of our website. I'll now turn the call over to Leonard, our CEO.

Thank you, Cary. Good afternoon, everyone, and thank you for joining us today. I'm delighted to 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 customers 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. Enterprises are learning that deploying AI at scale requires deep domain expertise. We cannot build an effective Agentic system for a production floor without understanding manufacturing. 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 two 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-influenced revenue reached a significant milestone in 2025, exceeding 19% of our total revenue. This 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 and 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 agents 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.

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 sources 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 manages 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 one. 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 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 to decrease, 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, taking 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 become dependent on system integration, assembling Software-as-a-Service ecosystems, configuring cloud services, and stitching together vendor products. In the Agentic era, this changes fundamentally. Production deployments require bespoke engineering, purpose-built agent workflows, specific data and knowledge layers, distributed systems, 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 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 a 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 a 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 and 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, 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 engineers are 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 the industrial and manufacturing environment. Our flagship platform here is Incarna, a software platform that supports the robotics industry. Incarna dramatically compresses the 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 is high inspection consistency, improved quality assurance and scalable automation in environments where precision is non-negotiable. 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, resulting in a greater than 90% cycle time reduction, validated in production. We will have more to share as this program scales. As we look ahead, we will build on our foundations. We are rapidly and deliberately scaling toward a multi-industry AI-led business transformation. GAIN and Rosetta codify our engineering judgment so it 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. Our Agentic practice is shifting from 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 the 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. 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 clients. And finally, health care and pharma contributed 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. 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 enhance 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.

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 your 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. 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 affordably 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. Clients see ROIs in weeks, not in months or years. This allows us to expand those accounts very quickly based on these successes which we see in this domain. The second is enterprise AI platforms, which are not as visible as front-end work or AI-powered customer experiences. However, 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. What we see in our projects is as those platforms mature and go to production clients start to scale very quickly building AI agents. We are helping them to develop the AI agents, and we are going from 1 to 10 to 20 of those specific customer-facing agents very quickly. So this expands our work and allows us to move rapidly.

Great. And then anything else you would comment on as you move into 2026, how you expect the trend to evolve in 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? We were talking about merchandise experience platform, we were talking about bitemporal database, we're talking about Incarna robotics AI platform, subsequent growth of the Rosetta, its 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 about what to do. 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 an important contribution for Grid Dynamics as a mix between Grid Dynamics trained engineers, standard tools, and platforms from the market and customized tools, which we 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. Second, it moves away from our traditional talent material offering where we're putting together contributions 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 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 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. 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 that 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. There are more tools available in the market, but what's custom is the creation of the tools and solutions. Having our internal platforms makes Grid Dynamics much more efficient to customize solutions for individual clients and tests. We recognize that even though there is an overall look that there are potential declines of the needs, Grid Dynamics actually grows, 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 for our custom-built software. If in the past, customers were looking into improvements or enhancing their core platforms, now, given the cost of development getting reduced by utilizing an AI-native environment and SDLC, companies like Grid Dynamics definitely benefit from this trend by getting involved in implementations and rebuilding typically SaaS applications into custom-built, more tailored solutions for end customers like HR systems or travel dashboards, etc., which were traditionally outside the investment areas for the clients.

Okay. Okay. That's helpful. And then a follow-up. I want to dig into 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 Q1 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 were fewer working days relative to Q4. So that's a very simple point. Now you're absolutely right. We are positive on how we're looking at the full year. There are two components. One is that some of the recent trends in our pipeline growth. The second thing is all the gentlemen that have spoken about on our AI trends. I'll let them build up on that. But where we are today, how we look at the year, we feel more positive. The final thing is that if you look at the range I provided, it's a little wider relative to last year. We made it a little wider because we understand that during the course of the year, there are some positives and some not so positive events, so we kept it a healthy range.

