Grid Dynamics (GDYN) Q3 2026 Earnings Call Transcript

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DATE

Thursday, Oct. 29, 2026

CALL PARTICIPANTS

• Director of Branding and Communications - Cary Savas
• Chief Executive Officer - Leonard Livschitz
• Chief Financial Officer - Anil Doradla
• Chief Technology Officer - Eugene Steinberg

TAKEAWAYS

• Revenue -- $114.3 million, exceeding the high end of management guidance due to record AI-related contributions and demand from the Technology, Media and Telecom (TMT) vertical.
• Non-GAAP EBITDA -- $22.9 million, representing a record 20% margin and surpassing expansion goals a quarter early through cost improvement initiatives and AI-driven productivity.
• AI-Related Revenue -- 31% of total revenue, representing a 45% year-over-year growth rate for the third consecutive quarter as exploratory projects transitioned into production.
• TMT Vertical Revenue -- $37.0 million, accounting for 32.3% of total revenue and growing 29.3% year over year because of higher demand from major technology clients.
• Retail Vertical Revenue -- $31.1 million, contributing 27.2% of total revenue with 13.3% year-over-year growth driven by demand from specialty and home improvement retailers.
• Finance Vertical Revenue -- $25.7 million, representing 22.5% of total revenue and increasing 3.9% sequentially behind ongoing demand from global capital market customers.
• Headcount -- 4,559 employees, an 8.3% decline year over year as the company optimized nonengineering functions and increased automated recruitment and operations.
• Revenue Per Employee -- Exceeded $100,000 for the first time, signaling a decoupling of revenue from headcount as the company transitions to platform-based and fixed-price engagements.
• Non-GAAP Gross Margin -- 40.6%, an expansion of 370 basis points sequentially driven by improved resource utilization and efficiencies with nonbillable resources.
• Fourth Quarter Revenue Guidance -- $113.5 million to $115.5 million, reflecting a positive backdrop for multiquarter production programs entering 2027.
• Fourth Quarter Non-GAAP EBITDA Guidance -- $20 million to $22 million, supported by systematic changes in operational delivery and disciplined expense management.
• AI Training -- 93% of engineers, surpassing the company's goal of ensuring the technical workforce is trained on AI software development life cycle (SDLC) tools.
• Cash and Cash Equivalents -- $304.3 million, providing capital for management's stated objective of evaluating larger and more strategically impactful acquisition targets in 2027.
• Share Repurchase Program -- $6.7 million for 0.9 million shares during the quarter, bringing total buybacks to $37.5 million of the $50 million authorization.
• Non-GAAP Diluted EPS -- $0.18, compared to $0.09 in the prior-year period.
• Top Customer Concentration -- 63.3% of revenue from the top 10 customers, up from 58.3% in the previous year due to vendor consolidation at large accounts.
• Compliance Automation -- Sanctions research and alert prioritization tools reduced transaction screening time by 70% and false positives by 90% for a global payment client.
• Bank AI Adoption -- An AI workspace used by 180,000 employees at a global bank was enhanced with autonomous agent capabilities and centralized cost analytics.
• Physical AI Initiatives -- Three new robotics partners were added in the third quarter, focusing on industrial applications such as welding automation and autonomous vehicles.

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RISKS

• Doradla stated, "As we go into Q1, you have seasonal, that is the lowest margins every quarter... in the whole year," noting a historical trend in the company's financial performance.

SUMMARY

Grid Dynamics Holdings, Inc. (NASDAQ:GDYN) reported a structural transition in its business model during the third quarter earnings call, emphasizing a decoupling of revenue growth from headcount expansion. Management reported that this shift was facilitated by a higher mix of AI-native delivery and fixed-price projects, which allowed for the monetization of intellectual property alongside engineering talent. The company reported record revenue and EBITDA while increasing its footprint in the technology and financial services sectors through vendor consolidation. Strategic efforts in 2027 are expected to focus on scaling operations through larger acquisition opportunities and the further integration of physical AI and robotics capabilities across global facilities.

• CEO Livschitz stated, "The commercial headline is clear. The AI-native model is validating its economics."
• The company launched a business consultancy practice focused on linking high-level AI strategy with implementation roadmaps rather than general management advisory.
• Management introduced the "software factory" concept, utilizing the GAIN platform to rebuild affected components quickly when project scopes change.
• CTO Steinberg noted, "When something unexpected comes up, the factory rebuilds affected components quickly and reliably, so that the project becomes more flexible and easier to manage and control."
• The company reported its first intralogistics humanoid deployment is on track for delivery at a global pharmaceutical client.
• CEO Livschitz noted that internal AI tools are transforming nonengineering functions such as recruitment, RFP responses, and finance, enabling the company to manage more client relationships with fewer people.

INDUSTRY GLOSSARY

• Agentic AI: AI systems designed to act autonomously as agents to complete complex, time-consuming tasks with minimal human intervention.
• AI SDLC: Artificial Intelligence Software Development Life Cycle, the integration of AI tools throughout the process of designing, developing, and testing software.
• Fixed-Price Projects: Engagements where the client pays a set fee for specific outcomes, allowing the service provider to benefit from increased delivery efficiency.
• GAIN: Grid Dynamics Artificial Intelligence Nexus, a proprietary platform containing reusable engineering components and AI accelerators.
• MuJoCo: Multi-Joint dynamics with Contact, a physics engine used for advanced robotics research and simulation.
• NVIDIA Isaac Sim: A robotics simulation application used for developing and testing AI-based autonomous machines.
• Physical AI: The application of artificial intelligence and machine learning to physical hardware, such as industrial robots and autonomous vehicles.
• TMT: Technology, Media, and Telecommunications, a core business vertical for the company.

