Q1 2026 Grid Dynamics Holdings Inc Earnings Call

April 30, 2026

Speaker #1: Good afternoon, everyone. Welcome to GRID DYNAMICS' first quarter 2026 earnings conference call. I'm Cary Savas, Director of Branding and Communications. At this time, our participants are in listen-only mode.

Speaker #1: Joining us on the call today are CEO Leonard Livschitz, CFO Anil Doradla, CTO Eugene Steinberg, and SVP Global Head of Partnerships and Marketing, Rahul Bindlish.

Cary Savas: Good afternoon, everyone. Welcome to Grid Dynamics' Q1 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, CTO Eugene Steinberg, and SVP Global Head of Partnerships and Marketing, Rahul Bindlish. 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.

Speaker #1: 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 it, I'd like to remind everyone that today's discussion will contain forward-looking statements.

Speaker #1: 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.

Speaker #1: 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.

Speaker #1: 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.

Speaker #1: Our CEO.

Speaker #2: Thank you, Cary. Good afternoon, everyone, and thank you for joining us today. We started 2026 with solid execution, delivering Q1 revenue of $104.1 million, that was higher than our guidance range, and ahead of market expectations.

Cary Savas: 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.

Speaker #2: This performance reflects continued strengths in our business model and validates our focus on AI-led transformation and high-value enterprise engagements. Three trends stood out this quarter: a meaningful and growing contribution from AI revenue, a structural shift in vertical mix toward technology and financial services, and our top customers, our undergoing meaningful vendor consolidation with GRID DYNAMICS, emerging as a clear beneficiary.

Leonard Livschitz: Thank you, Kerry. Good afternoon, everyone, and thank you for joining us today. We started 2026 with solid execution, delivering Q1 revenue of $104.1 million that was higher than our guidance range and ahead of market expectations. This performance reflects continued strength in our business model and validates our focus on AI-led transformation and high-value enterprise engagements. Three trends stood out this quarter. A meaningful and growing contribution from AI revenue, a structural shift in vertical mix toward technology and financial services, and our top customers are undergoing meaningful vendor consolidation, with Grid Dynamics emerging as a clear beneficiary. Last quarter, we called 2026 a pivotal year for the accelerating adoption of our AI offerings. Our Q1 results support that conviction, with AI revenue reaching 29.3% of total company revenue, growing nearly 60% year-over-year.

Speaker #2: Last quarter, we called 2026 a pivotal year for the accelerating adoption of our AI offerings. Our first quarter results support that conviction with AI revenue reaching $29.3% of total company revenue, growing nearly 60% year over year.

Speaker #2: Given this concentration and growth trajectory, AI practice has become the core of our business, fundamentally reshaping our offerings, our talent development, and our client relationships.

A structural shift in vertical mix to our technology and financial services.

Speaker #2: I'm confident we're well-positioned to further accelerate AI revenues in 2026. For the first time, our top five accounts are entirely outside of retail, reflecting meaningful diversification into technology and financial services.

And our top customers are undergoing meaningful, vendor consolidation with grid Dynamics emerging as a clear beneficiary.

Leonard Livschitz: Given this concentration and growth trajectory, AI practice has become the core of our business, fundamentally reshaping our offerings, our talent development, and our client relationships. I'm confident we're well-positioned to further accelerate AI revenues in 2026. For the first time, our top five accounts are entirely outside of retail, reflecting meaningful diversification into technology and financial services, sectors where AI adoption is accelerating and our capabilities are highly differentiated. This group includes two leading global technology companies, a global fintech leader, a US-based global bank, and a leading financial institution. What makes this group notable is that each of these customers has undergone meaningful vendor consolidation, and Grid Dynamics has emerged as a clear beneficiary. This positions us to capture greater market share in 2026 and beyond.

Last quarter, we call 2026 a pivotal year for the accelerating adoption of our AI offerings. Our first quarter results, support that conviction with AI Revenue, reaching 29.3% of total company. Revenue, growing nearly 60% year-over-year

Speaker #2: Sectors where AI adoption is accelerating and our capabilities are highly differentiated. This group includes two leading global technology companies, a global fintech leader, a US-based global bank, and a leading financial institution.

Given this concentration in gross trajectory, our practice has become the core of our business, fundamentally reshaping our offerings, our talent development, and our client relationships.

Speaker #2: What makes this group notable is that each of these customers has undergone meaningful vendor consolidation and GRID DYNAMICS has emerged as a clear beneficiary.

I'm confident, we are well, positioned to further accelerate, our revenues in 2026.

Speaker #2: This position us to capture greater market share in 2026 and beyond. Additionally, we have been actively engaged in AI initiatives across all five customers, with some of our largest and most strategic programs driven by this group.

For the first time, our top 5 accounts are entirely outside of retail, reflects a meaningful diversification into technology and financial services.

Sectors, where AI adoption is accelerating and our capabilities are highly differentiated.

Speaker #2: Our size and AI technology focus are strategic advantages in a rapidly changing environment. Large enterprises are increasingly seeking highly capable, nimble partners like GRID DYNAMICS, who can move quickly and deliver meaningful AI outcomes rather than relying on incumbent global system integrators burdened by legacy delivery models.

This group includes 2 leading global technology companies a global fintech leader, a us-based global bank and a leading financial institution.

What makes this group notable is that each of these customers has undergone meaningful vendor consolidation, and Grid Dynamics has emerged as a clear beneficiary.

Leonard Livschitz: Additionally, we have been actively engaged in AI initiatives across all five customers, with some of our largest and most strategic programs driven by this group. Our size and AI technology focus are strategic advantages in a rapidly changing environment. Large enterprises are increasingly seeking highly capable, nimble partners like Grid Dynamics, who can move quickly and deliver meaningful AI outcomes rather than relying on incumbent global system integrators burdened by legacy delivery models. In many ways, headcount leverage is no longer a competitive moat, and differentiation comes from domain knowledge, AI capabilities, and ability to rapidly skill relevant expertise. We're not a systems integrator. We're a product-centric engineering company focused on solving the most complex mission-critical challenges for Fortune 1000 clients with a deliberate emphasis on driving revenue-generating capabilities, not just cost optimization.

This position us to capture greater market, share in 2026 in India.

Speaker #2: In many ways, headcount leverage is no longer a competitive mode, and differentiation comes from the main knowledge. AI capabilities and ability to rapidly scale relevant expertise.

Additionally, we have been actively engaged in AI initiatives across all 5 customers with some of our largest and most strategic programs driven by this group.

Our size and AI technology focus are strategic advantages in a rapidly changing environment.

Speaker #2: We're not a systems integrator. We're a product-centric, engineering company focused on solving the most complex, mission-critical challenges for Fortune 1000 clients, with a deliberate emphasis on driving revenue-generating capabilities, not just cost optimization.

Large Enterprises are increasingly seeking, highly capable Nimble Partners like grid Dynamics, who can move quickly, and deliver, meaningfully AI outcomes rather than relying on incumbent global system integrators burdened by Legacy delivery models.

Speaker #2: As enterprises migrate toward custom-developed solutions, the advantage shifts to partners who can build sophisticated production-grade software from concept to deployment. This is precisely what GRID DYNAMICS does.

In many ways. Headcount Leverage is no longer a competitive mode and differentiation comes from the main knowledge, AI capabilities and the ability to rapidly scale relevant expertise.

We're not a systems integrator.

Speaker #2: AI meaningfully expanding GRID DYNAMICS addressable market. For example, AI-native SDLC and agentic coding fundamentally changed the economics of delivering services. With delivery time and cost compressing, we can take on larger client initiatives that were previously out of our reach.

Leonard Livschitz: As enterprises migrate toward custom-developed solutions, the advantage shifts to partners who can build sophisticated production-grade software from concept to deployment. This is precisely what Grid Dynamics does. AI is meaningfully expanding Grid Dynamics addressable market. For example, AI-native SDLC and agentic coding fundamentally change the economics of delivering services. With delivery time and cost compressing, we can take on larger client initiatives that were previously out of our reach. AI is unlocking a wave of legacy modernization that was not previously economically viable. For years, replacing core legacy infrastructure was considered too expensive, time-consuming, and risky. AI lowers these barriers. At a leading home improvement retailer, the infrastructure of global operations is based on legacy mainframe platforms. Modernizing this legacy mainframe platform was considered risky and required specialized and expensive talent. Using AI agents, Grid Dynamics delivered a full modernization program within the timeline and budget.

We're a product Centric, engineering company, focus on solving the most complex Mission critical challenges for Fortune 10000 clients with a deliberate emphasis on driving Revenue, generating capabilities, not just cost optimization.

Speaker #2: Also, AI is unlocking a wave of legacy modernization that was not previously economically viable. For years, replacing core legacy infrastructure was considered too expensive, time-consuming, and risky.

Production grade software from concept to deployment.

This is precisely what greets the Nameks does.

Speaker #2: AI lowers these barriers. At the leading home improvement retailer, the infrastructure for global operations is based on legacy mainframe platforms. Modernizing these legacy mainframe platforms was considered risky and required specialized and expensive talent.

AI, meaningfully, expanding greed Dynamics. Addressable market, for example, AI native sdlc an agenda, coding fundamentally changed the economics of delivering services.

With delivery time and cost cost compressing, we can take on larger client initiatives that were previously out of Outreach.

Also AI is unlocking a wave of Legacy modernization. That was not previously economically viable.

Speaker #2: Using AI agents, GRID DYNAMICS delivered a full modernization program within the timeline and budget. GRID DYNAMICS expertise is now extending into physical AI. In CPG and manufacturing, enterprises are turning to self-learning robotics and AI technologies, to drive operating efficiencies.

For years, replacing core legacy infrastructure was considered too expensive, time-consuming, and risky.

AI lowers. These barriers

Speaker #2: Our game platform for physical AI makes intelligent robotics more accessible and economically viable. In the first quarter, we closed our first commercial engagement in physical AI with a heavy equipment manufacturer.

At the leading home improvement retailer, the infrastructure for global operations is based on legacy mainframe platforms. Modernizing these legacy mainframe platforms was considered risky and requires specialized and expensive talent.

Leonard Livschitz: Grid Dynamics expertise is now extending into physical AI. In CPG and manufacturing, enterprises are turning to self-learning robotics and AI technologies to drive operating efficiencies. Our GAIN platform for physical AI makes intelligent robotics more accessible and economically viable. In Q1, we closed our first commercial engagement in physical AI with a heavy equipment manufacturer. We're enabling their mining equipment with intelligent autonomous capabilities. We're building the company around AI. Four pillars define this transformation: AI-native delivery, prioritized engineering, AI consulting, and internal AI automation. The first pillar, AI-native delivery, marks a fundamental shift in how we work, from human-led workflows to AI agent-driven spec-based executions across our fixed-bid engagements. The economics are compelling. Adoption is accelerating. Early indicators point to material productivity gains in select workflows and a structured different cost base.

Using AI agents, Grid Dynamics delivered a full modernization program within the timeline and budget.

Speaker #2: We're enabling their mining equipment with intelligent autonomous capabilities. We're building the company around AI. Four pillars define this transformation: AI-native delivery, productized engineering, AI consulting, and internal AI automation.

Read the names expertise is now extending into physical AI.

In cpg and Manufacturing Enterprise are turning to self-learning Robotics and AI Technologies to drive operating efficiencies.

Speaker #2: The first pillar: AI-native delivery marks a fundamental shift in how we work. From human-led workflows to AI agent-driven, spec-based executions, across our fixed bid engagements.

Our game platform for physical AI makes intelligent robotics more accessible and economically viable in the first quarter. We closed our first commercial engagement and physical AI with a heavy equipment manufacturer, where enabling their mining equipment with intelligence autonomous capabilities,

Speaker #2: The economics are compelling, and adoption is accelerating. Early indicators point to material productivity gains in select workflows and a structured different cost base. In Q1, at our global bank, our autonomous AI workflows analyzed 150 green production applications and uncovered latent defects across systems, including test and coding incorrect behavior.

We're building the company around the area.

4 pillars, Define these transformation.

AI native delivery.

Productized engineer.

AI Consulting and internal AI Optum automation.

The first pillar, AI native, delivery marks a fundamental shift in how we work.

From human-led workflows to AI agent, driven spec based executions across our fixed bid engagements.

Speaker #2: By expanding validated behavior coverage, to greater than 70%, we reduced false confidence in system integrity and mitigated production security and regulatory risk. The second pillar: productized engineering focused on converting our repeatable IP into AI-native platform-based offering under the GAIN platforms.

The economics are compelling.

And adoption is accelerated.

Leonard Livschitz: In Q1, at our global bank, our autonomous AI workflows analyzed 150 green production applications and uncovered latent defects across systems, including test and coding incorrect behavior. By expanding validated behavior coverage to greater than 70%, we reduce false confidence in system integrity and mitigated production security and regulatory risk. The second pillar, productized engineering, focus on converting our repeatable IP into AI-native platform-based offering under the GAIN platforms. GAIN consists of four domain-specific platforms spanning from Agentic AI commerce, SDLC, risk and compliance, and physical AI. Our engineers increasingly operate as forward-deployed specialists composing and customizing these platforms to each client's specific environment, data, and workflows. The result is deeper differentiation and stronger client retention. A good example is that what we achieved is one of the world's largest food distributors.

Early indicators point to material productivity gains in select workflows and a structured, different call space.

Speaker #2: GAIN consists of four domain-specific platforms: spanning from agentic AI commerce, SDLC, risk and compliance, and physical AI. Our engineers increasingly operate as forward-deployed specialists, composing and customizing these platforms to each client's specific environment, data, and workflows.

In Q1, at our global bank, autonomous AI workflows analyzed 150 green production applications and uncovered latent defects across systems, including tests and encoding incorrect behavior.

By expanding validated Behavior coverage to greater than 70%. We reduce false confidence in system integrity and mitigated production security, and Regulatory risk.

The second pillar.

Speaker #2: The result is deeper differentiation and stronger client retention. A good example is that what we achieved at one of the world's largest food distributors.

Speaker #2: Our client sales associates were spending hours on manual research and proposal preparation for their restaurant clients. We developed AI agents, then compressed the preparation process to minutes while improving the quality of the reports.

Productizing engineering focus on converting, our repeatable, IP into AI native platform based offering under the game platforms. Game consists of 4 domain specific platforms spending from a genetic AI Commerce.

Sdlc.

Risk and compliance, and physical aid.

Speaker #2: Our efforts resulted in 50% reduction in preparation time and 18% increase in monthly spend for the targeted accounts. The third pillar is AI consulting.

How Engineers increasingly operate as forward. Deployed Specialists composing and customizing these platforms to each client's specific environment data and workflows. The result is deeper differentiation and stronger crime retention.

Leonard Livschitz: Our client sales associates were spending hours on manual research and proposal preparation for their restaurant clients. We developed AI agents that compress the preparation process to minutes while improving the quality of the reports. Our efforts resulted in 50% reduction in preparation time and 18% increase in monthly spend for the targeted accounts. The third pillar is AI consulting. As companies undergo AI transformation, existing business workflows must be evaluated and reimagined for a generative world. Clients are seeking out domain knowledge and deep understanding of AI and data. At a leading global fintech company, our engagement focused on development of AI agents which automate enterprise workflows. Early efforts with our forward-deployed engineers embedded inside the client organization have identified inefficiencies and deployed AI agents to automate, optimize, and scale these processes with a human in the loop, resulting in 15% productivity improvement.