So let me be more specific, right? Anil answered a very simple question about Q1 and it's a very substantial reduction of the working days. So it's not something that normally happens traditionally here. However, there is a bullish outlook for a very simple reason: The pace of adoption of AI solutions and applications by Grid Dynamics customers clearly outpaces the decline of maybe a little 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 notable changes. The tech and financial verticals are growing specifically in fintech and capital markets, which is quite new for us. When we look at the total equation, the rate of growth and AI-related businesses, the contribution from our partnerships, and our improved performance in terms of new types of agreements, we came up with a bullish but conservative approach. It's crucial to understand the revenue dollars that are coming with the customers. As our business grows, we also deploy our engineering talent globally in a follow-the-sun strategy, and different regions have different price points.

Given the recent news flow around Entropic Claude, are you seeing any changes in your client behavior, increased urgency among your clients to embrace AI? And second, I know you talked about the GAIN framework. I know it's built on proprietary as well as third-party tools. So does the evolution of the AI ecosystem 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 bit more of the multilayered approach. Then from the tech perspective, I think Eugene can comment as well. So, Vasily, please.

Yes. Let me start with the GAIN framework. As you know, we announced it in the middle of 2025. 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 part of this platform. I would say in 2026, we see this will be the year of rapid adoption of the GAIN platform across our customers. In fact, it became the de facto standard approach for our output-based engagements, essentially decoupling billable headcount from revenue growth. We definitely see performance improvements, and we transfer some of that to our customers, contributing to our improved profitability.

Yes. When it comes to the improvements we see from Agentic coding systems and Claude and others, many of our customers are embracing it, and we are bringing those capabilities with them together with Rosetta. They are not competing with those Agentic Assistance on the foundational layer, but we are making them better and stronger and embed our own institutional knowledge in those systems with every engagement. Of course, the impact of that very much depends on the actual nature of the project. For greenfield POC solutions, your gains are immense, like 10 times compared to traditional ways because you are creating in an unconstrained environment. In brownfield projects, you still see strong improvements because the agents are tools and do things much faster for you. However, in engagements and environments where the complexity is in communication or orchestration, realizing improvements from pure coding and the creation of artifacts is much more challenging.

Just quickly to add to what Eugene and Vasily mentioned, I think it's vital. We mentioned several times in our prepared remarks. The transition from T&M-based approaches to outcome-based engagements is essential. We see that happening during the transition from 2025 to 2026 and expect many more of those engagements going forward. Our GAIN framework, together with verticalized solutions and the platforms we leverage, will be very important this year.

Okay. Got it. Let me ask a follow-up to Bryan's question on the rest of the year beyond Q1. Based on our math, it seems like the full year guidance at its midpoint implies about a 5% to 5.5% sequential growth beyond Q1. Can you disaggregate that? What drives that growth in terms of pipeline, billing days, etc.?

Puneet, let me summarize and, of course, we'll have Anil back it up with the numbers. We take our forecasting seriously. The pipeline is robust and shows great opportunity with AI-related products across multiple verticals and clients. There is always seasonality, right? So Q2 is typically better than Q1, and Q3 better than Q2. We can disaggregate the seasonality and behavior from the adoption of AI. Our pipeline as it stands today has a very little assumption that some enormous number of white swans or Hail Mary happens during the year. The majority of what is on our books today is strong. Our own tools and accelerators are going to continue to roll out during the year, leading to growth.

Look, I think the key thing is what Leonard said. We look at the revenues from a bottoms-up and a top-down perspective. What we have as we transition from 2025 to 2026 is the AI factor. When we looked at that AI revenue kind of bottoms-up, top-down and the trajectory, I wish I could give a specific number, but it's healthy as we go into 2026. As we move from high to low, we bake in conservativeness with large clients, depending upon how we look at business today. But this is top-down and bottoms-up with some conservativeness. However, in 2026, the fundamental difference is that we have this AI trajectory along with the fastest-growing segments, TMT and financial verticals. That's key.

To summarize, Puneet, it may mathematically seem aggressive, but realistically, this is an unusual quarter to report. We will have healthy March. The impact of seasonality and fewer working days is behind us now. The rate of growth which you see is based on the lower performance in the first couple of months. As I said jokingly, a 4-month Q2 would be lovely, allowing us to push through the things that happened in the first two months. Regardless, it's a really healthy quarter.