Full Conference Call Transcript

Cary Savas: Good afternoon, everyone. Welcome to Grid Dynamics' third quarter 2026 earnings conference call. I'm Cary 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 Livschitz, CFO Anil Doradla, and CTO Eugene Steinberg. 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'd like to remind everyone that today's discussion will contain forward-looking statements. This includes our business and financial outlook and the answers to some of your questions. Such statements are subject to the risks and uncertainty as described in the company's earnings release and other filings with the SEC.

During this call, we will discuss certain non-GAAP measures of our performance. GAAP to non-GAAP financial reconciliations and supplemental financial information are provided in the earnings press release and the 8-K filed with the SEC. You can find all the information I just described in the investor relations section of our website. I now turn the call over to Leonard, our CEO.

Leonard Livschitz: Thank you, Cary. Good afternoon, everyone, and thank you for joining us today. Q3 2026 was a pivotal quarter with record financial results. Revenue of $114.3 million is the highest in our history and came in above the high end of our guidance range and well ahead of Wall Street expectations. Non-GAAP EBITDA was $22.9 million, also a record. Our efforts are paying off. We are growing faster, more profitable, and in the verticals and applications where AI enterprise spend is centered. We enter the fourth quarter with confidence and with a scalable client demand, setting a positive backdrop for 2027. In the third quarter, our AI revenues grew by 45% on a year-over-year basis.

This marks the third consecutive quarter where our AI revenue has grown over 45% on a year-over-year basis and is now approaching 32% of our total revenue. Companies that recently initiated AI exploratory projects are now signing multi-quarter production programs with us. Last quarter, I set a goal, 90% of our engineers trained on AI SDLC by the end of October. I'm happy to report we're currently at 93% and continue to expand. Grid Dynamics has always been a technology-first engineering company, and investing in our people ahead of client demand is simply how we operate. Going forward, I'm optimistic about our revenue growth trajectory, and that optimism is grounded in the structure, not sentiment.

As we look in 2027, we expect to revert to healthy double-digit growth and sustain that momentum over the following years. Our AI revenue is compounding on an even larger base. As it approaches and exceeds 40% of our total revenue, the growth rate of the overall business will increasingly reflect the growth rate of the AI practice. Our AI-based GAIN solutions continue to grow. We generate more revenue per headcount at an accelerated pace. We expand our physical AI and capital markets offerings, and our hyperscaler and NVIDIA partnerships create a co-sell motion that complements our direct sales. Altogether, they are the reasons to be optimistic.

We committed to 300 basis points of margin expansion in the fourth quarter of 2026 over the fourth quarter of 2025, and we exceeded our goal a quarter early. The structure drivers are a greater mix of AI projects, higher billing rates, optimal location strategy execution, and disciplined OpEx management. These margins represent a new norm, and in 2027, we'll continue to execute on the same operating framework. One of the most important trends in our business this year is the growing revenue per employee. In the third quarter, we exceeded $100,000 for the first time. Let me remind you that this is based on a total headcount and not just billable engineers.

In the second quarter, revenue grew 7% year-over-year, with headcount declined 3.5%, a divergence of more than 10 percentage points. In the third quarter, the gap widened further. Revenue grew 9.7% year-over-year, while headcount declined 8.3%, a divergence of 18 percentage points. We believe this is one of the strongest headcount-to-revenue decoupling metrics in the IT services industry today. These diversions reflect systematic changes across how we run our operations and deliver to our clients. Internally, AI tools are transforming every non-engineering function. Recruitment, RFP responses, knowledge management, finance, and HR. We are processing more candidates, responding to more proposals, and managing more client relationships with the same or fewer people.

Doing more with less is becoming the signature of every AI-native program we run. Beyond operations, the shift toward platform-based, fixed price, and output-based engagements means we're monetizing intellectual property alongside the headcount. When clients engage with our GAIN platforms, they get a combination of talent, processes, and IP. As such component of our revenue grows, the link between headcount and revenue weakens by design. In a sector where headcount and revenue have historically moved in lockstep, Grid Dynamics is demonstrating that the two can and should be decoupled. Now about AI-native delivery. 12 months ago, AI-native delivery was the direction we were heading toward. Today, it's how we deliver. A few examples.

At a leading global technology company, we secured a large AI-native fixed price project. At one of the largest food distribution company in the world, we delivered a production solution in half the planned time with 40% fewer engineers. At a leading global technology platform, an agentic solution reduced defect review time from 30 days to four hours. Our GAIN platforms are deployed across multiple active projects, and our embedded engineers arrive with codified IP that clients are paying premium for. The commercial headline is clear. The AI-native model is validating its economics. Our CTO will take you deeper into the technology progress in a moment. Our vertical diversification continues to reshape the composition of our business.

Technology and financial services now dominate our top account relationships. The retail exposure that once defined our revenue mix is now smaller, and we are less dependent on them for growth. The growth engine of the business is firmly in the sector where AI adoption is accelerating, and this is precisely where we have concentrated our investments and our talents over the past few years. Our capital markets practice is growing rapidly, with expanding teams across U.S., U.K., and India. In manufacturing and supply chain, a leading global energy infrastructure company selected us for AI-native application modernization. A major automotive part retailer is expanding its modernization program.

A leading global construction and industrial equipment manufacturer is advancing from a discovery to implementation autonomous system program. In physical AI, our first intralogistics humanoid deployment is on track for delivery at a global pharmaceutical company. The last couple of years have been a period of transition and execution as the company focused on growing revenue, enabling AI expertise, and improving margins. During this time, our targeted approach to capability-driven acquisition in capital market and robotics served us well. We will enter 2027 in a stronger position. The business is growing, margins are expanding, and strategic clarity we have built around AI-native delivery, productized engineering, and physical AI gives us a sharper lens for evaluating acquisition targets.