Speaker #2: As companies undergo AI transformation, existing business workflows must be evaluated and reimagined for agentic world. Clients are seeking out the main knowledge and deep understanding of AI and data.

A good example is that when we achieved that 1 of the world's largest Food, Distributors our client sales associates were spending hours on manual research and proposal preparation for their restaurant clients.

Speaker #2: At a leading global fintech company, our engagement focused on development of AI agents, which automate enterprise workflows. Early efforts with our forward-deployed engineers embedded inside the client organization have identified inefficiencies and deployed AI agents to automate optimize and scale these processes with a human-in-the-loop, resulting in 15% productivity improvement.

We developed AI agents. Then compressed the preparation process to minutes. While improving the quality of the reports. Our efforts resulted in 50% reduction in preparation, time and 18% increase in monthly, spend for the targeted accounts.

The third pillar is AI consult.

As companies undergo AI transformation, existing business workflows must be evaluated and reimagined for agent work.

Clients are seeking out the main knowledge and deep understanding of AI and data.

Speaker #2: The fourth pillar is tied to adapting AI for our internal operations. Over the past several months, we have been adapting AI tools both off-the-shelf and internally developed.

As a leading global fintech company, our engagement focused on development of AI agents, which automate Enterprise workflows,

Speaker #2: It enhances our productivity and efficiency. This includes areas such as recruitment, RFP responses, knowledge management, and HR. With recruitment, we have seen a 2x productivity improvement in terms of number of applicants we can process.

Optimize and scale these process with a human in the loop.

Resulting in 15% productivity. Improve.

Speaker #2: With RFPs, we have increased the number of responses by 50% without growing headcount. With knowledge management, our responses to employee questions improve from hours to minutes.

Leonard Livschitz: The fourth pillar is tied to adapting AI for our internal operations. Over the past several months, we have been adopting AI tools, both off-the-shelf and internally developed, in enhancing our productivity and efficiency. This includes areas such as recruitment, RFP responses, knowledge management, and HR. With recruitment, we have seen a 2x productivity improvement in terms of number of applicants we can process. With RFPs, we have increased the number of responses by 50% without growing headcount. With knowledge management, our responses to employee questions improve from hours to minutes. With HR, multiple initiatives are being rolled out, and we expect more than 20% operational improvement. Q1 project highlights. Our vertical execution in Q1 is best illustrated by a few notable client engagements. TMT.

The fourth pillar is tied to adapt in AI for our internal operations.

Speaker #2: And with HR, multiple initiatives are being rolled out, and we expect more than 20% operational improvement. Q1 project highlights: our vertical execution in the first quarter is best illustrated by a few notable client engagements.

Or the past several months, we have been adopting AI tools. Both of the shelf and internally developed in enhancing our productivity and efficiency.

This includes areas such as recruitment, Knowledge Management, and HR, are a few responses.

Speaker #2: TMT: for a global technology company, operating large-scale manufacturing environments, GRID DYNAMICS designed and validated a unified manufacturing intelligent platform to replace fragmented manual data flows.

With recruitment. We have seen a 2 expert activity Improvement. In terms of number of applicants, we can process with our teams, we have increased. The number of responses by 50% without growing head, count

with Knowledge Management. Our responses to employee questions, improve from hours to minutes and with a chart multiple initiatives are being rolled out and we expect more than 20% operational Improvement.

Speaker #2: The solution is projected to reduce data discovery and reporting cycle times by over 95%. It also lays the foundation for enterprise-wide operational intelligence. CPG and manufacturing: GRID DYNAMICS built and deployed a unified agentic AI platform for a leading global CPG manufacturer.

Q1 project highlights.

Our vertical execution in the first quarter is best illustrated by a few notable client engagements.

Leonard Livschitz: For a global technology company operating large-scale manufacturing environments, Grid Dynamics designed and validated a unified manufacturer intelligent platform to replace fragmented manual data flows. The solution is projected to reduce data discovery and reporting cycle times by over 95%. It also lays the foundation for enterprise-wide operational intelligence. CPG and manufacturer. Grid Dynamics built and deployed a unified Agentic AI platform for a leading global CPG manufacturer, creating the shared infrastructure required to develop, govern, and scale AI agents consistently across the enterprise. Running on a major cloud platform, the solution serves as an operational backbone for AI-driven transformation across the manufacturer's supply chain, consumer, and commercial domains. The highest complexity has impact areas of the business. Automotive part retailer. For a leading global retailer, Grid Dynamics led the end-to-end modernization of a mission-critical inventory and replenishment platform, migrating from legacy on-premise infrastructure to a cloud-native environment.

TMT.

Speaker #2: Creating the shared infrastructure required to develop, govern, and scale AI agents consistently across the enterprise. Running on a major cloud platform, the solution serves as an operational backbone for AI-driven transformation across the manufacturer's supply chain, consumer, and commercial domains.

for a global technology company operating large scale, manufacturing environments, great Dynamics design and validated a unified manufacturer intelligent platform to replace fragmented, manual data flows,

The solution is projected to reduce data Discovery and Reporting cycle Times by over 95%.

It also lays the foundation for Enterprise wide, operational intelligence.

Speaker #2: The highest complexity, highest impact areas of the business. Automotive part retailing: for a leading global retailer, GRID DYNAMICS led the end-to-end modernization of emission-critical inventory and replenishment platform, migrating from legacy on-premise infrastructure to a cloud-native environment.

Cpg, and Manufacturing.

Read Dynamics, build and deploy a unified agenda. AI platform for a leading Global cpg manufacturer.

Creating the shared infrastructure, required to develop government and scale AI agents consistently across the Enterprise.

Speaker #2: The program delivered over 70% reduction in infrastructure costs and approximately 40% improvement in query responses time, restoring the platform's ability to support real-time replenishment decisions at the global scale.

Running on a major Cloud platform. The solution serves as an operational backbone for AI driven transformation across the manufacturer's supply chain consumer and Commercial domains.

The highest complexity has impact areas of the business.

Automotive part with them.

Speaker #2: At the premier global multi-bread restaurant company, GRID DYNAMICS deployed an AI coding harness to replace the manual QA workflows that struggled to keep pace with frequent enterprise changes across web and mobile.

Leonard Livschitz: The program delivered over 70% reduction in infrastructure costs and approximately 40% improvement in query responses time, restoring the platform's ability to support real-time replenishment decisions at the global scale. At a premier global multi-brand restaurant company, Grid Dynamics deployed an AI coding harness to replace the manual QA workflows that struggle to keep pace with frequent enterprise changes across web and mobile. AI agents continuously simulate customer behavior and adapt automatically to UI modifications in real-time, eliminating testing bottlenecks without human intervention. The platform has reduced testing time by approximately 50%. With that, I will hand over to Rahul Bindlish, Global Head of Partnerships and Marketing, who will share some of the exciting initiatives currently underway and give you a closer look at where Grid Dynamics is headed. Rahul.

For a leading Global retailer greed, Dynamics. Led the end to end modernization of omission, critical inventory and replenishment platform. Migrating from Legacy on premise infrastructure to a cloud native environment

Speaker #2: AI agents continuously simulate customer behavior and adapt automatically to UI modifications, in real-time, eliminating testing bottlenecks without human intervention. The platform has reduced testing time by approximately 50%.

The program delivered over a 70% reduction in infrastructure costs and approximately a 40% improvement in correspondence time, restoring the platform's ability to support real-time replenishment decisions at a global scale.

Speaker #2: With that, I will hand over to Rahul Bindlish, Global Head of Partnership and Marketing, who will share some of the exciting initiatives currently underway and give you a closer look at where GRID DYNAMICS is headed.

As a premier Global multi Bread restaurant company, grey Dynamics deployed, an AI coding harness to replace the manual. QA workflows that struggle to keep Pace with frequent interpretation across, web and mobile.

Speaker #2: Rahul?

Speaker #1: Thank you, Leonard. Good afternoon, everyone. Partnerships are now a key component of how we go to market. Our partner-influenced revenues have grown to $19.1% of total company revenue in quarter one, underscoring the value of our ecosystem-driven approach in the agentic era.

Hey agents continuously simulate customer behavior and adapt automatically to UI modifications in real time. Eliminating testing bottlenecks without human intervention.

The platform has reduced testing time by approximately 50%.

Speaker #1: The majority of our partner-influenced revenue is driven by Google Cloud, AWS, and Microsoft Azure. Our three core hyperscaler relationships. They are an active, go-to-market channel for our platforms and services.

With that, I will hand over to Rahul English Global head of partnership in marketing who will share some of the exciting initiatives currently underway. And give you a closer look at where agreed Dynamics is headed.

Rahul.

Rahul Bindlish: Thank you, Leonard. Good afternoon, everyone. Partnerships are now a key component of how we go to market. Our partner influence revenues have grown to 19.1% of total company revenue in Q1, underscoring the value of our ecosystem-driven approach in the Agentic era. The majority of our partner influence revenue is driven by Google Cloud, AWS, and Microsoft Azure, our three core hyperscaler relationships. They are an active go-to-market channel for our platforms and services. Our go-to-market strategy is aligned with the AI strategy described by Leonard in his comments. We will be deploying all our platforms on the marketplace of hyperscalers. Our GAIN platform for risk and compliance is now listed on both Google Cloud Marketplace and AWS Marketplace. Enterprises searching for production-grade capabilities in this domain within those ecosystems will find Grid Dynamics IP directly, increasing our sales pipelines.

Thank you, Leonard. Good afternoon, everyone.

Speaker #1: Our go-to-market strategy is aligned with the AI strategy described by Leonard in his comments. We will be deploying all our platforms on the marketplace of hyperscalers, our gain platform for risk and compliance is now listed on both Google Cloud Marketplace and AWS Marketplace.

Partnerships are now at Key component of how we go to market, our partner, infants revenues, have grown to 19.1% of total company. Revenue in quarter. 1 underscoring. The value of our ecosystem driven approach in the identic era,

Speaker #1: Enterprises searching for production-grade capabilities in this domain within those ecosystems will find GRID DYNAMICS IP directly, increasing our sales pipelines. We also have joint sales motions with the hyperscalers to accelerate deal closures.

The majority of our partner influence revenue is driven by Google Cloud, AWS, and Microsoft Azure, our three core hyperscaler relationships.

They are an active go-to-market channel for our platforms and services. Our go-to-market strategy is aligned with the AI strategy described by Leonard in his comments.

Speaker #1: That is a fundamentally different way to win business compared to traditional services sales. This is the first deployment in a deliberate rollout. We are moving additional platforms onto the marketplaces of every major hyperscaler.

We will be deploying all our platforms on the marketplace of hyperscalers.

Again, platform for risk and compliance is now listed on both, Google Cloud Marketplace and needed this Marketplace.

Speaker #1: It also deepens our coastal relationships with these partners. Our gain platforms plus forward-deployed engineers model is a new approach to go-to-market with the hyperscalers.

Rahul Bindlish: We also have joint sales motions with the hyperscalers to accelerate deal closures. That is a fundamentally different way to win business compared to traditional services sales. This is the first deployment in a deliberate rollout. We are moving additional platforms onto the marketplaces of every major hyperscaler. It also deepens our co-sell relationships with these partners. Our GAIN platforms plus forward-deployed engineers model is a new approach to go to market with the hyperscalers. The platform creates the entry point. Our engineers deliver the value realization. Enterprises see this clearly, and the first few engagement wins reflect their willingness to pay for it. Each platform we bring to market addresses a specific business pain point with domain-specific IP. This changes the sales dynamic in a way that matters for our growth model.

Enterprises searching for production, great capabilities. In this domain, within those ecosystems, we'll find Grid Dynamics' IP directly increasing our sales pipelines.

Speaker #1: The platform creates the entry point. Our engineers deliver the value realization. Enterprises see this clearly in the first few engagement wins reflect their willingness to pay for it.

We also have joint sales motions with the hyperscalers to accelerate deal closures.

Compared to traditional Services sales.

This is the first deployment in a deliberate roll out.

Speaker #1: Each platform we bring to market addresses a specific business pain point with domain-specific IP. This changes the sales dynamic in a way that matters for our growth model.

We are moving additional platforms onto the marketplaces of every major hyperscaler, it also deepens our Coastal relationships with these partners.

Speaker #1: When we lead with a vertical-specific platform, whether that is agentic commerce, compliance, or physical AI, we enter a client conversation with a validated solution for a specific business problem.

Our game platforms plus forward deployed Engineers model is a new approach to go to market with the hyperscalers.

The platform creates the entry point.

Our engineers deliver the value realization.

Speaker #1: Sales cycles compress, conversion rates improve, and initial contracts expand faster because the platform's value is visible to both the business buyer and the technical evaluator.

And enterprises. You can see this clearly in the first few engagement wins, which reflect their willingness to pay for it.

Each platform we bring to Market addresses a specific business pain point with domain specific IP.

Speaker #1: This vertical specificity is what makes our coastal relationships with Google, AWS, and Azure productive. GRID DYNAMICS technical depth and domain knowledge combined with the hyperscalers' cloud infrastructure is what allows us to win engagements against competition.

Rahul Bindlish: When we lead with a vertical specific platform, whether that is Agentic AI, compliance, or physical AI, we enter a client conversation with a validated solution for a specific business problem. Sales cycles compress, conversion rates improve, and initial contracts expand faster because the platform's value is visible to both the business buyer and the technical evaluator. This vertical specificity is what makes our co-sell relationships with Google, AWS, and Azure productive. Grid Dynamics technical depth and domain knowledge, combined with the hyperscalers cloud infrastructure, is what allows us to win engagements against competition. Our AI revenue acceleration is the output of that combination. We are also expanding our partnership with NVIDIA by porting our solutions onto their software stack. Our GAIN platform for physical AI is built on NVIDIA stack, including Omniverse, and we are taking it to market with NVIDIA for manufacturing and CPG companies.

These changes the sales dynamic in a way that matters for a growth model when we lead with a vertical-specific platform, whether that is agentic Commerce, compliance, or physical AI. We enter a client conversation with a validated solution for a specific business problem.

Sales Cycles. Compress conversion. Rates improve.

Speaker #1: Our AI revenue acceleration is the output of that combination. We are also expanding our partnership with NVIDIA by porting our solutions onto their software stack.

And initial contracts expand faster because the platform's value is visible to both the business buyer and the technical evaluator.

Speaker #1: Our gain platform for physical AI is built on NVIDIA's stack, including Omniverse, and we are taking it to market with NVIDIA for manufacturing and CPG companies.

This vertical specificity is what makes our Coastal relationships.

With Google, AWS, and Azure productive.

Speaker #1: Industrial AI in manufacturing environments requires simulation fidelity and sensor integration that generic AI infrastructure does not support. Building on NVIDIA's stack positions us to address that requirement and enables joint go-to-market with NVIDIA into a customer segment where the demand for production-grade physical AI is accelerating.

Great Dynamics, technical depth and domain knowledge. Combined, with the hyperscalers. Cloud infrastructure is what allows us to win engagements against competition.