Anil, you gave guidance on EBITDA for the first quarter, but not for the full year. Should we expect the same sort of pattern as you mentioned on revenue growth in terms of margin expansion? 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. As you know, last quarter, we talked about margin expansion in 2026. We talked about 300 bps improvement. There are several efforts from internal productivity, geographic optimization, and we are working diligently on our margin expansion. That's largely driven by the change of our workforce over the past few years. We also have investments. Eugene is doing some amazing work in rolling out platforms on AI. So it’s a balance between the two. Revenue pick up and improved EBITDA margins will be modeled throughout the year; however, I won't provide that level of specificity yet. The trajectory should move upwards in line with previous guidance.

And it's not a constant currency situation, which you may want to comment on.

The other important thing is that there was a significant headwind on FX in 2025 versus 2024. If I look at the cost and revenue on a net basis, that was close to $8 million overall year-to-year. We're working through that as well.

To summarize, I gave you guidance for a direction of 3% improvement plus. I hope we can do better than that. There's a lot happening, but we will not artificially inflate reported numbers by reducing investments into Agentic AI or Robotics AI. These elements are vital for our business, but operational efficiency, contract efficiency will all play a part. AI efficiency will fundamentally drive margins.

I just wanted to comment on the same lines. This pertains to fixed-price engagements and outcome-based engagements that typically come with higher margins. That’s also part of this program as well.

Got it. Just very quickly, I wanted to ask about your comments around M&A. You mentioned you have a really good balance sheet and you're set to go out and do acquisitions. Are you finding that with the recent market volatility, multiples have come down? Are expectations more realistic on some of the potential targets?

Yes. Private companies received that memo a bit later than public companies, but we're having a good pipeline. We've mentioned that, and the number of exclusivities we have today is as high as it's ever been. It's not done until it's done. Valuations have come in, and they are better than they were six months or ten months ago, but it's still back and forth. The most important thing for us is strategic focus and fit.

We are not buying revenue, this is very clear. The relationship with the targets is focused specifically on technology components that we need to add and the knowledge of the verticals we want to be strong in. It’s about technology plus verticals. The message coming from those conversations allows us to be in a better shape than last year.

My question revolves around your discussion of moving from labor-scaled growth to IP-scaled growth and the shift from time and materials to outcome-based. I'm just wondering what kind of implications that has on your plans for hiring in 2026 and beyond. Where do you think the business model evolves over the longer term?

Okay. Logan, this is a very loaded question. The model has changed already, and people who will consistently say nothing has changed will face challenges. Our size is optimized. There is a place for growth, but we are not having any managed services or low-end contracts. Our changing orders reflect this. We see the model as a combination of capabilities, trained people, and solutions that meet customer needs more effectively.

Yes, just a few comments. Imagine if you have a project offered as a bid for fixed price. You bid at 25% to 35% lower than if delivered with traditional time and materials workforce while achieving 35% to 45% higher productivity. This is a clear path to improve profitability, achieved by implementing certain SDLC new processes, deploying specialized teams, and introducing artifacts that fit industry verticals, enhancing developer productivity.

The model is not just about individual contributors. It’s backed by IP, Rosetta, MXP, XTDB, and documented patterns from deployments. The client benefits from immediate expert deployment without a learning curve. We are actively shifting our focus from labor to IP, and this transition is essential for our future execution. Thank you for your question. The partnerships we have with key players are strong and fruitful. Our partner-influenced revenue has significantly grown to over 19%, which reinforces our position in modern enterprise infrastructure. Our partnerships have matured significantly, especially with hyperscalers, contributing to both our growth and theirs. These partnerships are key to our strategy.

As for the partnerships, we help many partners build value-add components and penetrate new customers and industries. One notable example is our partnership with Temporal, which is robust and scalable, opening interesting opportunities in key accounts.

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.

This quarter, we demonstrated that AI first transformation is delivering real measurable value. We continue to upskill our talent and embed AI-driven efficiencies through platforms. By running our AI first operational models, we are proving the same value proposition we advocate for our clients. We entered the next phase of our journey with a clear road map, a future-approved workforce, and a steadfast commitment to deliver long-term value for our shareholders. Thank you, and we look forward to updating you on our continuous progress.