We are acquiring capability, domain knowledge, and engineering depth that either accelerates an existing practice or opens a new one. In 2027, our focus is on building a pipeline of larger and more strategically impactful opportunities. After two years of disciplined execution, we are ready to acquire larger companies in 2027. During the quarter, Grid Dynamics delivered some notable projects. For a leading global technology company, Grid Dynamics built the data foundation for the launch of a new subscription package that brings together multiple online services as a bundle.

The new system enables accurate tracking of the entire subscriber life cycle, including acquisition, retention, churn, and transition between subscription offerings, while ensuring reliable revenue attribution and engagement analytics across multiple services. Delivered in time for the global launch, the engagement involved modernizing interconnected production data pipelines, ensuring data accuracy at scale, and establishing a scalable foundation for additional subscription models. The solution provides the critical analytics and financial reporting capabilities needed to support the successful launch of the new bundle offering across more than 100 markets, serving millions of subscribers worldwide. For a leading U.S.-based global bank, Grid Dynamics continued expanding the enterprise AI platform that powers AI-driven productivity and automation across the organization.

This quarter, we delivered new capabilities that enable employees to launch long-running AI agents directly from their AI productivity workspace, as well as a centralized service analytics platform that provides management with detailed visibility and control over AI adoption, access permissions, and costs. These innovations enable employees to delegate complex, time-consuming tasks to AI agents, freeing up their time to focus on higher value work, while giving management greater transparency and control over AI operations at scale. These enhancements extend the capability of an AI workspace used daily by more than 180,000 employees across the bank.

For a leading global payment company, Grid Dynamics modernized its core financial crime prevention platform, introducing machine learning, fraud detection models, self-service anti-money laundering capability, and agentic AI tools for sanctions research and alert prioritization. The modernized platform now screens approximately 14 million cross-border transactions annually for financial crime, which is 20% increase year over year, while reducing screening time per transaction by nearly 70%. Compliance false positives dropped by more than 90%, significantly reducing unnecessary manual reviews. AI power automation saves compliance analysts more than 1,200 hours annually, while self-service capability enable teams to launch new ML rules in minutes instead of weeks. The platform also achieved 99.99% availability, supporting reliable continuous payment process.

For an advanced humanoid robotics company, we are leading simulation effort using NVIDIA Isaac Sim and Google DeepMind MuJoCo. We are focused on advanced physics-based simulation to refine complex articulated movements for industrial applications such as welding automation. Leveraging our broader robotics capabilities, our technical scope quickly expanded into autonomy and manipulation architecture. Next, we plan to extend our engagement by helping the robots better perceive their surroundings and develop more dynamic movements. With that, let me turn the call over to our CTO, who will present our exciting technology offerings and AI-driven innovations. Eugene?

Eugene Steinberg: Thank you, Leonard. Good afternoon. Leonard described revenue decoupling from the headcount. Let me show you the engineering behind this process. The mechanism is transition to fixed price projects and AI native delivery for billable work, and doing more with less by using AI for our internal productivity. It all comes down to one idea, the software factory powered by our GAIN platforms. On every client project, we start by building a software factory, which is a client-specific harness for general-purpose AI coding agents. Since this factory does much of the heavy lifting, this allows a smaller team to deliver a large scope. Most importantly, it makes change cheaper. Such a factory approach makes projects shorter and more predictable.

At the end of the day, this is what allows us to commit to a fixed price project in a face of scope uncertainty. Every fixed price project starts half understood and half specified, but much of the detail only emerged during delivery, including problems nobody could predict. In traditional delivery, this risk is covered by padding the timeline and team size. The factory changes the situation. First and foremost, it makes change significantly cheaper and faster. When something unexpected comes up, the factory rebuilds affected components quickly and reliably, so that the project becomes more flexible and easier to manage and control. While AI agent provide the execution capacity, engineers provide specs, exercise judgment, and ensure verification and control.

This is why we can beat with an aggressive timeline and a smaller team while still delivering profitably. Here is an example. An AI bid manager assistant for a major food distributor. Previously, every RFP bid required hundreds of hours from dozens of specialists. Now, the AI system matches the RFP request with the distributor catalog and best supply offers. The first phase of this program is now in production with the goal to achieve faster, cheaper, and more competitive bids. We are building this program with a factory approach. The work runs in several work streams of 4 to 5 engineers each.

These factory teams are measured to deliver twice as much progress as conventional AI assistant teams on the same program. When we built a software factory, our GAIN platforms, like Rosetta or Allium, provides reusable engineering components and tools. After the project is done, we carry the learnings back to those platforms to continually compound knowledge. The critical aspect of AI delivery is security. Clients want the speed of AI-native delivery without adding new vulnerabilities. And new agentic threats require an adequate agentic response. Traditional security tools check code after it is written. We go further by shifting security left.

Our AI agents work inside the development process itself, so security checks happen while the code is being specified and developed. Specifically in capital markets, banks want correctness they can prove in front of regulators. This is where we deploy Allium. It helps to clearly specify functionality and find and fix vulnerabilities before they might leak into the release. We apply the same factory approach inside Grid Dynamics. It contributes to the productivity gains Leonard described outside client work. Our internal tools team can deliver more with less, and growing numbers of agentic applications and workflows already run in the Grid Dynamics environment. We drink our own champagne. Additionally, we continue to build up physical AI capabilities, pipeline, and projects.