Our AI Revenue acceleration is the output of that combination.

We are also expanding our partnership with Nvidia by porting a Solutions onto their software stack.

Our game platform for physical. AI is built on. Nvidia stack, including Omniverse.

Speaker #1: We have also expanded our partnership ecosystem in the AI consulting space. Entering into relationships with specialized firms in business process mining, and organizational change management.

And we are taking it to market with Nvidia for manufacturing and CPG companies.

Rahul Bindlish: Industrial AI in manufacturing environments requires simulation fidelity and sensor integration that generic AI infrastructure does not support. Building on NVIDIA stack positions us to address that requirement and enables joint go-to-market with NVIDIA into a customer segment where the demand for production-grade physical AI is accelerating. We have also expanded our partnership ecosystem in the AI consulting space, entering into relationships with specialized firms in business process mining and organizational change management. Effective enterprise AI deployment is more than just a technology problem. Clients who deploy agentic workflows are simultaneously re-engineering the processes those agents replace and managing the organizational change that follows. By integrating specialized process mining and change management partners into our delivery model, we extend the value that Grid Dynamics offers from platform and engineering through to adoption and measurable ROI capture. There are two more trends worth noting.

Industrial AI in manufacturing environments, requires simulation Fidelity, and sensor integration.

Speaker #1: Effective enterprise AI deployment is more than just a technology problem. Clients who deploy agentic workflows are simultaneously re-engineering the processes those agents replace, and managing the organizational change that follows.

That generic AI infrastructure does not support.

Building on Nvidia stack positions as to address that requirement and enables joint go to market with Nvidia into a customer segments. But the where the demand for production grade, physical AI is accelerating.

Speaker #1: By integrating specialized process mining and change management partners into our delivery model, we extend the value that GRID DYNAMICS offers from platform and engineering through to adoption and measurable ROI capture.

They have also expanded our partnership ecosystem in the AI Consulting space.

Entering into relationships with specialized forms in business, process, Mining and organizational, change management.

Speaker #1: There are two more trends worth noting. Many of the engagements that we are winning through partner channels are extending beyond the initial project. When an AI project delivers clear ROI, and our clients are seeing this at scale, the relationship does not close; it expands.

Effective Enterprise AI deployment is more than just a technology problem.

clients who deploy identic, workflows are simultaneously, re-engineering, the processes, those agents replace,

And managing the organizational change that follows.

Speaker #1: Clients return for more use cases, projects, and programs. That pattern is visible in our retention data and in the expansion of existing hyperscaler coastal accounts.

By integrating specialized process Mining and change management Partners into our delivery model. The extend the value that grid Dynamics offers

from platform and engineering through to adoption and measurable ROI capture.

Rahul Bindlish: Many of the engagements that we are winning through partner channels are extending beyond the initial project. When an AI project delivers clear ROI, and our clients are seeing this at scale, the relationship does not close, it expands. Clients return for more use cases, projects, and programs. That pattern is visible in our retention data and in the expansion of existing hyperscaler co-sell accounts. At one of the largest food distributors in North America, that pattern played out across three distinct phases. The initial engagement was a search project delivered through a co-sell motion with Google Cloud and built on GAIN platform for agentic commerce. The platform's search capabilities were in production within weeks. The client retained Grid Dynamics immediately following go live to extend the program using our catalog enrichment solution built on the same platform to improve the quality of the search results.

Speaker #1: At one of the largest food distributors in North America, that pattern played out across three distinct phases. The initial engagement was a search project delivered through a coastal motion with Google Cloud and built on gain platform for agentic commerce.

There are two more trends worth noting. Many of the engagements that we are winning through partner channels are extending beyond the initial project.

when an AI project delivers clear ROI

And our clients are seeing this at scale. The relationship does not close it. Expands,

Speaker #1: The platform search capabilities were in production within weeks. The client retained GRID DYNAMICS immediately following go-live to extend the program. Using our catalog enrichment solution, built on the same platform, to improve the quality of the search results.

Clients return for more use cases, projects and programs.

That pattern is visible in our retention data and in the expansion of existing hyperscaler coal accounts.

Speaker #1: We are now in the third phase, the development of an agentic platform for the client's commercial operations with the first use case targeting sales efficiency already in production.

At 1 of the largest food distributors in North America that pattern played out across 3 distinct phases. The initial engagement was a search Project

delivered through a coastal motion with Google cloud and built on gain platform for agentic Commerce.

Speaker #1: The margin profile of AI engagements especially those built on gain platforms is meaningfully different from the traditional services pipeline. When we win through a joint sales motion, clients are buying a validated solution at a fixed commercial structure.

The platform search capabilities were in production within weeks.

The client retained grid Dynamics immediately following go live to extend the program.

Using our catalog enrichment solution, built on the same platform, to improve the quality of the search results.

Rahul Bindlish: We are now in the third phase, the development of an Agentic AI platform for the client's commercial operations, with the first use case targeting sales efficiency already in production. The margin profile of AI engagements, especially those built on GAIN platforms, is meaningfully different from the traditional services pipeline. When we win through a joint sales motion, clients are buying a validated solution at a fixed commercial structure. That changes the margin profile. Higher gross margins than a blended services average. The GAIN platforms plus forward deployed engineers model is not just an acquisition strategy. It's a retention and margin expansion strategy, too. With that, I'll hand it to Anil to walk through the financials.

Speaker #1: That changes the margin profile. Higher gross margins then are blended services average. The gain platforms plus forward-deployed engineers model is not just an acquisition strategy.

We are now in the third phase, the development of an agentic platform for the client's commercial operations. With the first use case targeting sales efficiency already in production,

Speaker #1: It's a retention and margin expansion strategy too. With that, I'll hand it to Anil to walk through the financials.

The margin profile of EI engagements, especially those built on gain platforms.

Is Meaningful for the different from the traditional Services pipeline.

Speaker #2: Thanks, Rahul. Good afternoon, everyone. We recorded the first quarter revenues of $104.1 million slightly above the higher end of our guidance range of $103 million to $104 million.

When we went through a joint sales, motion clients are buying a validated solution at a fixed commercial structure.

That changes the margin profile.

Higher gross margins, then up blended services average.

Speaker #2: Our revenues grew 3.7% on a year-over-year basis. Non-GAAP EBITDA was 12.5 million or 12% of revenues and was at the midpoint of our $12 million to $13 million guidance range.

Forms plus forward deployed. Engineers model is not just an acquisition strategy. It's a retention and margin expansion strategy too.

With that, I'll hand it to Anil to walk through the financials.

Speaker #2: In the first quarter, there was a negative impact from FX fluctuations on a year-over-year basis. We are exposed to a currency basket across Europe, Latin America, and India.

Anil Doradla: Thanks, Rahul. Good afternoon, everyone. We recorded Q1 revenues of $104.1 million, slightly above the higher end of our guidance range of $103 million to $104 million. Our revenues grew 3.7% on a year-over-year basis. Non-GAAP EBITDA was $12.5 million or 12% of revenues and was at the midpoint of our $12 million to $13 million guidance range. In Q1, there was a negative impact from FX fluctuations on a year-over-year basis. We are exposed to a currency basket across Europe, Latin America, and India. While we utilize both natural hedges and an active hedging program, the net impact on a year-over-year basis on our EBITDA was a headwind of approximately $1.2 million. As Leonard highlighted, our top customers are global technology and financial enterprises.

Speaker #2: While we utilize both natural hedges and an active hedging program, the net impact on a year-over-year basis on our EBITDA was a headwind of approximately 1.2 million dollars.

Thanks Rahul. Good afternoon everyone. We recorded the first quarter revenues of 104.1 million slightly above the higher end of our guidance, range of 103 million to 204 million, our revenues grew, 3.7% on a year-over-year basis.

Speaker #2: As Leonard highlighted, our top customers are global technology and financial enterprises. And this is by design. Our growth strategy is deliberately focused on verticals where AI adoption is accelerating and are capabilities are highly differentiated.

Non-gaap ibitta was 12.5 million or 12% of revenues and was at the midpoint of our 12 million to 13 million guidance range.

In the first quarter, there was a negative impact from FX fluctuations on a year-over-year basis.

We are exposed to a currency basket across Europe, Latin America and India.

Speaker #2: In the first quarter revenue breakdown reflects this redistribution with meaningful diversification into our TMT and financial verticals. Looking at the performance of our verticals, TMT became our largest vertical and accounted for 29.5% of total revenues for the quarter, with growth of 30.3% on a year-over-year basis.

While we utilize both natural Hedges and an active hedging program. The net impact on the year-over-year basis on our Evita was a headwind of approximately 1.2 million dollars.

Anil Doradla: This is by design. Our growth strategy is deliberately focused on verticals where AI adoption is accelerating and our capabilities are highly differentiated. In Q1, revenue breakdown reflects this redistribution with meaningful diversification into our TMT and financial verticals. Looking at the performance of our verticals, TMT became our largest vertical and accounted for 29.5% of total revenues for the quarter, with growth of 30.3% on a year-over-year basis. The growth was primarily driven by a combination of our largest technology customers as well as new customers. Retail contributed 28.4% of total revenues in Q1 2026. The finance vertical accounted for 23.5% of total revenues in the quarter, and we witnessed strong demand from our banking and fintech customers.

As Leonard highlighted, our top customers are global technology and financial enterprises.

Speaker #2: The growth was primarily driven by a combination of our largest technology customers as well as new customers. Retail contributed 28.4% of total revenues in the first quarter of 2026.

And this is by design. Our growth strategy is deliberately focused on verticals where AI adoption is accelerating and our capabilities are highly differentiated.

In the first quarter, Revenue breakdown, reflects this redistribution with meaningful diversification into our TMT and financials verticals.

Speaker #2: The finance vertical accounted for 23.5% of total revenues in the quarter and we witnessed strong demand from our banking and fintech customers. For the remainder of 2026, we are bullish on our outlook with our banking and fintech customers.

Looking at the performance of our verticals.

TNT became our largest vertical and accounted for 29.5% of total revenues for the quarter with growth of 30.3% on a year-over-year basis.

Speaker #2: Turning to the remaining verticals, CPG and manufacturing represented 9.4% of quarterly revenues. In the quarter, we witnessed growth from our manufacturing customers in North America and new engagements in Europe.

The growth was primarily driven by a combination of our largest technology customers as well as new customers.

Retail contributed, 28.4% a total revenues in the first quarter of 2026.

Speaker #2: The other vertical contributed 7.1% of first quarter revenues. And finally, healthcare pharma contributed 2.1% of our revenues for the quarter. We ended the first quarter with a total headcount of 4,964, up from 4,961 employees in the fourth quarter of 2025 and from 4,926 in the first quarter of 2025.

Anil Doradla: For the remainder of 2026, we are bullish on our outlook with our banking and fintech customers. Turning to the remaining verticals, CPG and manufacturing represented 9.4% of quarterly revenues. In the quarter, we witnessed growth from our manufacturing customers in North America and new engagements in Europe. The other vertical contributed 7.1% of Q1 revenues. Finally, healthcare pharma contributed 2.1% of our revenues for the quarter. We ended the Q1 with a total headcount of 4,964, up from 4,961 employees in the Q4 of 2025, and from 4,926 in the Q1 of 2025. We continue to rationalize our overall headcount as we align our skill sets and geographic mix.

The finance vertical. Accounted for 23.5% on total revenues in the quarter and we witnessed strong demand from our Banking and fintech customers.

For the remainder of 2026, we are bullish on our outlook with our banking and fintech customers.

Turning to the remaining verticals.

Speaker #2: We continue to rationalize our overall headcount as we align our skill sets, and geographic mix. At the end of the first quarter of 2026, our total US headcount was 353 or 7.1% of the company's total headcount versus 7.2% in the year-over-year quarter.

Cpg, and Manufacturing represented 9.4% of quarterly revenues in the quarter. We witnessed growth from our manufacturing customers, in North America and new engagements in Europe.

The other vertical contributed 7.1% of first quarter revenues.

And finally Healthcare Pharma contributed 2.1% of our revenues for the quarter.

Speaker #2: Our non-US headcount, located in Europe, Americas, and India, was 4,611 or 92.9%. In the first quarter, revenues from our top five and top 10 customers were $40.8% and $59.7% respectively, versus $35.6% and $56.6% in the same period a year ago, respectively.

We ended the first quarter with a total headcount of 4,964 up from 4,961 employees in the fourth quarter of 2025 and from 4,926. In the first quarter of 2025, we continue to rationalize our overall headcount, as we allow our skill sets and Geographic mix.

Anil Doradla: At the end of Q1 2026, our total US headcount was 353 or 7.1% of the company's total headcount versus 7.2% in the year-ago quarter. Our non-US headcount located in Europe, Americas, and India was 4,611 or 92.9%. In Q1, revenues from our top five and top 10 customers were 40.8% and 59.7% respectively versus 35.6% and 56.6% in the same period a year ago respectively.

Speaker #2: Moving to the income statement, our GAAP gross profit during the quarter was $36.2 million or $34.8% compared to $36.1 million or $34% in the fourth quarter of 2025 and $37 million or $36.8% in the year-over-year quarter.

At the end of the first quarter of 2026, our total us headcount was 353 or 7.1% of the company's total headcount versus 7.2% in the year ago quarter. Our non-us headcount located in Europe America's and India was 4,611 or 92.9%

Speaker #2: On a non-GAAP basis, our gross profit was $36.7 million or $35.3% compared to $36.6 million or $34.5% in the fourth quarter of 2025 and $37.6 million or $37.4% in the year-over-year quarter.

In the first quarter revenues from our top 5 and top 10. Customers were 40.8%, and 59.7% respectively versus 35.6% and 56.6% in the same period a year ago. Respectively.

Anil Doradla: Moving to the income statement, our GAAP gross profit during Q1 was $36.2 million or 34.8% compared to $36.1 million or 34% in Q4 2025, and $37 million or 36.8% in the year-ago quarter. On a non-GAAP basis, our gross profit was $36.7 million or 35.3% compared to $36.6 million or 34.5% in Q4 2025, and $37.6 million or 37.4% in the year-ago quarter. On a year-over-year basis, the decline in the gross margin was from a combination of FX headwinds and higher cost structures across our delivery locations.

Speaker #2: On a year-over-year basis, the decline in the gross margin was from a combination of FX headwinds and higher cost structures across our delivery locations.

Moving to the income statement, our gaap gross profit, during the quarter was 36.2 million or 34.8% compared to 36.1 million or 34% in the fourth quarter of 2025 and 37 million or 36.8% in the year goal quarter.

Speaker #2: Non-GAAP EBITDA during the first quarter that excluded interest income, expense, provisions for income taxes, depreciation and amortization, stock-based compensation, restructuring, expenses related to geographic reorganization and transaction and other related costs was $12.5 million or 12% of revenues versus $13.7 million or 12.9% of revenues in the fourth quarter of 2025 and was down from $14.6 million or $14.5% in the year-over-year quarter.

On a non-gaap basis. Our gross profit was 36.7 million or 35.3%, compared to 36.6 million, or 34.5% in the fourth quarter of 2025 and 37.6 million or 37.4% in the year of little quarter.

On a year-over-year basis. The decline in the gross margin was from a combination of FX headwinds and higher costs structures across our delivery locations.

