Good afternoon, everyone. Welcome to Grid Dynamics' fourth quarter 2025 Earnings Conference call. I'm Kerry Savas, Director of Branding and Communications. At this time, our participants are in listen-only mode. Joining us on the call today are CEO, Leonard Lifshitz, CFO, Anil Garadla, CTO, Eugene Steinberg, COO, Yuri Grislov, 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 in a financial outlook and the answers to some of your questions. Such statements are subject to the risks and uncertainty as described in the company's earnings release and other filings with the SEC. During this call, we will discuss certain non-GAAP measures of our performance. GAAP to non-GAAP financial reconciliations and supplemental financial information are provided in the earnings press release and the 8K filed with the SEC. You can find all the information I just described in the Investor Relations section of our website. I now turn the call over to Leonard, our CEO.
Thank you, Kerry. Good afternoon, everyone, and thank you for joining us today. I'm delighted to share that Green 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. The 2025 non-GAAP EBITDA was $53.8 million. In Q4, our top three 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 strengths of our accelerators, and kind 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 tilt enterprises build versus buy calculus to rebuild at a lower cost. The shift aligns with great dynamics core strengths in building solutions for Fortune 1000 companies, leveraging specialized talents 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 strengths 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 and 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, autograble, 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 manufacture. You cannot build one for a global pyramid network without understanding the compliance architecture. Such expertise is what we have been building, vertical by vertical, for nearly two decades. Now we are codifying it into platforms. Our merchandising experience platform, MXP, brings our expertise to marketplaces and digital commerce. While XTDP, our bi-temporal data platform, helps financial clients, specifically in capital markets, with auditability and other compliance challenges. Platforms are unlike IP-driven outcome-based engagements, and that's how Great 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. Such 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 and 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 partnered with a global financial leader to launch a proprietary generative AI agent supporting more than 10,000 financial advisors. This interactive experience replaces static policies with personalized guidance as it's 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 chargeback challenges, increasing win rate, and reducing operational overhead. Financial governance. At the leading US-based global bank, we're building a global agent runtime, an AI orchestration platform enabled business-focused agent to automate complex workflows, starting with successful automation in internal compliance. We also deployed 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 serves 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 game initiative and provides a governance layer for AI coding agents Rosetta automates context setup enforces consistent workflows and manages engineering knowledge at both the engineer and organization level it operates within the clients own security perimeter and works across all major coding platforms developers get consistent project aware agent behavior fraud from day one engineering leaders get centralized governance and visibility across the entire agent footprint with Rosetta clients benefit from decades of institutional expertise seamlessly embedded into their engineering workflows we have several engagements underway and a scaling gain as the standard delivery backbone across all engagements in 2026 grid dynamics operations is client zero for our AI solutions cerebra our internally developed a genetic platform launch in Q3 it is built on Google AI stack general enterprise ADK and 8way within the 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 tested in production as ai revenues ramp they 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 depth to enterprise transformation at scale the agentic era is reshaping the economics of software delivery AI native development tools are lowering 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 taking on significantly late larger mandates that means moving away from si heavy engagements and towards original in-house engineering that rotation plays directly to our strengths in the past decade enterprises have increasingly became dependent on system integration assembling software as a service ecosystems systems, configuring cloud services, and stitching together vendors' products. In the agentic era, this changes fundamentally. Production deployments require bespoke engineering, purpose-built agent workflows, domain-specific data and knowledge layers, distributed system and platform engineering. GridDynamics is well known for its engineering capabilities and proprietary IP at leading global enterprises the agentic error rewards builders and that is where we have invested our go-to-market runs two tracks for tier one enterprise clients we architect and co-develop custom verticalized ai platforms built around their specific architecture governance and compliance requirements for tier two 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 their jumpstart program this initiative positions us as a technology consultants for temporal's customers embedded in crucial article 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 we are we are leading a broad agentic AI program we have developed a rack as a 