Next-generation robots are trained on a mix of real-world examples and simulation. This is where Grid Dynamics fits perfectly. We bring deep robotics research, simulation experience, and AI engineering that runs reliably at enterprise scale. We are working with our clients and partners to take AI-controlled robots from labs to the production line. That is the work behind the two programs Leonard mentioned. One is the autonomous vehicle program of the industry equipment maker. The other is a humanoid robot for a pharmaceutical company moving materials inside its facilities. Both programs are growing. Grid Dynamics continues to expand its robotics partnership network, adding three robotics partners in the third quarter.

Together, we participate in top-tier industry events like GTC in Berlin, actively building our physical AI and robotics business. The Grid Dynamics team is proud of the progress we are making on AI transformation, and we are excited about the journey ahead. Anil, over to you.

Anil Doradla: Thanks, Eugene. Good afternoon, everyone. The third quarter came in at $114.3 million, above the high end of our guidance range of $112 million-$114 million. That represents 9.7% year-over-year growth and 5.7% sequential growth. Our top customers continue to execute well, with our top 10 customers growing at 8.6% on a sequential basis. Non-GAAP EBITDA was $22.9 million, our highest quarterly EBITDA on record, representing 20% of revenues and coming in well above our $16.5 million-$17.5 million guidance range. The strong sequential improvement in EBITDA was driven by a combination of strong quarter-over-quarter revenues growth, aided by our cost improvement initiatives and AI-driven productivity improvements that resulted in better than expected cost of sales and operating savings.

Looking at the performance of our verticals, TMT remained our largest vertical and accounted for 32.3% of total revenues for the quarter, with a growth of 7.6% sequentially and 29.3% on a year-over-year basis. The growth was primarily driven by higher demand from our largest technology customers. Retail contributed 27.2% of total revenues in the third quarter of 2026. Revenues grew 8.5% sequentially and 13.3% on a year-over-year basis, primarily driven by increased demand from specialty and home improvement retailers. Finance accounted for 22.5% of total revenues in the quarter. Revenues grew 3.9% sequentially, largely driven by global capital market customers. CPG and manufacturing represented 10.9% of quarterly revenues and grew 5.8% sequentially.

The growth came from a leading wholesale food distributor and from our manufacturing customers. Turning to our remaining verticals, our other vertical contributed 5.3% of third quarter revenues, while healthcare and pharma accounted for 1.8% of our revenues for the quarter. We ended the third quarter with a total headcount of 4,559, down from 4,838 employees in the second quarter of 2026, and from 4,971 in the third quarter of 2025. Our total headcount trends reflects productivity gains, particularly from our non-engineering functions. At the end of the third quarter of 2026, our total U.S. headcount was 377, or 8.3%, of the company's total headcount. Our non-U.S. headcount, located in Europe Americas, and India was 4,182, or 91.7%.

In the third quarter, revenues from our top five and top 10 customers were 45.4% and 63.3%, respectively, versus 40.1% and 58.3% in the same period a year ago. Moving on to the income statement. Our GAAP gross profit during the quarter was $46.1 million, or 40.3%, compared to $39.6 million, or 36.6%, in the second quarter of 2026, and $34.7 million, or 33.3%, in the quarter a year ago. On a non-GAAP basis, our gross profit was $46.5 million, or 40.6%, compared to $40 million, or 36.9%, in the second quarter of 2026, and $35.2 million, or 33.8%, in the year ago quarter.

On a sequential basis, gross margin expanded by approximately 370 basis points on both GAAP and non-GAAP basis. The increase in both GAAP and non-GAAP gross margin % on a sequential basis was primarily driven by a combination of improved resource utilization, efficiencies with non-billable resources, and working time. Our non-GAAP EBITDA during the third quarter that excluded interest, taxes, depreciation and amortization, and other income and expenses, fair value adjustments, stock-based compensation, transaction and transformation-related costs and restructuring costs, as well as geographic reorganization expenses, was $22.9 million, or 20% of revenues, versus $14.7 million, or 13.6% of revenues in the second quarter of 2026, and was up from $12.7 million, or 12.2%, in the year ago quarter.

Our GAAP net income in the third quarter was $6.2 million, or $0.08 per share, based on a diluted share count of 81.9 million shares, compared to the second quarter net income of $2.9 million, or $0.03 per share, based on a diluted share count of 83 million, and a net income of $1.2 million, or $0.01 per share, based on 85.8 million diluted shares in the year ago quarter.

On a non-GAAP basis, in the third quarter, our non-GAAP net income was $14.7 million, or $0.18 per share, based on 81.9 million diluted shares, compared to the second quarter non-GAAP net income of $9 million, or $0.11 per share, based on 83 million diluted shares, and $8.2 million, or $0.09 per share, based on 85.8 million diluted shares in the year ago quarter. On September 30th, 2026, our cash and cash equivalents total $304.3 million, up from $298.4 million on June 30th, 2026. During the third quarter, we repurchased approximately 0.9 million shares for a total consideration of $6.7 million.

Cumulatively, since our board authorized the $50 million share repurchase program, we have repurchased approximately 5.5 million shares for a total consideration of $37.5 million, reflecting our continued confidence in the long-term value of the business. Coming to the fourth quarter guidance, we expect our revenues to be in the range of $113.5 million to $115.5 million. We expect our fourth quarter non-GAAP EBITDA to be in the range of $20 million to $22 million. For the fourth quarter 2026, we expect our basic share count to be in the range of 81 million to 82 million, and our diluted share count to be in the range of 82 million to 83 million shares. That concludes my prepared remarks.

We are ready to take your questions.

Operator: Thank you, Anil. As we go into the Q&A session of this call, I will first announce your name. At that point, please unmute yourself and turn on your camera. The first question comes from Maggie Nolan of William Blair. Go ahead, Maggie.