Anil Doradla: Non-GAAP EBITDA during Q1 that excluded interest income expense, provisions for income taxes, depreciation and amortization, stock-based compensation, restructuring, expenses related to geographic reorganization and transaction and other related costs was $12.5 million or 12% of revenues versus $13.7 million or 12.9% of revenues in Q4 2025 and was down from $14.6 million or 14.5% in the year-ago quarter. The sequential and year-over-year decline in EBITDA was largely due to a combination of FX headwinds and higher operating costs.

Speaker #2: The sequential and year-over-year decline in EBITDA was largely due to a combination of FX headwinds and higher operating costs. Our GAAP net loss in the first quarter was $1.5 million or a loss of $0.02 per share based on a diluted share count of 84.7 million shares compared to the fourth quarter net income of $0.3 million or break-even per share based on diluted share count of 86.4 million and net income of $2.9 million or $0.03 per share based on 87.8 million diluted shares in the year-over-year quarter.

Non-GAAP EBITDA during the first quarter, that excluded interest income and expense.

Anil Doradla: Our GAAP net loss in Q1 was $1.5 million, or a loss of $0.02 per share based on a diluted share count of 84.7 million shares, compared to the Q4 net income of $0.3 million, or breakeven per share based on diluted share count of 86.4 million, and net income of $2.9 million, or $0.03 per share based on 87.8 million diluted shares in the year-ago quarter. On a non-GAAP basis, in Q1, our non-GAAP net income was $7.5 million, or $0.09 per share based on 85.9 million diluted shares, compared to the Q4 non-GAAP net income of $8.7 million, or $0.10 per share based on 86.4 million diluted shares, and $10 million, or $0.11 per share based on 87.8 million diluted shares in the year-ago quarter.

Million or 12% of revenues versus 13.7 million or 12.9% of revenues in the fourth quarter of 2025 and was down from 14.6 million or 14.5%. In the year low quarter. The sequential and year-over-year decline in Evita was largely due to a combination of FX headwinds and higher operating costs.

Speaker #2: On a non-GAAP basis, in the first quarter, our non-GAAP net income was $7.5 million or $0.09 per share based on 85.9 million diluted shares compared to the fourth quarter non-GAAP net income of $8.7 million or $0.10 per share based on 86.4 million diluted shares and $10 million or $0.11 per share based on 87.8 million diluted shares in the year-over-year quarter.

Our GAAP net loss in the first quarter was $1.5 million, or a loss of $0.02 per share, based on a diluted share count of 84.7 million shares, compared to the fourth quarter net income of

3 million.

Speaker #2: On March 31, 2026, our cash and cash equivalents totaled $327.5 million down from $342.1 million on December 31, 2025. Since our fourth quarter earnings call, we repurchased approximately $1.8 million shares for a total consideration of $11.5 million.

our break even per share, based on diluted share count of 86.4 million and net income of 2.9 Million or 3 cents per share based on 87.8%

Speaker #2: Since our board authorized the $50 million share repurchase program, we have repurchased approximately $2 million shares for a total of $13.5 million. Reflecting our continued confidence in the long-term value of the business.

Anil Doradla: On 31 March 2026, our cash and cash equivalents totaled $327.5 million, down from $342.1 million on 31 December 2025. Since our Q4 earnings call, we repurchased approximately 1.8 million shares for a total consideration of $11.5 million. Since our board authorized the $50 million share repurchase program, we have repurchased approximately 2 million shares for a total of $13.5 million, reflecting our continued confidence in the long-term value of the business. M&A continues to take priority in our capital allocation strategy. We are committed to augmenting our organic business with acquisitions that strategically enhance our capabilities, geographic presence, and industry verticals. Coming to the Q2 guidance, we expect revenues to be in the range of $106 million to $108 million.

On a non-GAAP basis, in the first quarter, our non-GAAP net income was $7.5 million, or $0.09 per share, based on 85.9 million diluted shares. This compares to the fourth quarter non-GAAP net income of $8.7 million, or $0.10 per share, based on 86.4 million diluted shares, and $10 million, or $0.11 per share, based on 87.8 million diluted shares.

Speaker #2: M&A continues to take priority in our capital allocation strategy. We are committed to augmenting our organic business with acquisitions that strategically enhance our capabilities geographic presence and industry verticals.

On March 31st 2026, our cash and cash. Equivalents total 327.5 million down from 342.1 million on December 31st 2025.

Since our fourth quarter earnings call, we repurchased approximately 1.8 million shares for a total consideration of 11.5 million.

Speaker #2: Coming to the second quarter guidance, we expect revenues to be in the range of $106 million to $108 million. We expect our second quarter non-GAAP EBITDA to be in the range of $14 million to $15 million.

Since our board authorized the million dollar share repurchase program, we have repurchased approximately 2 million shares for a total of 13.5 million, reflecting our continued confidence in the long-term, value of the business.

Speaker #2: For Q2 2026, we expect our basic share count to be in the range of $84 to $85 million. And our diluted share count to be in the range of $85 to $86 million.

Speaker #2: For the full year 2026, we're maintaining our revenue outlook of $435 million to $465 million. That concludes my prepared remarks. We're ready to take your questions.

M&A continues to take priority in our capital allocation strategy. We are committed to augmenting our organic business with acquisitions that strategically enhance our capabilities, geographic presence, and industry verticals.

Anil Doradla: We expect our Q2 non-GAAP EBITDA to be in the range of $14 million to $15 million. For Q2 2026, we expect our basic share count to be in the range of 84 million to 85 million, and our diluted share count to be in the range of 85 million to 86 million. For the full year 2026, we're maintaining our revenue outlook of $435 million to $465 million. That concludes my prepared remarks. We're ready to take your questions.

coming to to the second quarter guidance, we expect revenues to be in the range of 106 million to 108 million

We expect our second quarter, non-gaap ebita to be in the range of 14 million to 15 million dollars.

For Q2 2026, we expect our basic share count to be in the range of 84 to 85 million and our diluted share count to be the range of 85 to 86 million.

Speaker #1: 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.

For the full year 2026, we're maintaining our Revenue Outlook of 435 million to 465 million.

Speaker #1: First question comes from Puneet Jain of JPMorgan. Go ahead, Puneet.

That concludes my prepared remarks.

We're ready to take your questions.

Speaker #3: Hey, thanks for taking my question. So Leonard, thanks for sharing updates on the, again, framework. As these platforms become increasingly integrated in your delivery, could you talk about the impact it has on overall operations?

Cary Savas: Thank you, Anil. As we go into the Q&A session of this call, I will first announce your name. At that point, please unmute yourself and turn on your camera. First question comes from Puneet Jain of JPMorgan. Go ahead, Puneet.

Thank you, O'Neal.

Speaker #3: Say, like, are these necessarily fixed price contracts? Do clients pay for tokens like or for LLMs? Or are they bundled in your overall services?

As we go into the Q&A session of this call, I will first announce your name at that point. Please unmute yourself and turn on your camera. First question comes from Punnett Jane of JP Morgan.

Go ahead, please.

Puneet Jain: Hey, thanks for taking my question. Leonard, thanks for sharing updates on the GAIN framework. As these platforms become increasingly integrated in your delivery, could you talk about the impact it has on overall operations? Say, like, are these necessarily fixed price contracts? Do clients pay for tokens, like, or for LLMs or are they bundled in your overall services? You talked about, like, forward deployed engineers. Like, can you train your current employees to be FDEs or do you have to change your hiring mix to be able to offer GAIN platform to your customers?

Speaker #3: And you talked about, like, forward deployed engineers. Like, can you train your current employees to be FDEs? Or do you have to change your hiring mix to be able to offer gain platform to your customers?

Hey, thanks for taking my question. Um,

So, uh, let me thank you for sharing updates on the, again, uh, framework. Uh, as these platforms become increasingly integrated.

Speaker #1: I think, Puneet, yeah, let me try to unpack some of your questions. It's a lot in one. But, you know, let's go backwards. It's probably a little bit easier.

Uh, in your delivery. Could you talk about the impact? It has on overall operations say like are these necessarily fixed price contracts do clients pay for tokens like or

Speaker #1: So let's start with engineering talent and, you know, forward deployed engineers. Majority of the people who we deploy obviously are internally trained. We have a large number, substantial large number of very technically educated people who we internally build our services and promotions and train them in the models.

For llms or are they bundled in your overall services? And you talked about like, uh, forward deployed Engineers? Like can you train your current employees to be fdes? Or do you have to change your hiring mix, uh, to be able to offer gain platform to your customers?

Leonard Livschitz: I think we need. Yeah, let me try to unpack some of your questions. It's a lot in one. You know, let's go backwards, probably a little bit easier. Let's start with engineering talent and, you know, forward deployed engineers. Majority of the people who we deploy, obviously are internally trained. We have a large number, substantial large number of very technically educated people who we internally build our services and promotions and train them in the models. It's led by our R&D organization. You see, Eugene is gonna give you some more comments which combining with the retraining the delivery organization bring us the talent. Obviously, when we bring the talent from the market, it still needs to be structured. They're gonna be able to adapt Grid Dynamics GAIN platform's approach.

Speaker #1: And it's led by our R&D organizations. So you see Eugene is going to give you some more comments, which combining with the retraining the delivery organization brings us the talent.

I think you can, you know, let me try to unpack some of your questions. It's a lot in 1 but um, you know, let's let's go backwards. Probably a little bit easier. So let's start with engineering talent and, you know, forward deployed Engineers. Um,

Speaker #1: Obviously, when we bring the talent from the market, it still needs to be structured. So they're going to be able to adapt redynamics, gain, platforms approach.

Majority of the people who we, uh, deploy, obviously are internally trained.

Uh, we have a

large number substantial, large number of, very

Speaker #1: And the gain platforms approach is really what makes us different. So rather than talking about a very specific model for each individual customer, let me explain a little bit in the words what this new platforms means for the contracts.

Speaker #1: So basically, we developed a lot of tools over time. And even last board meeting, we introduced lots of lots of different names. And now we're maturing to the point that we can offer a suite of solutions to the client where we actually define a kind of a combination of redynamics IP and open available sources into the total solution.

Leonard Livschitz: The GAIN platform's approach is really what makes us different. Rather than talking about a very specific model for each individual customers, let me explain a little bit in the words what this new platforms means for the contracts. Basically, we developed a lot of tools over time, and even last board meeting we introduced lots and lots of different names. Now we're maturing to the point that we can offer a suite of solutions to the client, where we actually define a kind of a combination of Grid Dynamics IT and opens available sources into the total solution. The total solutions which we offer are driven by adoption of the engineers and agents in the form of the guidance where we expect a return on investment for the clients.

Signing with a retraining, the the delivery organization brings us the talent, obviously, uh, when we bring the talent from the market, it still needs to be structured. So uh they going to be able to adapt. Renaming gain platforms approach.

And again, uh, platforms approach is really what makes us different. So, um, rather than talking about a very specific model, for each individual customers, uh, let me explain a little bit. In the words, what this new platforms means for the contracts.

Speaker #1: And the total solutions, which we offer, are driven by adaption of the engineers and agents in the form of the guidance where we expect the return on investment for the clients.

Speaker #1: So answering your question, the number of non-TNM projects and because there's a lot, there's a tokenization, there's offering all the fixed bid, there's a performance-related, they are significantly increased.

So basically, um, we developed a lot of tools over time. And even the last board meeting we introduced lots of lots of different names. And uh, now we're maturing to the point that we can offer a suite of solutions

Speaker #1: And they continue to increase. And you will actually see that as we continue to answer your questions today because that model, itself, requires not only training the FD engineers, but adapting the internal processes and a program management, delivery management team to actually control a proper engagements in a different venue.

Leonard Livschitz: Answering your question, the number of non-T&M projects, because there's a lot, there's a tokenization, there's offering of the C's bid, there's a performance related. They are significantly increased, and they continue to increase. You will actually see that as we continue to answer your questions today, because that model itself requires not only training the FD engineers, but adapting the internal processes and the program management, delivery management team to actually control a proper engagement in a different venue. Answering your question, definitely there is a big shift toward not T&Ms. The training and rollout of our engineering force is going very successfully. You haven't seen right now from the absolute number of employees how the dynamics of the headcount has changed yet because number looks flat.

To the client where we actually Define a kind of a combination of green namings, it and uh, opens available sources into the total solution and the total Solutions, which we offer are driven by adoption of the engineers and agents in the form of, uh, the guidance where we expect the return on investment for the clients. So, answering your question, the number of non tnm projects and because there's a lot, there's a tokenization, there's offering all the 6 bit the

Speaker #1: So answering your question, definitely there is a big shift toward not TNMs. The training and rollout of our engineering force is going very successfully.

Speaker #1: You haven't seen right now from the absolute number of employees how the dynamics of the headcount has changed yet because number looks flat. But if you again unpack that number, you will see a significantly higher contribution of the engineering workforce because some of them require an additional training and reclassification before we deploy them to the clients.

There's a performance related. They they are significantly increased and they continue to increase and you will actually see that as we continue to answer your questions today because that model itself.

Speaker #1: But the good news is an overall, we have a very strong vector where we are building our position with adopting well, clients, new models, relates to the gain platforms.

Speaker #3: Got it. That's a big change. And so it seems like you are already doing like a lot of hard work that's involved. Let me ask Anil, so the guidance, like the full year on top line, so it does imply like the mid-single digit growth, even in the lower half, mid-single digit average sequential growth in second half to hit the lower half of the guidance.

Leonard Livschitz: If you, again, unpack the number, you will see a significantly higher contribution of the engineering workforce, because some of them require an additional training and reclassification before we deploy them to the clients. The good news is, overall, we have a very strong vector where we are building our position with adopting, well, clients' new models relates to their GAIN platforms.

Requires not only training the FD Engineers, but adapting the internal processes and the program management driven management team to actually control a proper engagement in a different way. So, enter your question, definitely, there's a big shift toward not, uh, tnms the training and roll out of our engineering force is going very successfully. You haven't seen right now from the absolute number of employees, how the, uh, dynamics of the headcount has changed yet because number looks flat. But if you again unpack the number, you will see a significantly higher contribution of the engineering Workforce because some of them require an additional training and reclassification before we deploy them to the clients. But the good news is an overall, we have a very strong Vector where we are building our position with adopting uh well clients new models relates to the game.

Speaker #3: So what drives the confidence or the visibility on achievement of this guidance for the full year?

Puneet Jain: Got it. Now, it's a big change, and so, it seems like you're already doing, like, lot of hard work that's involved. Let me ask Anil. The guidance, like, the full year on top line, it does imply, like, the mid-single digit growth even in the lower half. Mid-single digits average sequential growth in H2 to hit the lower half of the guidance. What drives the confidence or the visibility on achievement of this guidance for the full year?

Got it. No, it's a big change. And so uh, it seems like um, you have you are already doing like a lot of hard work that's involved.

Speaker #4: So there are two or three factors here. Leonard, do you want to talk about pipeline? Then I can take it.

Speaker #1: Well, I will answer the easy part. And then Anil will dive in a little bit of the numbers. You know, there are two parts of the confidence level we have.