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 bill time and 60 reduction in ongoing maintenance effort with a 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 at the 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 codifying 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 this progression most clearly it began as search engineering expertise evolved into a reusable accelerator and in 2025 crossed Intel license revenue with a growing customer base across North America Europe and Latin America is deployment for a leading European luxury retailer delivered a 7% total revenue uplift and a 50% reduction in merchandising teamwork load 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 Traders require full point-in-time reconstruction of any decision. Banks deploying AI agents for trade processing, compliance, or investigations need systems that can capture precise information related to trading activities. XEDB 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. They arrive 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 Incarno, a software platform that supports the robotics industry. Incarno 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 internal AI model for robotic weld inspection well the inspection is demanding quality 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 non-negotiable. At a Fortune 10 manufacturer, we automated the conversion of CAD files to CNC machine instructions. A workflow that previously took five days now completes in hours. Greater than 90% cycle time reduction, validated in production. We will have more to share as this programs 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 it scales beyond individual engineers. MXP shows that our IP can generate revenue as software, not just as a services. XTDB gives us a technically differentiated entry into finance. Incarno opens doors in manufacturing. And our agentic practice is shifting from bespoke delivery to structured vertical offerings, where our accelerators compress time to value and our contracts increasingly capture outcups.
We are moving from labor-scaled growth to IP-scaled growth. and that transition defines our 2026 execution is that let me turn over to annual thanks Eugene good afternoon everyone we recorded for quarter revenues of 106.2 million slightly above the midpoint of our guidance range of 105 million 207 million this represents a sequential growth rate of 1.9% and the year-over-year growth rate of 5.9 percent there were 30 bips and 22 bips of FX headwinds on a sequential and year-over-year basis respectively non-gap evita was 13.7 million or 12.9 percent 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 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 dollars on a sequential basis there was a tailwind of approximately 160 000 to our ebitda as a dollar strengthened relative to the british pound and euro looking at performance of verticals retail remained our largest vertical contributing 28.7 percent of total revenues in the fourth quarter of 2025 while revenues in this vertical increased by 5.3 percent on a sequential basis there was a decline of 6.9 percent on a year-over-year basis the sequential increase was broad based across a retail customer base tmt our second largest vertical accounted for 28.3 percent of total revenues for the quarter the vertical delivered strong results with growth of 5.3 percent on a sequential basis and a 27.5 percent increase on a year-over-year basis the strong year-over-year growth was primarily driven by our top two technology customers the finance vertical accounted for 22.9 percent of total revenues in the quarter growing five percent 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 percent of our fourth quarter revenues this vertical remains stable in absolute dollars sequentially but declined 4.3 percent on a year-over-year basis the year-over-year decline was largely due to decline at some of our automotive customers and this was partially offset by our cpg customers the other vertical contributed 7.3 percent of fourth quarter revenues this remained flat on a dollar basis relative to the third quarter and grew by 8.4 percent 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 percent of the company's total headcount, versus 7.4 percent in the year-ago quarter. Our non-U.S. headcount, located in Europe, Americas, and India, was 4,604, or 92.8 percent. In the fourth quarter, revenues from our top five 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 percent compared to 35.2 million or 33.8 percent in the third quarter of 2025 and 37.6 million or 37.5 percent 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 UK-based headcount firmer acquisition of JEXT. 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 percent of revenues in the third quarter of 2025 and was down from 15.6 million or 15.6 percent 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 segments. Our gap 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 one cent per share based on a diluted share count of 85.8 million and net income of 4.5 million or 5 cents per share based on 83.8 million diluted shares in the year ago quarter on the non-GAAP basis in the fourth quarter our non-GAAP net income was 8.7 million or 10 cents per share based on 86.4 million diluted shares compared to the third quarter non-GAAP net income of 8.2 million or 9 cents 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 total $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 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 to $86 million and our diluted share count to be in the range of $87 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
Thank you, Emil. As we go into the Q&A session of this call, I will first announce your name. At that point, please unmute yourself and turn on your camera. The first question comes from Maggie Nolan of William Blair.