Maggie Nolan: Hi. I think the video is disabled by the host, but hopefully you can hear my audio.

Operator: Yeah, go ahead. You can start it now.

Maggie Nolan: Okay, great. Hi, thank you, and congratulations. Leonard, so much went right this quarter across growth and margins and productivity. So if you had to distill it down to what really happened here, maybe what changed most meaningfully in the business, and how sustainable is that over the next several years?

Leonard Livschitz: Thank you, Maggie. It's always good to start the conversation in such a nice moment of time. It's been long awaited for. Yeah. I think instead of making it a long speech about all these details, I think that fundamentally, we have approached the structural change of the company. We're making the change implemented through our various organizations. There are several parts of that. On the client side, you heard the prepared remarks, you'll hear from the guys. We're doing more fixed-bid projects. We're having a better positioning with the growth of AI implementation solutions. We're doing the right thing, so it actually helps us with the margin profile.

On the cost side, there are several elements of that, and one of the very key one is that we've been talking for quarters in terms of that we are the client zero for many of the solutions we roll out to the clients. That actually helps us with ability to create a more efficient backend organizations, tooling, recruiting, hiring, operations. You've noticed there is a probably most significant diversions from the perspective of revenue versus headcount. That's a reason for that. The reason being is not only we're automating more of the solutions, but we are impacting virtually the ability of us to consolidate many of the functions.

Remember, in 2022, we grew to so many countries, and we had to contain the ability to actually manage our organization through all these different countries and offices. I think we've come to the point we are fully in control. That's one thing on the cost side. The other one is, again, more efficient deployment of engineers. I think we are having more predictive tools. We understand where technology leads, so we can have enough time to prepare the engineers and proper right size the teams where they're properly deployed.

Maggie Nolan: Thank you. Very helpful. Eugene, as CTO in the middle of this transformative technology cycle, I'm curious where you're spending most of your time and how that's maybe shifted over the last year.

Eugene Steinberg: Yeah. I am spending my time across the three horizons I have been always talking about on these calls. I am scaling things which work, things like AI-first modernizations of applications and data, GAIN platforms which are taking off the ground and scaling. On the second horizon, I am working to nurture and help to take off the ground the things which are emerging, like AI harness engineering, physical AI projects. Of course, I am always looking ahead and what happens next, things like AI native cybersecurity, sovereign AI, and many other interesting emerging themes which we consider as a next horizon for us.

Maggie Nolan: Great. Thank you.

Leonard Livschitz: Thank you, Maggie.

Operator: Thank you, Maggie. The next question comes from Puneet Jain of JPMorgan. Go ahead, Puneet. You can start your video now, Puneet.

Puneet Jain: Hey, thanks for taking my question. You recently announced winning the Partner of the Year Award at Sysco. Given that client also works with other large vendors that have much larger accounts, could you share how you were able to outperform other vendors, how you were able to punch above your weight, if you will, at that account, and is that replicable at other accounts?

Leonard Livschitz: Sure. Well, the hero of the day is not here today. We will have our earnings call early next year, and you will have Vasily, who runs our sales operations, he will tell you all the details. I was actually, Puneet, very intimately involved with the account as well. What happened is, many things start with understanding of the customer tasks. Usually for Grid Dynamics, you need to rely on the previous background. Even though it is not a traditional retail, but as many things logistics relate to B2B instead of B2C, we developed and governed many of the capabilities and accelerators were in that.

The people who we engage with, they actually realized that our expertise would give us the good chance to start the relationship. What happened then, it was not your typical land and expand. Of course, the center of gravity was the partnership with one of the major hyperscaler. Then we had a runaway train because we quickly not only uncovered the challenges customer need to solve rather rapidly, but scaled the solution and proved the real-time return on investment fairly quickly. To make story short, we are well-positioned in multiple regions. The customer utilizes us across the globe.

Right now, part of our team is actually in one of their offshore location, helping them to catch up because we are very, very friendly with the clients. We do not want to cannibalize everything from themselves to take over. Our business is to be partnering with them. The business is growing, and I was there at the presentation, and what really humbled me is how necessary and how timely our engagement has happened. Capabilities, unrelenting support, knowledge, and factual performance.

Puneet Jain: That is great to hear. Also nice to see this new factory approach. But given adoption of this new model will require thousands of employees across the globe embracing and execute against this delivery model, talk to us how you like your approach to achieve that, both from change management perspective as you de-link revenue from headcount was down this quarter, as well as from technical skill perspective for your employees.

Leonard Livschitz: Well, there are multiple facets of this question. I think, Puneet, you asked to show the secret sauce of Grid Dynamics, and there are many spices. Maybe it is good to wait for a celebration to give you some more runway. In a short, there are a few key elements. First of all, it starts with a really tiresome, or I would say not tiresome, shoulders of our CTO and his organization. Many of the practices when it comes to the implementations need to be trained and run internally. We need to evaluate multiple models. We need to weed out solutions which perhaps are a bit too optimistic.

More important, being a thrifty company as we are, we need to make sure that there is no overreach and overspend. There are companies who are reporting in that season, and some of them are very much overextended. We do not want that to happen to our clients. I think what happens first and foremost, we build a mousetrap for the client to deliver the capabilities within reasonable time and controlled cost. Of course, the solution changed rapidly, so we have to build more and more internal know-how, which we do.

The pressure comes on actual implementation teams, and you will see it a little bit as we come forward, that we have more on-prem, onshore resources, our talented enterprise architects and our leading specialists who work very closely with the customer, trying to crack down exactly what they need. This is ultimately what fixed projects are. You have to be able to understand to the much higher level of granularity the expected outcomes. We are learning that, we are training that, it is on R&D side, and it is in delivery side, and it also really comes from the ability for customer to build their stepping stone in the solution.