Um, let me ask anel. Uh, so the guidance like the full year on Topline um

Speaker #1: The number one in the demand has grown substantially. So we are the record number of demand. And I'm avoiding the word number of engineering demand.

So it does imply like the mix single-digit growth even in the lower half uh mix single digit. Sic average sequential growth in second half to hit the lower half of the guidance.

so,

Speaker #1: Because again, we're talking about the teams, the platforms, the offering. But overall demand, the vector is very steep right now. That's a subjective factor because again, this could happen and may not happen or whatever, but it's good news.

Anil Doradla: There are two or three factors here. Leonard, do you wanna talk about pipeline, then I can take it?

What drives the confidence or the visibility uh, on achievement of this guidance, for the full year?

Anil Doradla: There are two or three factors here. Leonard, do you wanna talk about pipeline, then I can take it?

Leonard Livschitz: Well, I will answer the easy part. Anil will dive in a little bit of the numbers. You know, there are two parts of the confidence level we have. The number 1, the demand has grown substantially. We are the record number of demand, I'm avoiding the word number of engineering demand because, again, we're talking about the teams, the platforms, the offering, but overall demand, the vector is very steep right now. That's a subjective factor because, again, this could happen, it may not happen or whatever, but it's a good news. It's a record high. The more interesting factor is, Anil will dive into the financial estimates, we are facing a larger, as I mentioned in the previous comment to you, number of non-T&M projects.

Speaker #1: It's a record high. The more interesting factor is, and Anil will dive into the financial estimates, we are facing a larger as I mentioned in the previous comment to you, number of non-TNM projects.

So, uh, there are 2 or 3 factors here, Leonard, do you want to talk about python then I can take him? Well, um, I will answer the easy part and then, uh, and you will have a little bit of the numbers, you know? Um, there are 2 parts of the confidence level. We have the number 1 in. Um the demand has grown substantially

Speaker #1: These work for is defined by a different estimate how do we qualify the revenue based on this project in which point. So when we unpack the number, we are a bit more conservative, which we're going to guide this particular quarter or the next quarter because now it becomes a little bit more of a financial exercise.

So, we are the record number of demand, and I'm avoiding the word number of engineering demand, because again, we're talking about the teams, the platforms, they're offering. But overall demand the vector is, is is very steep right now. That's a subjective Factor because, again, this could happen and may not happen or whatever, but it's a good news, it's a record time.

Speaker #1: The work is being signed. The work is going on. But Anil probably will give you a little bit better feedback. But the summary for you, the takeaway for me, two parts.

Leonard Livschitz: This work for is defined by a different estimate, how do we qualify the revenue based on this project, in which point? When we unpack the number, we are a bit more conservative, which we're gonna guide this particular quarter or the next quarter, because now it becomes a little bit more of a financial exercise. The work has been signed, the work is going on, Anil probably give you a little bit better feedback. The summary for you, the takeaway from me, two parts: significantly higher, you know, number of the pipeline, and a very large number of the non-T&M project, which require a little bit more financial attention how we guide the numbers for the near future, for next couple of months.

The more interesting factor is and and you will dive into the financial estimates. We are facing a larger. As I mentioned in the previous coming to you number of non tnm projects,

these work for, is defined by a

Speaker #1: Significantly higher number of the pipeline and a very large number of the non-TNM project, which require a little bit more financial attention. How we guide the numbers for the near future, for next couple of months.

Speaker #4: Yeah. No, look, I mean, Leonard, you pretty much hit it. Let me kind of build upon that. Leonard and the team in our prepared remarks talked about a fundamental transformation on how we're moving.

Different estimate. How do we qualify the revenue based on this project in which point so when we I'm taking the number we are a bit more conservative which we're going to guide this particular quarter or the next quarter, because now it becomes a little bit more of uh, Financial exercise.

Speaker #4: And the word you will see again and again is a platform. Now, the historical approach we all know is that you take the engineer, you have a certain TNM rate, you multiply it by hours, days, and the formula, as you know, is a very linear.

Speaker #4: We're transitioning. We're seeing that. Rahul is leading the way. From a partnership and Eugene is leading the way, obviously, on the CTO. We've introduced all these new products and platforms, and we're working on monetization.

Anil Doradla: Yeah. No, look, I mean, Leonard, you pretty much hit it. Let me kind of build up on that. Leonard and the team in our prepared remarks talked about a fundamental transformation on how we're moving, and the word you will see again and again is a platform. The historical approach we all know is that you take the engineer, you have a certain T&M rate, you multiply it by hours, days, and the formula, as you know, is very linear. We're transitioning. We're seeing that. Rahul is leading the way from a partnership, and Eugene is leading the way, obviously, on the CTO. We've introduced all these new products and platforms, and we're working on monetization. There are stages of monetization. There's upfront, that we'll get start off small.

Significantly higher, uh, you know, number of the pipeline and a very large. Number of the non tnm project which require a little bit more financial attention, how we guide the numbers for the near future for next couple of months? I mean, yeah, no look. I mean Leonard, uh, you pretty much hit it. Let me kind of build upon that.

Speaker #4: Now, there are stages of monetization. There's upfront that will get started small. There's greater stickiness with these engineers. And as our clients become comfortable with both our products as well as our engineers in this new model, that's when we start seeing a lot more monetization there.

Leonard and the team in our prepared, remarks talked about a fundamental transformation on how we're moving.

And the word you will see. Again again is a platform.

Speaker #4: So when we started looking at these numbers, the obviously revenue recognition is a key component to it, right? And we're taking it think of it as baby steps right now.

Speaker #4: We see the pipeline. I look at year to date from January 1 through now, compare that with last year. Really good. I look at some of these initiatives we're working on on AI.

Anil Doradla: There's greater stickiness with these engineers, and as our clients become comfortable with both our products as well as our engineers in this new model, that's when we start, you know, seeing a lot more monetization there. When we started looking at these numbers, obviously revenue recognition is a key component to it, right? Think of it as baby steps right now. We see the pipeline. I look at year-to-date, from 1 January through now, compare that with last year, really good. I look at some of these initiatives we're working on AI, really good. The question will be, how do we time it? Is it a linear timing or nonlinear timing? From that context, for the full year, we're keeping it. Now let's see the couple of quarters. You know.

Now, the historical approach, we all know is that you take the engineer, you have a certain tnm rate you multiply by hours days and the formula as you know, is a very linear, we're transitioning. We're seeing that Rahul is leading the way from a partnership and Eugene is leading the way obviously, on the CTO, we've introduced all these new uh, products and platforms and we're working on monetization. Now, there are stages of monetization, there's upfront that we'll get started off small.

Speaker #4: Really good. But the question will be, how do we time it? Is it a linear timing or non-linear timing? So from that context, for the full year we're keeping it.

Speaker #4: Now, let's see the couple of quarters. You know, do we is it does it turn out much stronger? Because we have some of the recognitions or not.

Speaker #4: So we're still experimenting with this. We're working through it. So the optics of it looks slightly different from what you can see underneath from a business point of view.

Speaker #1: Now, let me add one more factor because it could be a bit missed from the first point of view. We also got a substantially better margins.

There's greater stickiness with these engineers and as our clients become comfortable with both our products, as well as our engineers in this new model. That's when we start, you know, seeing a lot more monetization there. So, when we started looking at these numbers, um, the obviously Revenue recognition is a key component to it, right? And we're taking it think of it as baby steps. Right now, we see the pipeline, I look at here to date from January 1 through now, compare that with last year. Brilliant but

Speaker #1: So if you look at the delta between Q1 and Q2, you may ask a question, how can you grow such a steep increase of profitability on relatively modest increase of revenue?

Anil Doradla: Does it turn out much stronger because we have some of the recognitions or not? We're still experimenting with this. We're working through it. The optics of it look slightly different from what you can see underneath from a business point of view.

Speaker #1: So it gives you a little bit more a story that we look at a new projects we've been awarded to us as Rahul was mentioning in his statement at a different margin profile than occurred business, which is don't want to run ahead of the time and do the all the financial qualification of that till we see the results.

Leonard Livschitz: Now let me add one more factor because it could be a bit missed from the first point of view. We also guide substantially better margins. If you look at the delta between Q1 and Q2, you may ask a question, How can you grow such a steep increase of profitability on relatively modest increase of revenue? This gives you a little bit more a story that we look at the new projects we've been awarded to us. As Rahul was mentioning in his statement, that a different margin profile than the current business. We just don't wanna run ahead of the time and all the financial qualification of that till we see the results. We are very confident in the progress we're about to make.

I look at some of these initiatives we're working on on AI really good but the question will be how do we time it? Is it a linear timing or non-linear timing? So from that context for the full year we're keeping it. Now let's see the couple of quarters you know do we is it does it turn out much stronger because we have some of the recognitions or not. So we're still experimenting with this. We're working through it. So the Optics of it looks like different from what you can see underneath from a business point of view. Now, let me add 1 more Factor because it could be a bit missed from the first point of view, we also got a substantially better margins.

Speaker #1: But we are very confident in the progress we're about to make.

Speaker #3: Got it. So it seems like you are at the cusp of that monetization and that drives the confidence. No, I appreciate it. Thanks for the color.

So if you look at the Delta between q1 and Q2, you may ask a question, how can you grow such uh uh, steep increase of profitability, on relatively modest increase of Revenue?

Speaker #1: Thank you.

Speaker #4: Thank you.

Speaker #2: Thank you, Puneet. The next set of questions comes from Maggie Nolan of William Blair. Go ahead, Maggie.

Speaker #5: Hi. Thank you. I wanted to ask about your partner revenue that crossed 19% of revenue. So where do you anticipate that going? And to what extent do you expect that to be a positive margin driver for the company?

Puneet Jain: Got it. It seems like you are at the cusp of that monetization, and that drives the confidence. No, I appreciate it. Thanks for the color.

So it gives you a little bit more of a story that we look at a new projects. We've been awarded to us as Rahul was mentioning in in his statement, that a different margin profile than our current business. We just don't want to run ahead of the time and do the all the financial qualification of that till we see the results. But we are very confident in the progress. We're about to make

Speaker #1: I think maybe the best way to start it is with the person who is responsible for that. I think Rahul, you have a perfect opportunity to tell how you build the business, continue to grow.

Leonard Livschitz: Thank you.

Anil Doradla: Thank you.

Cary Savas: Thank you, Puneet. The next set of questions comes from Maggie Nolan of William Blair. Go ahead, Maggie.

Okay. So it seems like you are at the cusp of that monetization and that drives the confidence. Know, I appreciate it. Thanks for the color. Thank you. Thank you.

Speaker #1: So please go ahead.

Speaker #6: Yeah. Thanks for that question, Maggie. Like you have seen, partnerships have become one of our key go-to-market channels. And it will continue to be.

Thank you, Punnett. The next set of questions comes from Maggie, Nolan of William. Blair, go ahead. Maggie.

Maggie Nolan: Hi. Thank you. I wanted to ask about your partner revenue that crossed 19% of revenue. Where do you anticipate that going, and to what extent do you expect that to be a positive margin driver for the company?

Hi, thank you.

Speaker #6: We have a long-term goal to get to about 25% to 30% of our revenues being influenced by partnerships. And we are well on our path to achieve that.

Leonard Livschitz: I think, Maggie, the best way to start it is with the person who is responsible. I think, Rahul, you have a perfect opportunity to tell how you build the business continue to grow. Please go ahead.

I wanted to ask about your partner Revenue, that crossed 19% of Revenue, so where do you anticipate that going and to? What extent do you expect that to be a positive, margin driver for the company?

Speaker #6: In fact, I would say we are tracking slightly ahead when we look at our internal goals to achieve that. And with gain platforms being deployed, on the hyperscaler marketplaces, we'll probably see acceleration of that partner interest revenues in the future quarters.

Rahul Bindlish: Yeah. Thanks for that question, Maggie. Like you have seen, partnerships have become one of our key go-to-market channels, and it'll continue to be. We have a long-term goal to get to about 25% to 30% of our revenues being influenced by partnerships. We are well on that path to achieve that. In fact, I would say we are tracking slightly ahead when we look at our internal goals to achieve that. With GAIN platforms being deployed on the hyperscaler marketplaces, we'll probably see acceleration of that partner influence revenues in the future quarters.

Um, I—I think, I mean, the best way to start is with a person who is responsible for that. I think, uh, Rahul, you have a perfect opportunity to tell how you built the business and continued to grow. So, please go ahead. Uh, thanks for that question, Maggie. Uh,

Speaker #1: So let me just add one more color, Megan, this. Rahul, a bit kind of mentioned in his prepared remarks, but it's important because, again, it's new.

Like you have seen Partnerships have become 1 of our key go-to Market channels, uh and it will continue to be uh we have a long-term goal to get to about 25 to 30% of our revenues being influenced by Partnerships.

Speaker #1: So we talk with Puneet about the new model of the business. Now we talk a little bit of different model of engagement with our partners.

And, uh, we are well on our path to achieve that. In fact, uh, I would say we are tracking slightly ahead, uh, when we look at our internal goals to achieve that.

Speaker #1: In the past, we basically been talking about hyperscalers. And that was a very consistent message because, frankly, the influence revenue generated with these partnerships.

Speaker #1: Now we're re starting adding especially with the physical AI, some interesting new level of partnerships. And monetization is a little bit lower, but yet but we see a substantial growth because now we're adding into relation with a heavy hitters in the industry because it adds more addressable markets.

Leonard Livschitz: Let me just add one more color, Maggie, on this. Rahul a bit kind of mentioned in his prepared remarks, but it's important because, again, it's new. We talked with Puneet about the new model of the business. Now we talk a little bit of different model of engagement with our partners. In the past, we've basically been talking about hyperscalers, and that was a very consistent message because frankly, the influence revenue generated with these partnerships. Now we start adding, especially with the Agentic AI, some interesting new level of partnerships. Monetization is a little bit lower, but yet, we see a substantial growth because now we're adding intellectual with the, you know, heavy hitters in the industry because it adds more addressable markets.

And it gain platforms, being deployed on the hyperscaler marketplaces. Uh we'll probably see acceleration of that partner interest revenues uh in the future quarters.

Speaker #1: The other element, which is kind of getting also related to our gain platforms, it's a consultancy. So now we're also getting partnerships with some of the business organizations, which asking us to become the lead technology implementation partner, which adding a little bit more of the flavor from transition from the business conceptual idea to implementation relates to specific AI platforms.

So let me just add 1 more caller, Megan this um Rahul a bit kind of mentioned in in his prepared remarks but it's it's important because again, it's new. So we talked with Punnett about the new model of the business. Now we talked a little bit of different model engagement with our partners uh in the past we may actually be talking about hyperscalers and that's was a very consistent is because frankly the influence revenue generated with these Partnerships now we're starting uh especially with the physical AI. Some interesting new level of Partnerships.

Leonard Livschitz: The other element, which is kind of getting also related to our GAIN platforms, is the consultancy part. Now we're also getting partnerships with some of the business organizations which asking us to become the lead technology implementation partner, which adding a little bit more of the flavor from transition from the business conceptual idea to implementation relates to specific AI platforms. As you know, business leaders are a little bit more cautious about spending the budget because you can spend a lot of money on experimentation. They would like to seek some clarity where they would have a confidence that the investment is not gonna be just risky, but send them to wrong direction. GreenLake is becoming the partner that our consultancy works. I think it's another really important difference from the past.