Hi, thank you. 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, Manga. Thank you for your kind words. Well, we extensively discuss in various forums what AI represents to Green Dynamics and what is the opportunity for us going forward. Fundamentally, what makes a big difference for Green Dynamics for 2026 on is that we're not only moving from the small development project full-scale implementation but also we introduce 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 our own tools as a new way to building the solution faster and more affordable for the clients. Perhaps some words from Eugene.
Yes 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 search, personalization, agent e-commerce is very obvious and measurable by our clients. And this is where the clients see ROIs in weeks not in months or years and that allows us 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 our customer experiences but this is a foundational layer which helps the companies to organize their data builds the agent factories on top of this data and then go into developing business agents on top of this platforms and what we see in our projects is as those platforms mature and go to production clients start to scale very very quickly are building the agents and we are helping them to develop the C agents and they're going from 1 to 10 to 20 of those specific customer facing the centralized agents very very quickly so this expands our work and allows us to move very quickly great thank you 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 we've wanted you with a bunch of
names during this press release right so we were talking about you know merchandise experience platform we're talking about by temporal database we're talking about it kind of being a robotics AI plot form subsequent growth of the Rosetta it's automation within gain model the platform against the celebra which is kind of celebra which is picks up a lot of internal process bringing Green Dynamics as a client zero 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 on the market of clearness what to do, but when you work with Green 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 Green Dynamics as a mix between Green Dynamics trained engineers, the standard tools and platform from the market, and customized tools which we 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 time and material offering where we're putting together a contribution based on client outcomes, which ultimately leads not only for them to gain momentum and have a better financial return, but a higher value add for the market. and expansion for grid banks. Those are three elements.
Thank you. Nice quarter. Thank you. Thanks, Mike.
Operator
Thank you, Maggie. The next question comes from Brian Bergen of TD Cowan. Go ahead, Brian.
Good to see you. Thanks for taking the questions here. The first one I'll ask you at a high level. So just with everything that's going on in the market, services, software-based pressure, the whole kind of satspocalypse 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, you know, 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. 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 on the market. But what's the custom part is, is that creation of the tools and solutions, having our internal platforms, makes RedoLynX much more efficient to really customize solutions for the individual clients and tasks. And the reason why we're doing this is because it's very nice from the high-level perspective to look at these all wonderful models, but it's experimentation going to production that's quite pricey. And many of the clients are hesitant to throw a lot of money without clear outcome. And that's where GridDynamics comes in with a 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 potentials and decline of the needs, the company like GridDynamics needs is actually growing. And I will have Vasilya to bring some examples. Sure.
Thank you for the question, Brian. You are right on point. We definitely see increased demands for 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 as you'll see, 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 traditionally were outside of the investment areas for the companies, for the clients.
Okay. Okay, that's helpful. Another follow-up, I want to dig in on the growth outlook for the year and unpack it a bit. Neil, 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 bill 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?
Yeah, Brian, 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 is 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've provided, it's a little wider, right? Relative to last year, you know, we made it a little wider because we understand that during the course of the year, There's some positives. There's not some positives. So we kept it a handy range.
So let's be more specific, right? So I think Anil answered a very simple question about Q1. It's actually a very substantial reduction of the working days. So it's not something like normally happened in a traditional year. But there is a bullish outlook for a very simple reason. The pace of adoption of AI solutions and AI applications, like Redynamics customers, clear outpaces the decline of maybe a little bit more edged retail business. It happens simultaneously and is no secret because if you look at the rate of growth of our client verticals, you can see two notable changes. It's a tech 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 in AI-related businesses, the contribution from our partnerships, the improved our 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 traditional aged business which been there for years we came up with a bullish but conservative outlook and what's the conservative part of that I think it's very important to understand we've learned a little bit of our lesson from 2025 right I mean we 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. You know, follow the sound 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 delivered variability of Q1, we do not get you guys' question, are we sane or not? We are very sane.