We are not offering just one solution fits all, and that is why we kind of enjoy being placed between two very large camps. We are not heavy on OpEx. We are not spending a huge amount of money on a back-end hardware capability, and we are not married to one particular enterprise software product. We are kind of on our groove with the AI deployment solution as we were years ago in a digital transformation and cloud migrations.

Puneet Jain: Got you. Thank you.

Anil Doradla: Thank you, Puneet.

Operator: The next set of questions comes from Bryan Bergin of TD Securities. Go ahead, Bryan.

Bryan Bergin: Hey, good afternoon. Good to see you.

Leonard Livschitz: Hey, Bryan.

Bryan Bergin: Wanted to start first on encouraging commentary here on 2027, so the growth profile that you see, the recovery there, getting back to double-digits. Not trying to get too far ahead of ourselves, but just based on what you are seeing in the conversation today, do you expect the growth to kind of be more broad-based growth attribution across industries and across clients, or is it more so you have visibility to some of these really large, strong relationships and that they are going to really carry the load or continue to carry the load?

Leonard Livschitz: It is a little bit of both. I think, Bryan, the right answer is the clients where we have a very strong, long-lasting relationship, we do a lot of experimentation. We see a little bit better the budget versus returns going more than just a quarter ahead, and sometime more than a year ahead. We start signing much longer deals we had before, so this is factual, and that gives us a little bit more productivity from planning perspective. You have been with us for many years, and you have been in this where the biggest question is, how is the engineering company can live out of every quarter resigning new SOW, right? That has changed dramatically.

We expanded it beyond the year more horizon. We are not there yet on a BPO type of style, five, seven years renewables, but we are getting very well controlled. So that is on existing clients. The partnerships brought us to the clients who need solutions the most right now, right? And those relationship start accelerating way more fast, faster than they were before. Typically, in a past world, we would start with a proof of concept, and it will take three to six months just to analyze the situation. Now it is a fail fast. In other word, we quickly determine what works, what does not work. Something always works in a new world, right?

So we just need to be experts on a consultancy, technology consultancy, which we have become and growing. So when we looked at forecasting the business, where it is too soon to guide exactly where we are, and you guys love the numbers. And for me, I just look at now, and I look back where we were during the good years, and I see so many proven similarities. That is why we look for next two, three years with a very high level of confidence. Plus, the mousetrap is widening, and there are more and more partners creating the relation with us in a new verticals.

And those verticals may not give us revenue in the next three to six months as much as the existing business, but they are rapidly getting deployed.

Anil Doradla: Adding one point to that, Bryan, if you look at our top customers, we talked about this, vendor consolidation. As vendors are getting consolidated, we get more wallet share too. We are seeing that also.

Bryan Bergin: Okay. All right, very good. My follow-ups on the announcement you had this week on the business consulting launch. A couple here really. How much of this opportunity would you say is incremental kind of consulting-led spend versus simply pulling forward AI engineering work you were already pursuing? What you see as being the biggest challenges as you try and blend this model with the engineering prowess that you have? And just how would you say it is different than traditional management and advisory consultancies?

Leonard Livschitz: Okay. Well, I think we will split the question with Eugene. You want to start?

Eugene Steinberg: Yes. The business consultancy which we are talking about is not about strategy, it is about functionality and the product. What is happening right now is with AI agents, which are doing the heavy lifting of the coding itself, the value shifts very quickly towards what to do and why.

And this is where we see a lot of value which we can bring, advising our clients not only on how to do things, but also what to do, why to do that, and bring in our best specialists, architects, and product managers to the forward-deployed roles and help them to get their head together what is possible right now with AI, where to invest, and how to connect all these to technology. This is the essence of this practice right now. Not talking about the grand strategies with customers.

Leonard Livschitz: Well, also to add to that, I think it's important to understand, Bryan, that the definition of, as Eugene alluded to, the business consultancy has changed. Some of those companies who are very strategic business consultants come to us, and they want us, together with them, to create this kind of gap filler between these high-level business needs and realistic implementations. We usually worked, as you know, historically, with the technology teams, with the CTOs, CIOs, VP of engineering, in some cases, marketing people. Now we're going instrumental across all the facets of the companies because they want to see their spend to be projected and understood for years to come.

Of course, with the token factories, with all the spend, many of the top decision-makers and boards are a bit worried. So we're giving them a bit more, I would say, concise and more confident roadmap of how the spend will convert into some of the solutions we're offering as an engineering organization.

Bryan Bergin: Okay. All right, very good. Thank you very much.

Anil Doradla: Thank you, Bryan.

Leonard Livschitz: Stay on.

Operator: The next set of questions come from Mayank Tandon of Needham and Company. Go ahead, Mayank.

Mayank Tandon: Great. Thank you, and congrats on the quarter.

Anil Doradla: Thank you, Mayank.

Mayank Tandon: I wanted to just start with, Anil, you made a comment about growth potential within your top five, top 10 accounts. How much capacity do you have left to grow with them? As you try to grow low-double-digits or whatever, I think Leonard mentioned double-digits, I shouldn't say low-double-digits. Do you need a certain level of new logo activity to be able to drive that level of growth, or can you grow within your existing base and growth from new logos would be maybe more gravy on top of that?

Anil Doradla: Look, if I look at the wallet spend of my top 10 customers, I think we're not even a rounding error at this point. These are very small portions. Mayank, if the question is, based on the spend of our top five, top 10, top 20 clients, can we continue growing? The answer is yes. And you've seen it. Our top five, top 10 continue to grow quarter after quarter, year after year. I think couple of things are changing. Grid Dynamics is approaching half a billion. We're now, I call a global company, truly global company, where we are having our engineers in the locations where most of our global clients are.