More addressable markets.

Speaker #1: As you know, business leaders are a little bit more cautious about spending the budget because you can spend a lot of money on experimentation.

The other element, which is kind of also getting related to game platforms, is the consultancy part.

Speaker #1: So they would like to seek some clarity where they would have a confidence that the investment is not going to be just not just risky, but send them to the wrong direction.

So now we're also getting Partnerships with some of the business organizations which asking us to become the lead technology, implementation partner, which adding a little bit more.

Speaker #1: And Gryzlov is becoming the partner that a consultancy works. So I think it's another really important difference from the past.

From.

Speaker #5: Got it. Thank you. And then on the TMT growth, do you think that's durable into the back half of the year? To what extent was that driven by concentration with particular clients and what's the visibility into those clients?

Speaker #5: That drove that.

Speaker #4: Yeah. Maggie, that's clearly a highlight. And it's super exciting. Even not only the TMT, but if you look at some of our financial clients there, we have seen many of these customers, consolidating.

Transition from the business conceptual idea to implementation relates to specific AI platforms. As, you know, Business Leaders are a little bit more cautious about spending the budget because you can spend a lot of money on experimentation. So they would like to seek some clarity where they would have a confidence that the investment is not going to be, just not just risky, but send them to the wrong direction and it's becoming the partner that a consultancy works. So I think it's another really important. Uh, difference from the past.

Maggie Nolan: Got it. Thank you. Then on the TMT growth, do you think that's durable into the back half of the year? To what extent was that driven by concentration with particular clients? What's the visibility into those clients that drove that?

Got it. Thank you. And then on the

Speaker #4: And the other thing is that in some of them, we have now become a preferred vendor. We were always there, but now as they were consolidating, we've reached the preferred vendor status.

Anil Doradla: Maggie, that's clearly a highlight, and it's super exciting. Even not only the TMT, but if you look at some of our financial clients there, we have seen many of these customers consolidating. The other thing is that in some of them, we have now become a preferred vendor. We were always there, but now as they were consolidating, you know, we've reached the preferred vendor status. With the TMT, there are two nuances to the movement. There's obviously our work with them, what we're doing. They know what AI is, and they appreciate us. It's a very interesting thing. The smartest technology customers are the one who are seeking our AI capabilities the most, which is a little counterintuitive, right?

Speaker #4: With the TMT, there are two nuances to the movement. There's obviously our work with them, what we're doing. They know what AI is, and they appreciate us.

Do you think that's durable into the back half of the year to what extent was that driven by concentration with particular clients and and what's the visibility into those clients? Um, that that drove that yeah Maggie. That's clearly a highlight and it's it's super exciting. Um,

even not only the TNT, but if you look at some of our financial, uh, clients there,

Speaker #4: It's a very interesting thing. The smartest technology customers are the ones who are seeking our AI capabilities the most, which is a little counterintuitive, right?

We have seen.

Many of these customers consolidating.

and,

Speaker #4: But the other interesting thing that is going on with these customers is that there's a hyperscaler relationship too. So on both fronts, we are seeing a lot of activity.

The other thing is that, in some of them, we have now become a preferred vendor. We were always there, but now, as they were consolidating, you know, we've reached the preferred vendor status.

Speaker #4: Now, every quarter, there might be some positive negatives moving there, but the trajectory is very strong as we get consolidated, as we're one of the few vendors, as we've got a clean sheet with many of these new stakeholders.

Speaker #4: And we augment that with some of the hyperscaler growth that is going on.

Anil Doradla: The other interesting thing that is going on with these customers is that there's a hyperscaler relationship too. On both fronts, we are seeing a lot of activity. Now, every quarter there might be some positives, negatives moving there, but the trajectory is very strong as we get consolidated, as we're one of the few vendors, as we've got a clean sheet with many of these new stakeholders, and we augment that with some of the hyperscaler growth that is going on.

With the TMT. There are 2 nuances to the movement. There's obviously our work with them. What we're doing, they know what AI is and they appreciate us. It's a very interesting thing. The smartest technology customers are the 1, who are seeking our AI capabilities in both which is a little counterintuitive, right?

Speaker #1: Yeah. But I think the important color, very specific color for you, Maggie, is that Anil mentioned about selection being a preferred vendor. We're not talking about generic preferred niche vendor anymore.

Speaker #1: The AI proliferation equalizes the supply base. In other words, there is the size does not provide advantage to some of the largest vendors. The capability of deploying AI solution at scale has been determined as a vital part.

Leonard Livschitz: Yeah. I think the important color, very specific color for you, Maggie, is that Anil mentioned about selection being a preferred vendor. We're not talking about generic preferred niche vendor anymore. The AI proliferation equalize the supply base. In other words, the size does not provide advantage to some of the largest vendors.

But the other interesting thing, uh, that is, uh, uh, going on with these, uh, customers is that there's a hyperscaler relationship, too. So, on both fronts, we are seeing a lot of, uh, activity. Now, every quarter, there might be some positives moving, uh, negatives moving there. But the trajectory is very strong as we get consolidated, as we're one of the few vendors, as we've got, agree, uh, a clean sheet with many of these, uh, state new stakeholders. And we augment that with some of the hyperscaler, uh, growth that is going on.

Speaker #1: And being a smaller company and being able to transition faster remember, again, the very first question from Puneet, how quickly we can train people.

Yeah but I think the important color very specific color for you me is that uh Anil mentioned about selection being a preferred vendor. We're not talking about generic, preferred nishin vendor anymore.

The AI proliferation equalize.

Speaker #1: It's amount of quality work with those specialized teams which determine our awards on the business side. And with the TMTs, it's definitely the number one, followed right now with the financial clients.

The supply base. In other words, there is the size does not provide advantage.

Anil Doradla: Yeah.

Anil Doradla: The capability of deploying AI solution at scale has been determined as a vital part. Being a smaller company and being able to transition faster, remember this again, the very first question from Puneet, how quickly we can train people, it's amount of quality work with those specialized teams which determine our awards on the business side. With the TMTs, it's definitely the number one, followed right now with the financial clients. We'll talk a little bit more about others as time comes. The top five, top six clients, we are in the driver's seat for AI deployments.

Leonard Livschitz: The capability of deploying AI solution at scale has been determined as a vital part. Being a smaller company and being able to transition faster, remember this again, the very first question from Puneet, how quickly we can train people, it's amount of quality work with those specialized teams which determine our awards on the business side. With the TMTs, it's definitely the number one, followed right now with the financial clients. We'll talk a little bit more about others as time comes. The top five, top six clients, we are in the driver's seat for AI deployments.

To some of the largest vendors.

The capability of deploying AI solution at scale.

Speaker #1: We'll talk a little bit more about others at time comes. But the top five to six clients we are in the driver's seat for AI deployments.

Speaker #5: Great. Thank you. Next quarter.

Speaker #4: Thank you. Thank you, Maggie.

Has been determined as a vital part and being a smaller company and being able to transition faster. Remember this again, the very first question from Benin how quickly we can train people. It's amount of

Speaker #1: Thank you, Maggie. The next question comes from Surinder Thind of Jefferies. Go ahead, Surind.

Speaker #6: Thank you, guys. When we think about the non-time and materials model, how do we think about the incremental risk that you're taking on? Obviously, over the past decade, two decades, we moved in that direction because projects got bigger.

quality work with those specialized teams, which determine our Awards on the business side. And with the tmts, it's definitely the, uh, the number 1.

Followed.

Right now with the financial clients, we'll we'll talk a little bit more about others. Time comes, but the top 5 tax 6 clients. We are in the driver's seat for a deployments.

Maggie Nolan: Great. Thank you. Nice quarter.

Anil Doradla: Thank you.

Leonard Livschitz: Thank you.

Anil Doradla: Thank you.

Anil Doradla: Thank you, Maggie.

Cary Savas: Thank you, Maggie. The next question comes from Surinder Thind of Jefferies. Go ahead, Surinder.

Speaker #6: They got more complex. There was maybe greater uncertainty about scope or changes in scope. How does that work in a new model? Because if you're looking at an outcome-based or fixed-price token usage, where is the risk in the model for you guys?

Right. Thank you. Nice quarter. Thank you. Thank you Maggie. Thank you Maggie. The next question. Comes from surrender. Thinned of Jeffrey's. Go ahead sir.

Surinder Thind: Thank you, guys. When we think about the non-T&M model, how do we think about the incremental risk that you're taking on? Obviously, over the past decade, 2 decades, we've moved in that direction because projects got bigger, they got more complex. There is maybe greater uncertainty about scope or changes in scope. How does that work in a new model? Because if you're looking at an outcome-based or fixed-price, token usage, like, where is the risk in the model for you guys? How are you guys addressing it?

thank you guys when when we think about

Um, the non-time materials model.

Speaker #6: Or how are you guys addressing it?

Speaker #1: Good. So Surinder, I will actually have Eugene Steinberg, our CTO, to start talking because he's a bit of an architect of the system. And then certainly, has two prongs.

How do we think about the incremental risk that you're taking on? Obviously, over the past decade to decades, we've moved in that direction because

Projects got bigger. They got more complex.

Speaker #1: One of them is a risk level. The second one is a reward level. And I will let Eugene talk about the coexistence of both and how we handle it.

There was maybe greater uncertainty about scope or changes in scope.

How does that work in a new model? Because—

Speaker #1: Please, Eugene.

Speaker #7: Yes. Of course. When you are taking a fixed-price project, you always have to balance risk versus reward. So on the risk standpoint, the main risks in the fixed-price projects are uncertainty.

if you're looking at an outcome based or fixed price, um,

Leonard Livschitz: Good. Surinder, I will actually have Eugene Steinberg, our CTO, to start talking because he's a bit our architect of the system. Uncertainty has two prongs. One of them is the risk level, the second one is the reward level. I will let Eugene talk about the coexistence of both and how we handle it. Please, Eugene.

Speaker #7: Uncertainty is coming usually from understanding of the requirements and finding gaps in the requirements of the project. We are using very actively our AI agents and our specific gain Rosetta framework to uncover all the uncertainties in the requirements and clarify with our sources.

Eugene Steinberg: Yes. Of course, when you are taking a fixed price project, you always have to balance risk versus reward. On the risk standpoint, the main risks in the fixed price projects are coming from uncertainty. Uncertainty is coming usually from understanding of the requirements and finding gaps in the requirements of the project. We are using very actively our AI agents and our specific GAIN Rosetta framework to uncover all the uncertainties in the requirements and clarify with our sources ahead of time during the presale phase, and that builds us a very strong confidence in the understanding of what needs to be done.

Eugene Steinberg of Co to start talking because she's a bit of an architect of the system. And then certainly has two prongs. One of them is a risk level. The second one is a reward level, and I will let Eugene talk about the coexist on both, and how will you handle it, please? Yes, of course. When you are taking a fixed price project, you always have to balance risk versus reward.

Speaker #7: It's 's ahead of time during the presale phase. And that builds us a very strong confidence in the understanding of what needs to be done.

So on the risk and point the main risks in the next price, projects are coming from uncertainty.

uncertainty is coming, usually from

Speaker #7: During implementation, we are very actively using always AI coding assistance and our, again, gain Rosetta framework. Helping to accelerate the delivery of a project and building the buffer for any unknown unknowns which usually happen.

Understanding of the requirements and finding gaps in the requirements of the project.

Speaker #7: In those projects, so let me just add one thing to what Eugene just said. So Surinder, you know, you've been in the IT industry, and this is a risk not unique to GRID.

Eugene Steinberg: During implementation, we are very actively using always AI coding assistance and our again GAIN Rosetta framework helping to accelerate the delivery of a project and building the buffer for any unknown unknowns, which usually happen in those projects.

We are using very actively, uh, our AI agents, and our specific, uh, Gain Rosetta framework to uncover all the uncertainties, uh, in the requirements and clarify, as our sources is ahead of time during the pre-sale phase, and that builds us, uh, very, uh, strong confidence in their understanding of what needs to be done.

Speaker #7: It's a universal risk. It's a risk. And all I'll add is a couple of additions to what Eugene said. The first thing is that when you scope out projects, if you don't have a deep understanding of the project, or as Eugene says, the risk, it's a problem.

During complementation. We are very actively using always uh, EI coding assistance and uh, our again, again Raza framework.

Anil Doradla: Let me just add one thing to what Eugene just said. Surinder, you know, you've been in the IT industry, and this is a risk not unique to Grid. It's a universal risk.

Uh helping to uh accelerate the delivery of a project and building with buffer for any unknown unknowns, which usually happen in those projects.

Anil Doradla: Let me just add one thing to what Eugene just said. Surinder, you know, you've been in the IT industry, and this is a risk not unique to Grid. It's a universal risk.

Speaker #7: Now, when I look back at the history over the last five years, historically, we were a T&M shop. We moved towards fixed price. And actually, during those first year or two of our fixed price, we learned a lot.

Surinder Thind: Correct. Yeah.

Anil Doradla: All I'll add is a couple of added additions to what Eugene said. The first thing is that when you scope out projects, if you don't have a deep understanding of the project, or as Eugene says, the risk, it's a problem. When I look back at the history over the last 5 years, historically we were a T&M shop. We moved towards fixed price, and actually, during those first year or 2 of our fixed price, we learned a lot. We have committed mistakes in the past, you know, this is a pre-AI era, and we worked. As a matter of fact, there were times when our fixed price project margins were comparable with our T&M, and I always went back to the team, What's going on? We learned.

Speaker #7: We have committed mistakes in the past. This is a free AI era. And we worked. As a matter of fact, there were times when our fixed price project margins were comparable with our T&M.

So let me just add 1 thing to what Eugene just said. So surrender, you know, you've been in the IT industry and this is a risk, not unique to Grid. It's a universal risk. Uh, it's right. Yeah. And I'll all I'll add is a couple of, uh, uh,

Additions to what Eugene said?

Speaker #7: And I always went back to the team, "What's going on?" So we learned. Now, when you look at our fixed price margins, pre-AI, they're higher than our T&M.

Speaker #7: And those learnings are now moving into our AI. So we really know what we're doing. I think what we've learned is that if you don't understand the problem, that you're dealing with, and you don't have the technological know-how, you're absolutely right.

The first thing is that when you Scope our projects, if you don't have a deep understanding of the project, um, or as Eugene says the risk, it's a problem. Now, when I look back at the history Over The Last 5 Years, historically, we were a tnm shop. We moved towards fixed price. And actually, during those first year or 2 of our fixed price? We learned a lot.

Speaker #7: There is a heightened level of risk. We'll always have that risk. But as Leonard pointed out, there's a reward component too with that.

Speaker #1: Yeah. And I just want to close on that with one simple statement. In my prepared remarks, I mentioned clearly that GRID MX is not a system integrator.

Anil Doradla: Now when you look at our fixed price margins pre-AI, they're higher than our T&M, and those learnings are now moving into our AI. We really know what we're doing. I think what we've learned is that if you don't understand the problem that you're dealing with and you don't have the technological know-how, you're absolutely right, there is a heightened level of risk. We'll always have that risk, but as Leonard pointed out, there's a reward component too with that.