All right, that's clear. Thank you, guys.
Operator
Thank you. Thank you, Brian. Thank you, Brian. The next question comes from Kunit Jain of JPMorgan. Go ahead, Kunit.
Hey, thanks for taking my question. So given like the recent news flow around entropic cloud, 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 great gain framework, and 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 their clients in terms of productivity savings?
Very good. Well, let's start with, again, Vasilya is the last time to give a little bit more of the multi-layer approach and then from the technology perspective, I think Eugene can comment as well.
So, yeah, maybe let me start with, again, framework. So, as you know, we announced it in the middle of 2025, and during the six 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 game 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.
Yes, and when it comes to the actual improvements which we are seeing from agentic coding assistants and Claudie and Courser and all the kind of others, of course, many of our customers are embracing it and we are bringing those capabilities with GAN together with Rosetta, which is a layer on top of it. We are not competing with those agentic assistants on the foundational layer, but we are making them better, stronger, and embed our own institutional knowledge into those assistants 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, migration, you still have a very strong improvement because the agents 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 is when it's much more challenging to realize the improvements from pre-recording and creation of artifacts. 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, and I mentioned several times in our prepared remarks as well. I think this transition from TNM-based approach to outcome-based and output-based, it's very important to emphasize because this is definitely real. We see that a lot. It happened, you know, during the 2025 and 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.
Got it. And let me ask like follow up to Brian'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 five, five and a half percent 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 five, five and a half percent sequential growth beyond Q1 to get to the midpoint of full year number?
I'll make a comment and of course, we'll have Anil to back it up with the numbers. As I mentioned to Brian, we took very seriously to make sure that we are reasonable but conservative in our radio. It is I'm sorry. Okay. The pipeline is very robust. And the pipeline which we have right now, not only robust but it shows quite opportunity with AI related products and projects across multiple verticals and multiple There's always a seasonality, right? So Q2 is better than Q1, and Q3 is better than Q2, and then Q4 may have some additional forlows, like what happens in Q4 last year, and all this stuff. But we kind of desegregate the seasonality and behavior from adoption of AI. And we look at our pipeline as it stands today. So there's a very little assumption for you that there is going to be some enormous number of white swans or some Hail Mary or something extraordinary or great happens during the course of the year. Obviously, not everything on the books today, but the 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 coming quite robustly as well. And we see that adoption, as again Brian asked before, of the custom-developed solution on a combination of the deployed engineers and trained program and our internal tooling brings us much higher acceleration. So the same people, the same trained capacity of the people can have several terms of the execution during the year. That's kind of the high level but very clear understanding what does that pipeline mean. But maybe Anu will back it up with some numbers.
Yeah, 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 variations this year. We understand, you know, 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 2016, 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, Puneen, 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 a year end. So we are in March. So you can suspect that we probably know numbers in Q1 a little bit better than typically when we present our earnings data a few, two, three 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 two months of the quarter as I was joking would be lovely to have a Q2 four months then you can throw all this stuff in the first two months and you have a 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.
Operator
Thank you. Thank you, Paneet. Thank you. Thank you, Paneet. The next questions come from Mayunk Tandem of Needham. Go ahead, Mayunk.
Great. Thank you. Good evening. Anil, you gave guidance on EBITDA for the first quarter, but not for the full year. 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?
Yeah. Thanks for that question, Mike. So, as you know, last quarter, we talked about margin expansion in 2026, right? Q4, we talked about 300 bps. Within the company, there's several efforts, right from internal productivity, right from the 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 three, four years, which you all know about. Along with that, we have investments too. Eugene is talking. Eugene is doing some amazing work with 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, you know, 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, you know, year to year. If I look at the last year of 24 and compare 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, a direction of 3% improvement plus. It still stays. I hope we can do better than that there's a lot of activities happen 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 number one of three. And I think, Yuri wanted to...