So the way they're treating us is slightly on the higher scale, so to speak. And I made a comment with, I think it was Puneet or Bryan. Vendor consolidation is a very important theme over the last two years. At these very, very large logos, they've got dozens and dozens of partners. As this technological revolution is taking place, they want to focus, they want to consolidate. Grid Dynamics was always an outlier. Our DNA, our structure, and another interesting thing, in the past, scale was considered a positive thing. Now, lack of scale or smaller size is considered a very positive thing.

So the number of conversations we're seeing with C-level Fortune 1,000, Fortune 100, customers, "I love your size, Grid Dynamics. You're in the 4,000 to 5,000. When we kick off this AI project, 50 people, 100 people, you bring the granularity, you bring the focus, you bring a high quality." When we look at the well-established vendors, they're in hundreds of thousands, and they're still thinking in terms of headcount. I gave you a little bit long answer, but in a nutshell, we will continue on. Leonard pointed out something on the partnerships. That's very exciting. Through partnerships, we find we get different types of clients that we never were able to get access to.

In some cases, these clients have grown very fast. So the pipeline of new clients through our partnership is a multiplier effect. Within our existing book of business, we're just becoming more meaningful to our partners.

Leonard Livschitz: So just to be very clear, Mayank, we can grow double-digits without major new finds where we would need to go and search, like, a new business with a new client. As Anil said, there is a strong position with existing clients.

Anil Doradla: Yes

Leonard Livschitz: Top 10-20. The share of the wallet goes up. At the same time, you know very well there were years, and it may happen in the future as well, there could be some of the fluctuation with these clients. Now we have the faster-growing acquisition of the new clients. We talk about Sysco Foods as being a matter of two years when we got to that level, and faster. But even more on the technology side, on the capital markets side, on the manufacturing, industrial, on robotics, on solutions for pharmaceutical companies, U.S., Europe, Southeast Asia. So just the sheer momentum is exactly where we want to be to be confident on the growth.

Of course, being where the clients are. I think they need to have fewer, but extremely relevant people. We may not be staying at this 4,000 to 5,000 people. I think we're going to grow.

Anil Doradla: Yeah.

Leonard Livschitz: But it's not going to be incremental growth to meet the client demand proportionally to the headcount. We crossed 100,000 per employee. We grew significantly faster than we expected, and we're growing, of course, by billable engineers and all this good stuff. Just keep watching us.

Mayank Tandon: Very helpful. That's super encouraging to hear. Then maybe turning to margins, obviously you're going to end up with your target goal of 300 basis points year-on-year. So just thinking about 2027, again, not looking for specific guidance, but just directionally, as you approach half a billion dollars in revenue, potentially with double-digit growth, how should we think about gross and EBITDA margins into 2027?

Anil Doradla: I knew this was going to come. Look, you're absolutely right. We delivered one quarter before, but remember, Mayank, the work started in Q4 of last year. This is not something we've started working on one quarter, two quarters. It's been in the works for some time. The timing happens as that sometimes things align sooner, we're executing better. I think in Leonard's comments, a very important thing he said, which is structure. Look, I know we're very excited that our margins are getting up, but look back, way back when. We're approaching our historical margins, right? So it's not like we've never done this.

We used to do it, but obviously over the last three years, you know what happened. So we're approaching that. All the things that we're doing are not a one-quarter thing, right? Whether it's on the COGS side, whether it's on the OpEx side, and we've listed almost half a dozen of these. So all I can say is that some of these things that we're doing are not one quarter. Obviously, you're going to have seasonality in the course of the year, so that goes without saying.

And what we are trying to get to is a company, as we get into 2027, where we have a certain growth vector on the revenue and a certain structure on the margins. So I'll just leave it at that, and look, we'll come back and give more color.

Leonard Livschitz: Mayank, very important from me as a CEO perspective, we're not trying to squeeze the water out of the stone. There are a couple areas of investment will only continue to grow. There's a relentless commitment to technology investments. We have to do it. This is the foundation. And training and developing proper engineers. We talk about 90%+ as you'll see training. We're leveraging our GAIN model 93%+. Those are not just numbers. This is a huge work behind the scene. And to me, we will properly position ourselves, margin investment perspective, to make sure you guys will see our growth continue for a long time.

Mayank Tandon: Great. Thank you. Appreciate it.

Anil Doradla: Thank you, Mayank.

Leonard Livschitz: Thanks, Mayank.

Operator: The next set of questions comes from Surinder Thind of Jefferies. Go ahead, Surinder.

Surinder Thind: Thanks, guys.

Anil Doradla: Thanks, Surinder.

Surinder Thind: I'd like to revisit the margin debate or question here. Obviously, there's a big move margins between where you were in 2Q versus what you produced in 3Q and the guide. How should we actually think about the run rate at that point?

Anil Doradla: Yeah.

Surinder Thind: We're talking about completely different levels of margin versus a blended year-end rate. Is 4Q the right starting point for seasonality, or how should we think about that? Or is there some one-time adjustments that we need to think about?

Anil Doradla: Yeah. Let's look at what happened, Surinder, the optics of it, right? Revenue grows up by $6.1 million. The COGS is flattish. The OpEx goes down a little bit. Effectively, the revenue pickup happens because of you have more billable headcount. The other very interesting thing is look at the average revenue per person. The margin, the contribution margins are also picking up at an individual engineer level, right? There are reasons for that. On the COGS side, we made comments. There is more efficiencies due to incorporation of these tools, AI included. There is more upskilling in there, and also there is more utilization. Of course, in Q3 we had working time. There was benefit from there.