Speaker #1: We have product-centric engineering company. And that actually gives us the higher-level confidence than we take on a project. We have a higher probability of success.

Speaker #1: So Eugene was mentioning Rosetta and other methodology we're using. It's all part of the game platforms. Now, the outcomes on a greater scale, Surinder, will be seen as we'll propagate more and more results of this work.

We we have committed mistakes in the past, you know, this is a free AI era and we worked. As a matter of fact, there were times when our fixed price, uh, project margins were comparable with our team, and I always went back to the team. What's going on? So we learned now, when you look at our fixed price, margins, pre AI, they're higher than RTM and those learnings are not moving into our AI. So we really don't know what we're doing. I think what we've learned is that if you don't understand the problem that you're dealing with and you don't have the technological know-how, uh, you're absolutely right.

Leonard Livschitz: I just wanna close on that with the one simple statement. In my prepared remarks, I mentioned clearly that Grid Dynamics is not a system integrator. We're a product-centric engineering company, and that actually gives us the higher level confidence that we take on the projects, we have a high probability of success. Eugene was mentioning Rosetta and other methodology we're using. It's all part of the GAIN platforms. The outcomes on a greater scale, Surinder, will be seen as we will pro-propagate more and more results of this work. It's not about how much money we generate during the project, but how much rate of growth we're gonna see this project going forward.

Speaker #1: So it's not about how much money we generate during the project, but how much rate of growth we're going to see this project going forward.

There is a heightened level of risk. We'll always have that risk but as Leonard pointed out there's a reward component too with that. Yeah and I just want to close and then with the 1 simple statement in my prepared remarks, I mentioned clearly that Greenland mix is not a system integrator, we have product Centric, engineering company.

Speaker #1: Right now, at the size of the we have and the scale of the tasks, we are training not only the models, but our customers how to react on gradual I would say continuation of the development and approaching the goals.

Speaker #1: So it's very, very important. For the fixed bit, for us, to make sure we have intermediary goals because the approximation of the work and delivery results have to be iterative process.

Leonard Livschitz: Right now, at the size of the we have and the scale of the tasks, we are training not only the models, but our customers how to react on gradual, I would say, continuation of the development and approaching the goals. It's very, very important for the fixed bids for us to make sure we have intermediate goals because the approximation of the work and delivery results have to be iterative process, and that's very important. We're improving not only our technology capability, but our project management relationship with the clients as well.

Speaker #1: And that's very important. So we're improving not only our technology capability, but our project management relationship with the clients as well.

Speaker #6: And then maybe just a quick related follow-on. Any color commentary on the delta between kind of the fixed price margins that you're able to achieve currently and what you're achieving on the time and materials side?

Speaker #7: Sure. So when I look at now, it varies quite a bit, right? So I'll throw a number out. And somewhere in the zip code, I have seen the contribution margins.

And that actually gives us the higher level confidence. Then we take on a projects, we have a higher probability of success. So Gina was mentioning rosette and other methodology. We're using, it's all part of the game platforms. Now the outcomes on a greater scale, surrender will be seen as we will propagate more and more results of this work. So it's not about how much money we generate during the project but how much rate of growth? We're going to see this project going forward right now at the size of the we have and the scale of the task. We are training, not only the models, but our customers how to react on gradual, uh, I would say, uh, continuation of the development and approaching the goals. So it's very, very important for the fixed bids for us to make sure we have intermediate goals because the, uh, approximation of the work and delivery results have to be iterative process. And that's where I'm

Speaker #7: When we get to some of our AI work, somewhere in the 60-plus range too. Now, I mean, not every project is a 60%. Otherwise, we would have been a 60% gross margin.

And so we're improving, not only the technology capability, but project management relationship with the clients as well.

Surinder Thind: Then maybe just a quick related follow on. Any color or commentary on the delta between kind of the fixed price margins that you're able to achieve currently and what you're achieving on the time and materials side?

Speaker #7: But this is the contribution margin. And then obviously, you have to offset by some of the overhead. I've seen in general, if you look at most of our AI work, it is higher margins.

Anil Doradla: Sure. Now it varies quite a bit, right? I'll throw a number out and in somewhere in the zip code. I have seen the contribution margins when we get to some of our AI work, somewhere in the 60-plus range too. Now, I mean, not every project is a 60%, otherwise we would have been a 60% gross margin, but this is the contribution margin, and then obviously you have to offset by some of the overhead. I've seen, in general, if you look at most of our AI work, it is higher margins. If you look at the deltas, between our T&M business and non-T&M business, there is a delta.

Speaker #7: If you look at the deltas, between our T&M business and non-T&M business, there is a delta. So we see non-T&M in general being higher.

And then maybe just a quick related follow on any color, commentary on the, on the Delta between kind of the fixed price margins that you're able to achieve currently and what you're achieving on the time of the material side. Sure. So when I look at, now, it varies quite a bit, right? So I'll throw a number out and in somewhere in the zip code, I have seen the contribution margins. When we get to some of our AI work somewhere in the 60 plus range too.

Speaker #7: And then when you look at AI business, portions of the business, we do see some outliers very positive outliers.

Speaker #6: Got it. And then ultimately, what does this mean from a gross margin perspective? There's obviously the near term, that you're able to handle from both managing headcounts, but can you talk about where utilization is relative to your headcount goals and how we should think about the evolution over the next not just next quarter, but the next 12 to 24 months?

Um, I've seen uh, in general, if you look at some most of our AI work, it is higher margins.

Anil Doradla: We see non-T&M in general being higher, and then when you look at AI business, portions of the business, we do see some outliers, very positive outliers.

Um if you look at the Deltas uh between our team and business and uh non tnm business, there is a Delta. So we see non tnm in general being higher. And then when you look at AI business, portions of the business, we do see some outliers very positive outliers.

Surinder Thind: Got it. Ultimately, what does this mean from a gross margin perspective? There's obviously the near term that you're able to handle from managing headcount. Can you talk about where utilization is relative to your headcount goals and how we should think about the evolution over the next, not just next quarter, but the next 12 to 24 months?

Speaker #6: Because it sounds like there's a big opportunity here. And I just want to make sure I understand the through managing headcount and utilization versus the component that's ultimately going to roll out as a result of just the revenue mix itself.

Got it. And then ultimately,

What is this means from a, a close margin perspective, there's obviously the near-term.

Speaker #7: Very good question. So the way I look at Surinder your question is there is what I call the near to intermediate areas of focus, which is part of our 300 bits margin expansion.

Anil Doradla: Sure.

Um, that you're able to handle from both managing headcounts, but can you talk about where utilization is relative to your headcount goals and how we should think about the evolution over the next? Um, not just next quarter but the next 12 to 24 months,

Surinder Thind: It sounds like there's a big opportunity here, and I just wanna make sure I understand.

Speaker #7: Right? Q4 to Q4. And you're already seeing that, right? Then there's a more fundamental question that you're asking is, what is this pricing model and what is the margin model?

Anil Doradla: Oh, yeah.

Surinder Thind: The component that you control through managing headcount and utilization versus the component that's ultimately gonna roll out as a result of just the revenue mix itself.

Because it sounds like there's a big opportunity here, and I just want to make sure I understand the

Surinder Thind: The component that you control through managing headcount and utilization versus the component that's ultimately gonna roll out as a result of just the revenue mix itself.

Speaker #7: So that is a more evolutionary thing that will not happen overnight. That has a more longer term. And that is what we're all working on as we work on these AI platforms.

Anil Doradla: Very good question. The way I look at, Surinder, your question is, there is what I call the near to intermediate areas of focus, which is part.

The the the the components that you control through managing headcount and utilization versus the component that's ultimately going to roll out as a result of just the revenue mix itself.

Speaker #7: The whole game, if as a finance guy, if you really look at what I tell Rahul, from a game platform and Eugene, who's always excited about technology, is what does it do to the margins and what does it do to the stickiness and what does it do to the growth?

Surinder Thind: Yeah

Anil Doradla: Of our 300 basis points margin expansion, right? 244. You're already seeing that, right?

Surinder Thind: Yep.

Anil Doradla: There's a more fundamental question that you're asking is, what is this pricing model and what is the margin model? That is a more evolutionary thing that'll not happen overnight, that has a more longer term, and that is what we are all working on as we work on these AI platforms. The whole GAIN. As a finance guy, if you really look at what I tell Rahul from a GAIN platform, and Eugene, who's always excited about technology, is what does it do to the margins and what does it do to the stickiness and what does it do to the growth? I mean, that's what it really boils down to, right? Our long-term model is to embed GAIN platforms with our customers that is just not human capital, but it's agents and actually IP.

Speaker #7: I mean, that's what it really boils down to, right? And our long-term model is to embed game platforms with our customers that is just not human capital, but it's agents and actually IP create more stickiness, move towards a more fixed price model, and which should result in a higher margin structure.

Very good question. So the way I look at surrendering, your question is there is what I call the near to intermediate areas of focus, which is part of our 300 bits margin expansion, write 2, 404, and you're already seeing that right? Then there's a more fundamental question that you're asking is, what is the pricing model? And what is the margin model?

So, that is a more.

Speaker #7: Now, what does that finally going to end up being? It's work in progress.

Speaker #1: Yeah. So I think Anil gave you a lot of financial guidance. Let me break it down to a couple of key elements, which I gauge the business.

Evolutionary thing that will not happen overnight, that that has a more longer term and that is what we're all working on. As we work on these AI platforms, the whole gain, if, as a finance guy, if you really look at what I tell Rahul, from a game platform and Eugene, who, who's always excited about technology is what does it do to the margins? And what does it do? The stickiness and what does it do to the growth? I mean, that's what it really boils down to write and our long-term model is to

Speaker #1: So there are three elements. Obviously, adoption of AI in terms of the efficiency of the business. The marginality of the business. But there's a third factor, which you guys use quite often, which is not totally irrelevant.

Anil Doradla: Create more stickiness, move towards a more fixed price model, and which should result in a higher margin structure. Now, what is that finally gonna end up being? It's work in progress, you know.

Embed game platforms with our customers. That is just not human capital but its agents and actually IP.

Create more stickiness move towards a more fixed price Model.

Speaker #1: I think it's quite appropriate. It's the revenue per person. So utilization of the past becomes more driven by the revenue per person increase. And there are two parts of that.

And which should result in a higher margin structure. Now, what is that finally going to end up being?

Leonard Livschitz: Yeah. I think Anil gave a lot of financial guidance. Let me break it down to a couple key elements which I gauge the business. There are three elements. Obviously, adoption of AI in terms of the efficiency of the business, the marginality of the business, but there is a third factor which you guys use quite often which is not totally irrelevant. I think it's quite appropriate. It's the revenue per person. Utilization of the past becomes more driven by the revenue per person increase. There are two parts of it. On a overall EBITDA margin and a net margin, this is the internal, the fourth pillar of the platform, how internally we utilize it. That doesn't help with the growth of the business.

It's work in progress, you know? Yeah. So I think uh and you'll give you a lot of financial guidance. Let me break it down to a couple of key elements which I

Speaker #1: On an overall EBITDA margin, on an net margin, this is the internal, the fourth pillar of the platform, how internally we utilize it. But that doesn't help with the growth of the business.

Gauge the business. So there are 3 elements, obviously, adoption of AI in terms of the efficiency of the business.

Speaker #1: What the growth of the business, it comes actually with the idea that we are going to have a repeatable and a kind of reusable IP intelligence of our platforms.

The marginality of the business but there's so factor which you guys use quite often, which is not totally irrelevant. I think it's quite appropriate, it's the revenue per person.

So you utilization of the past.

Speaker #1: So the utilization part comes with the utilization of humans and the IP capital. So it's a new formula, which is really will be gauged, in my opinion, which I'm going to drive the company, is increased revenue per person.

Speaker #1: Now, saying that, there's another factor, right? It's your versus India versus US local consultancy. Different categories of different regions create a different ratio between revenue and the margin.

Leonard Livschitz: With the growth of the business, it comes actually with the idea that we are going to have repeatable and a kind of reusable IP intelligence with our platforms. The utilization part comes with the utilization of humans and the IP capital. It's a new formula which is really will be gauged, in my opinion, which I'm gonna drive the company, is increase revenue per person. Now, saying that, there is another factor, right? It's Europe versus India versus US local consultancy. Different categories of different regions create a different ratio between the revenue and the margin.

Becomes more driven by the revenue per person, increase and there are 2 parts of it, uh, on a overall iida margin and the net margin. This is the, uh, internal the fourth pillar of the platform, how internally? We utilize it, but that doesn't help with the growth of the business.

Speaker #1: And I'm telling my team, it's irrelevant. The revenue per person as a guidance for utilization has to grow everywhere. The new ability to create gain-based platforms forward deployed engineers and the models should drive the efficiency as we already see as an early adoption regardless of the regions and the traditional T&M models which are not going to be as much used as we go forward.

With the growth of the business, it comes actually with idea that we are going to have a repeatable and uh a kind of reusable IP intelligence while platforms. So the utilization part comes with a utilization of humans and uh IP Capital. So it's a new formula which is really will be engaged in my opinion which I'm going to drive. The company is increased Revenue per person now saying that there's another Factor, right? It's your versus uh India versus um um us local consultancy, different categories of different regions, create a different

Surinder Thind: Yeah.

Leonard Livschitz: I'm telling my team it's irrelevant. The revenue per person as a guidance for utilization has to grow everywhere. The new ability to create GAIN-based platforms, forward deployed engineers and the models should drive the efficiency as we already see as an early adoption regardless of the regions and the traditional T&M models, which are not gonna be as much used as we go forward.

Ratio between revenue and the margin.

And I'm telling my team.

Speaker #1: Of course. Pleasure.

It's irrelevant.

Speaker #7: Thank you, Surinder. The next set of questions comes from Brian Bergen of TD Cowen. Go ahead, Brian.

The revenue per person as a guidance for utilization has to grow everywhere.

Speaker #8: Hey, guys. Thanks for taking the question. Good afternoon. Maybe just at a high level, to start on client sentiment, just given the war in Iran, anything you can comment on how the conversation with enterprises has progressed over the last two months here and just more recently as well, anything in recent weeks that's different?

The new ability to create gain-based platforms, forward-deployed engineers, and AI models should drive the efficiency, as we already see in the early adoption, regardless of the regions and the traditional TNM models, which are not going to be as much used as we go forward.

Surinder Thind: Thank you.

Leonard Livschitz: Of course. Pleasure.

Thank you.

Cary Savas: Thank you, Surinder. The next set of questions comes from Bryan Bergin of TD Cowen. Go ahead, Brian.

Speaker #7: You want to talk?

Speaker #6: Yep. I can go there. Thanks for that question, Brian. So there are clear trends, Brian, that we are seeing with our clients. Number one is whereas last year, there was clearly clients who were looking at AI projects as POCs and trying to progress them into projects.

Thank you, sir. Render the next set of questions comes from. Brian Bergin of TD Cowen. Go ahead Brian.

Bryan Bergin: Hey, guys. Thanks for taking the question. Good afternoon.

Anil Doradla: Hey.

Bryan Bergin: Maybe just at a high level to start on client sentiment. Just given the war in Iran, anything you can comment on how the conversation with enterprises has progressed over the last 2 months here and just more recently as well? Anything in recent weeks that's different?