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, you know, with a higher margin. So that's why it's also part of this program as well. And this year, again, this will be quite substantial.
Got it. And then just very quickly, I wanted to ask about your comment around M&A. Anil, you mentioned that, you know, 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 till it's done. When it comes to evaluation, things have come in. They're better than what it was six months or ten months ago. But it's still a back and forth. Again, 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 it because we have to buy it. We're going to do it if it's strategically fitting.
Yeah, I think what Anil didn't tell you 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 strongly at. So it's not about the one size fits all. It's not about just following 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 the somebody who tells them, okay, now it's going to attain their expectations, I think we're going to be in a better shape because last year it was dissatisfactory.
Great. Thank you so much.
Operator
Thanks. Thank you, Maya. The next question comes from Logan Hsu of Jefferies. Go ahead, Logan.
Hi, guys. My question revolves around your discussion of kind of moving from 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 the 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 egenic delivery, some different competitors saying, no, you know, 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 words, but I think this is a good question. for a round table. It's almost like a fire chat, not an 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 earful from everyone telling you something. So it will not be very different. We'll 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 are we going to continue to build the large size of the team and more people you have as merrier, will probably face some challenges, especially of the large size. Now, I've been saying this for a long time, and it actually works for Green Dynamics' benefit. We're not only a technology-driven company and innovation-driven company, we're a nimble company. You know, our size is fairly optimized. Obviously, there's 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, and all this fashion, they are falling off. And that's where you see this kind of changing of the order in both ways. But where we see our model, and I hope Lucila will give you 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 you can be an expert in everything. You try to be an 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 bats need to be a bit concentrated even though diversified. So where I see it's kind of a middle ground. One thing which I give you again as my input may be a little bit different from others but it's kind of resonates with our clients very well. The definition of the senior engineer has changed. So traditionally the The word senior engineer means the person with many years of experience, maybe less But today the definition of the senior engineer means relevancy of the technology competence and the foundational acumen around their own DNA within the modern 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 lab training, combination that these fellows also contribute to building our own 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 the 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 questions.
Yeah, just a few comments. Imagine if the customer has a project, let's say, which is provided as a bid for a fixed price. And you come and bid for that, let's say, with a 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 with the regular engineers. But actually you have the productivity 35% to 45% higher. So, that's the clear path for improvements 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 the vertical we are working in. Also understand the coding policies, all the existing code base, and et cetera, which would help developers to deliver higher productivity. And that's essentially on the high level what GAIN model and what the path Grid Analytics is going with. Essentially, verticalized solution, high-performance teams, very well-educated engineers on the modern technology, and delivering outcome and output-based engagement.
Thank you. That was very clear. and then I wanted to ask about the partnerships I know they were 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 We'll bring him in next time.
It's Rahul Bindlish, and that's where we're looking. Okay, we're going to send one thought message, right? Thank you for asking this question, Les, because it's actually a very vital part of our growth. You know, when a few years ago we started talking about one partnership, we're basically exploring what it means to read the names. 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. solutions, talk about cloud solutions or their modern large language models or the features. But the elements associated how we are adding our layers, our technology know-hows, our technology platforms on 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, of 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 as the growing clients themselves. So from there we pretty much covered all the hyperscales And that's great because it means the customer has a value with great dynamics to get a bespoke solution for the best fit for everyone. And this is good because ultimately not every offering fits at 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 a 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, because 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 Green Dynamics. We are having a strong and growing team. And I really count in you guys believing in us as we do in ourselves. So thank you for that. And Eugene, please wrap it up.
Yes, thank you. And this is a great question. And indeed, we, as Dan said, we are helping many of our partners to build value-add components and penetrate new customers and new industries. One notable example is, for example, our partnership with Temporal, which is a workflow management system at its core. Very robust, very scalable, and very powerful. and we applied 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 helped them to go into major accounts together and now we enjoy a pretty good partnership as well.
Operator
Thank you. 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 upscale 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 enter the next phase of our journey with a clear roadmap 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