As you go down on the OpEx, we started our efforts late last year, and we fully realized the benefits in Q3. There was a little bit of a compounding effect by the fact that it was Q3. The question is, look at where we are on Q4, $20 million-$22 million EBITDA, right? You do the math, obviously there is a setup point. Historically, as we went from, call it, Q3 to Q4, somewhere in that range, maybe a step below, flattish, we have been there. But the point is we enter 2027 with a fundamental different structure.

It is a structure that involves headcount, it is a structure that involves tools, and it is a structure that, to some extent, involves clients that are paying us differently as you get more and more AI projects. As we go into Q1, you have seasonal, that is the lowest margins every quarter, right? In the whole year. But I like to believe that we are entering 2027 structurally different than what we have had over the last couple of years. I have to balance that with investments. As Leonard said, there is a lot of work going on robotics. There is a lot of work going on physical AI. A lot of work going on cybersecurity.

So there will be some investments. But in general, the average revenue per engineer is going up, the contribution margin of engineers are going up, and we are benefiting from a little bit of a decoupling of spending money. I think these things are all playing out. I thought it would show up in Q4, it just happened to show up in Q3.

Surinder Thind: Fair enough. Where does that actually put you guys at from a utilization perspective? Are you at the target that you want to be at, or is there more that you can squeeze here? To Leonard's point about not wanting to squeeze too much.

Anil Doradla: So look, we've always had an eight handle on utilization. We've always had that. If you look at some of the headcount metrics that you saw here, may be a little misleading because it's not like there was a big change in our engineers, total number of engineers. What ended up happening is that we've obviously had greater conversion to billability. In terms of our utilization, we have some movements every quarter, but we're not expecting a very fundamental change. You will see an increased headcount as our revenue picks up because we benefited in 2026 with some of the non-engineering resource optimization. You're seeing some of the benefits there.

But in terms of engineering headcount, the utilization levels are in the same range, and we expect that to continue on.

Surinder Thind: But then, I guess as a point of clarification here The reduction in headcount that occurred, how much was billable and how much was non-billable?

Leonard Livschitz: We don't guide on the specific breakdown, but pretty much it was all non-engineering. Instead of talking about billable, non-billable part, I'll mention you about utilization. Majority of reduction, significant majority was purely from the non-engineering headcount. When it comes to, and I understand where you're coming from. I think the rate of speed, how we deploy people, the time to billability become shorter, the onboarding become shorter, the training of people in advance, because again, the technology structural solutions become available sooner, so we're able to determine what kind of skills are most relevant to the client become faster. It's efficiency game, not reduction of engineers.

Surinder Thind: Fair enough. Then as a follow-up, just commentary on it sounds like you're gearing up to use the balance sheet at this point for M&A. Sounds like you're working on some, maybe a bigger deal in the pipeline, or bigger deals. How should we think about your capital allocation at this point? What's the minimum you want to keep, your willingness to lever up, or where you want to end up from a capital structure perspective? Or how big a deal can you do at this point? Maybe what you're interested in from a technology perspective.

Anil Doradla: So I think the way I'll answer is pretty much the way Leonard commented, but it's very important. The last 24 months has been changes in the environment, right? We don't have to go through it. We've done a lot of work. We enter 2027 with incremental confidence. We feel really confident about where we are, how we are settling in, both from the number of countries where we're located, the skill sets, the upskilling towards SDLC. So we've gotten our house in order. Now the mandate from the board and Leonard to me is we need to now scale.

Look, I'm not going to say what's in the pipeline or not, but the appetite right now is for larger acquisitions, which we hope to do in 2027. As you know, Surinder, it's not done till it's done, right? We've had many close calls. But the intent is there, and we are entertaining. The areas that we want to entertain are areas where we want to scale some of our skill sets, entering into some of the new ones. We believe we're ready in 2027.

Surinder Thind: Then in terms of the skill set, is there any appetite for when you start to think about the evolution of some of the consulting businesses towards a more product-oriented strategy, how do you guys think about that versus adding more, I'll just say technical skills or services-oriented skills versus maybe coming in with more of a product bend on perhaps a particular vertical that you're interested in?

Leonard Livschitz: Yeah, I think we went a little bit too far, Surinder, in terms of philosophical discussion. Obviously not this quarter. The overall discussion in terms of what solutions and offerings can become a full-fledged product is eternal discussion between the services and consultancy. Everybody said, "Okay, if you have some solutions you can kind of lean upon, your business is better." That's what we do. When we talk about product versus services, we're a service company, and we have a very clear path where the customers, where the partners looking for us. Our job today is to assist our partners, our infrastructure with building accelerators on top what they offer.

In terms of the pure product side, you may have seen some of our, I would say, explorations, but we're very clear we're not competing with our partners. We are complementing, adding. Sometimes you build solution, it's pretty much a product, but then you work with both vendors and clients to make it work. That ecosystem is very strategically aligned. I think more discussion about the topic would be great for our investor day. When we announce, we're happy to have much longer conversation, but I appreciate you thinking about it because obviously everybody wants to have even higher revenue per person. From that perspective, obviously we consider many avenues.

Surinder Thind: Okay. I really appreciate the patience here, so thank you for the-

Anil Doradla: Thank you, sir.

Surinder Thind: questions.

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

Leonard Livschitz: Q3 2026 was a quarter of great Grid Dynamics success. The results validated our vision, strategy, and execution. Record revenue, record EBITDA, and AI Native platforms in production at some of the world's largest enterprises. Margin improvement that are structural and durable, and a business increasingly anchored in verticals where AI is moving fastest. I'm confident in the fourth quarter and in the momentum we're carrying into 2027. Thank you

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