Speaker #6: Clearly, this year, there are production projects being invested in clients. Across the industries. Very consistent. Second trend we are seeing is with AI, it is driving more projects and programs even for application modernization and data platforms.

And I ran—anything you can comment on, on how the conversation with enterprises has progressed over the last few months here, and just more recently as well. Anything in recent weeks that's different?

Leonard Livschitz: Anil.

Anil Doradla: You want to come?

Rahul Bindlish: Yep, I can go there. Thanks for that question, Bryan. There are clear trends, Bryan, that we are seeing with our clients. Number one is whereas last year there was clearly clients who were looking at AI projects as POCs and trying to progress them into projects. Clearly this year, there are production projects being invested in plans across the industries. Very consistent. Second trend we are seeing is with AI, it is driving more projects and programs even for application modernization and data platforms. We are seeing our pipeline grow in those two areas as well. Third, very clearly we are seeing whereas till last year there were the early adopters of AI, now we are seeing a wave of fast followers.

Yep, I can go there. Uh, thanks for that question, Brian. Uh, so there are clear trends, Brian, that we are seeing with our clients.

uh, number 1 is

Speaker #6: So we are seeing our pipeline grow in those two areas as well. And third, very clearly, we are seeing whereas the last year, they were the early adopters of AI, now we are seeing a wave of fast followers.

whereas last year, there was clearly

clients were looking at AI projects as PC's and trying to progress them into projects.

Clearly this year there are production projects being invested in Plants across the industries.

Very consistent.

Speaker #6: That is increasing really our pipelines as well as in some ways our total addressable market.

Speaker #7: But Brian, coming to your point, the Iran war, to me, at least when I look at the business, is a non-event at this stage, right?

Second Trend we are seeing is with AI, it is driving more projects and programs even for application, modernization and data platforms.

So, we are seeing our pipeline grow in those two areas as well.

Speaker #7: With our clients.

Speaker #1: Yeah. I would say I would not really comment right now because the situation is very fluid there. We don't conduct the business in an area of the direct impact.

And third, very clearly, we are saying whereas last year they were the

Rahul Bindlish: That is increasing, really our pipelines as well as, you know, in some ways our total addressable market.

early adopters of AI. Now, we are seeing a wave of fast followers.

Speaker #1: So it's very hard to say that. The secondary impact on the business, again, is negligible, I think, that we had a huge impact continuing to get impact of the Russian invasion to Ukraine, right?

That is increasing, uh, really our pipelines as well as, you know, in some ways, our total addressable market.

Anil Doradla: Bryan, coming to your point, the Iran war to me, at least when I look at the business, is a non-event, at this stage, right? With our clients, right?

Speaker #1: That's much more dear to us. I don't think we're affected as much. But the global world has changed more with the conflict of the Middle East than obviously conflict between Russia and Ukraine.

Leonard Livschitz: Yeah. I, I would say I would not really comment right now because the situation is very fluid there. We don't conduct the business in an area of the direct impact, so it's very hard to say that. The secondary impact on the business, again, is negligible. I think that we had a huge impact continuing to the impact of the Russian invasion to Ukraine, right? That's much more dear to us. I don't think we're affected as much. The global world has changed more with the conflict with Middle East than obviously conflict between Russia and Ukraine. There are various factors. I mean, look, ultimately, the peace and resolution is the benefit for everyone. How the peace is gonna be achieved is very important.

Speaker #1: And there are various factors. I mean, look, ultimately, the peace and resolution is the benefit for everyone. But how the peace is going to be achieved is very important.

Speaker #1: Right now, which is plugging alone, in and out business model and our customer relationship, there is no detriment. There are some positive movements related to their retooling, especially in the manufacturing space because they're obviously more demand for manufacturing of certain type of other products.

Speaker #1: And that's if we talk about our digital twin approach and about our physical AI approach, we're getting gaining momentum. But I would hate to say that it's really driven specifically by the individual event.

But the brand coming to your point. Uh, the Iran War to me at least, when I look at the business is a non-event at this stage right in the third line. Yeah, I I I would say I would not really comment right now because the situation is very fluid. There, we don't conduct the business in an area of the direct impact. So, uh, is there a hard to say that the secondary impact on the business? Um, again is negligible. I think that we had a huge impact continued to get impact of the Russian invasion to Ukraine, right? That that's much more geared to us. I don't think we're affected as much, but the global world has changed more with the conflict with Middle East and obviously conflicts uh, between uh, Russia and Ukraine and there are various factors. I mean, look

Leonard Livschitz: Right now, we just plug in alone in our business model, in our customer relationship, there is no detriment. There are some positive movements related to their retooling, especially in the manufacturing space, because there are obviously more demand for manufacturing certain type of products. That's if we talk about our digital twin approach and about our physical AI approach, gaining momentum. I would hate to say that it's really driven specifically by the individual event. We definitely see the shift of manufacturing to the much higher retooling and scaling the production, and one of them is related to the traditional manufacturing, one of them is related to more semiconductor manufacturing.

Speaker #1: But we definitely see the shift of manufacturing to the much higher retooling and scaling the production. And one of them is related to the traditional manufacturing.

Speaker #1: One of them is related to more semiconductor manufacturing.

Speaker #8: Okay. All right. Appreciate all that detail. But second question here, just as it relates to kind of the AI productivity conversation, just coming out of a lot of the larger traditional SIs, the conversation around productivity, pricing, oppression for them, became more pronounced here in recent weeks.

ultimately the peace and resolution is the benefit for everyone but how the piece is going to be achieved is very important right now. We just plug in the loan in and out business model and our custom relationship. There is no detriment. There's some positive movements related to their retooling, especially in the manufacturing space because they're obviously more demand for manufacturer of certain type of the products. And that's if we talk about our

Speaker #8: And I fully understand you're not competing in many of the places that they are, but just how are the enterprise conversations for you in engagements that are not transitioning under the game framework as far as that type of a dynamic?

Digital twin approach and about our physical AI approach. We're getting gaining momentum. But I would hate to say that it's really driven specifically by the, uh, individual event. But we definitely see the shift of manufacturing to the much higher retooling and scaling the production and 1 of them is related to the traditional manufacturing, 1 of them, is related to more semiconductor Manufacturing.

Bryan Bergin: Okay. I appreciate all that detail. Second question here, just as release of kind of the AI productivity conversation, just coming out of a lot of the larger traditional SIs, you know, the conversation around productivity, pricing oppression for them became more pronounced here in recent weeks. Fully understanding you're not competing in many of the places that they are, but just how are the enterprise conversations for you in engagements that are not transitioning under the GAIN framework as far as that type of a dynamic?

Speaker #1: Okay. So how the conversations are going in the framework, so in this case, very often we still enjoy a significant productivity improvements from AI.

Speaker #1: I can give you some examples. So we just completed a project with one of the wealth management clients of ours. And this is where we deployed AI agents across the QA pipelines in one of the large business units.

Okay, I appreciate all that detail, but second question here just as early as to kind of the AI productivity conversation, just coming out of a lot of the larger traditional SIs, and you know, the conversation around productivity, pricing, and compression for them became more pronounced here in recent weeks. Now, fully understanding you're not competing in many of the places that they are, but just—how are the enterprise conversations for you in engagements that are not transitioning under the GenAI framework, as far as that type of a dynamic?

Eugene Steinberg: Okay. How the conversations are going in the framework. In this case, very often, we still enjoy a significant productivity improvements from AI. I can give you some examples. We just completed a project with one of the wealth management client of ours. This is where we deployed AI agents across their QA pipelines in one of their large business units. There we saw 3 to 6x productivity improvements in the creation of the test coverage. That allowed us to go wide in this customer and increase our stickiness and increase our reach to all business units of these customers going forward. That proved that we can do more with less resources, and this differentiate us across other vendor base of this customer.

Okay.

So, uh, so how are the conversations going? Uh,

In the framework. Uh,

Speaker #1: So there we saw three to six X productivity improvements in the creation of the test coverage. And that allowed us to go wide in this customer.

So in this case, uh, very often, uh, we still enjoy, uh, significant productivity improvements.

From our AI.

Speaker #1: And increase our stickiness and increase our reach to all business units of these customers going forward. So it proved that we can do more with less resources.

I can give you some examples. So we just completed a project with uh 1 of the uh, wealth management client of ours.

And this is where we deployed, uh, AI agents across the QA pipelines in one of the large business units.

Speaker #1: And this differentiates us across other vendor base of this customer.

So there we saw 3 to 6x productivity improvements.

Speaker #7: Yeah. So let me add a couple of statements to what Eugene just said. So the question is really, how is the pricing environment right now?

Uh, in the creation of the test coverage.

And that allowed us to.

Go. Uh,

Speaker #7: Beyond the AI. So AI obviously has its own dynamics and then we'll put that aside. When I look at the business, I look at a couple of very interesting things.

Wide in this customer and increase our stickiness.

Speaker #7: One is that I do not see clients coming and asking that now that same engineer, give me a big discount now. I'm not seeing that.

And increase our reach to all business units of these customers going forward that proved that we can do.

Speaker #7: So now we can argue whether I'm seeing a premium or more premium. That's a slight second question. But we're not seeing any pricing pressures.

Anil Doradla: Yeah. Let me add a couple of statements to what Eugene just said. The question is really how is the pricing environment right now beyond the AI? AI obviously has its own dynamics, and then we'll put that aside. When I look at the business, I look at a couple of very interesting things. One is that I do not see clients coming and asking that now that same engineer give me a big discount now. I'm not seeing that. Now we can argue whether I'm seeing a premium or more premium, that's a slight second question. We're not seeing any pricing pressures. Number 2 is that in our case, you know, tied to Leonard's opening comments, you know, we've seen a lot of vendor consolidation over the last 18 months.

Speaker #7: Number two is that in our case, tied to Leonard's opening comments, we've seen a lot of vendor consolidation over the last 18 months. Now, the very interesting thing about vendor consolidation, it's good news and not so good news.

With less resources entries, uh, and this differentiate us across other vendor base of this customer. Yeah. So let me add a couple of statements, to what Eugene just said. So the question is really, how is the pricing environment right now beyond the AI? So AI obviously has its own Dynamics and then we'll put that aside

uh, when I look at the business,

I look at a couple of very interesting things.

Speaker #7: The good news is that they go from hundreds to dozens. The bad news is that, okay, they say that you're one of the chosen one.

Speaker #7: Give me a little bit of a discount for the next year or so, something like that, right? So we've gone through that. So I would say maybe that would be the closest thing I could come to.

1 is that I do not see clients coming and asking that. Now, that same engineer giving me a big discount. Now I'm not seeing that so now we can argue whether I'm seeing a premium or more premium. That's, that's a slight, a second question, but we're not seeing any any pricing pressures?

Speaker #7: But the team does a very good job when it comes to new customers, new logos. They're very particular. We have a very strong discipline in terms of ensuring that the margins come in.

Number 2 is that in our case.

Leonard Livschitz: The very interesting thing about vendor consolidation, it's good news and not so good news. The good news is that they go from hundreds to dozens. The bad news is that, okay, they say that you're one of the chosen one, give me a little bit of a discount for the next year or so, something like that, right? We've gone through that. I would say maybe that would be the closest thing I could come to. The team does a very good job when it comes to new customers, new logos. They're very particular. We have a very strong discipline in terms of ensuring that the margins come in. It's with our well-established customers, and there we're seeing some of these trends. I don't know, Rahul Bindlish. Go ahead.

Speaker #7: It's with our well-established customers. And there we're seeing some of these trends. I don't know around.

Speaker #1: Yeah. Go ahead. It's important. You have a pretty clear example now.

Speaker #7: Yeah. Yeah. No, I just want to add a couple of points there, Brian. Number one, productivity improvement in the industry is still being shown at individual developer level.

Speaker #7: When you translate that into projects, especially brownfield projects where the majority of our businesses where you are integrating into legacy systems, that productivity at a project level actually falls down to significantly lower numbers, right?

Rahul Bindlish: Okay.

Rahul Bindlish: It's important. You have a pretty clear example now.

Speaker #7: So from that perspective, there is less pressure because you're executing projects and programs and not providing individual engineers. At the same time, when we have examples of consistently showing productivity improvements, we are able to go back to our customers and grab more business.

You know, tied to Leonard's opening comments, you know, we've seen a lot of vendor consolidation over the last 18 months. Now, the very interesting thing about vendor consolidation, it's good news and not so good news. So good news is that they go from hundreds to dozens the bad news. Is that okay? They say that you're 1 of The Chosen 1. Give me a little bit of a discount for the next year or so, something like that, right? So we've gone through that. Um, so I would say maybe that would be the closest thing I could come to, but the team does a very good job. When it comes to new customers new logos, they're very particular. We have a very, uh, strong discipline in ter in terms of ensuring that the margins come in. It's with our well established customers and their we're seeing some of these Trends. I don't know around, you know, go ahead. It's important. You have a

Rahul Bindlish: Yeah. No, I just want to add a couple of points there, Bryan. Number one, productivity improvement in the industry is still being shown at individual developer level. When you translate that into projects, especially brownfield projects, where majority of our business is, where you are integrating into legacy systems, that productivity at a project level actually falls down to significantly lower numbers, right? From that perspective, there is less pressure because you're executing projects and programs and not providing individual engineers. At the same time, when we have examples of consistently showing productivity improvements, we are able to go back to our customers and grab more business. It becomes expansion of a business strategy rather than play on the margin or the rate.

Speaker #7: So it becomes expansion of a business strategy. Rather than play on the margin or the rate.

Speaker #1: I think let me just conclude. It's a good environment. People talk about their side cases and kind of summarize from the global business positioning.

Speaker #1: So what I see and this is quite promising because when I personally meet with the leaders, well, clients, and usually when you go to the top, the conversations on an overall spendings and the priorities and budgets come quite clearly as a critical path, especially when those leaders coming from technology organizations, which depend to show concrete results to their business leaders.

Pretty clear example now. Yeah. Yeah. No. I just want to add a couple of points there. Brand number 1, productivity Improvement in the industry. Still being shown at individuals developer level. When you translate that into projects, especially roanfield projects, where majority of our businesses where you are integrating into Legacy systems, that productivity at a project level actually falls down to significantly lower numbers, right? So from that perspective, there is less pressure because you're executing projects and programs and not providing individual engineers at the same time when we have examples of

Consistently showing productivity improvements. We are able to go back to our customers and

Leonard Livschitz: I think, let me just conclude. You know, it's a good e-environment. People talk about their side cases. I kind of summarize from the global business positioning. What I see, and this is quite promising because when I personally meet with the leaders or clients, and usually when you go to the top, the conversations on the overall spendings and the priorities and budgets come quite clearly as a critical path. Especially when those leaders coming from technology organizations which depend to show concrete results to their business leaders. They are much more focused on productivity in terms of the overall return to the clients. Remember, we talked about this in the past, so you agree with business people on ROI, on a total budget versus outcome, and then you go to the VMO, and VMO breaks it down by the rate per person.

Grab more business. So it becomes expansion of a business strategy, uh, rather than, uh, play on the margin or the rate.

I think let me just conclude it, you know, it's a good it's a good environment. People talk about their side cases and kind of summarize from the global business positioning.

Speaker #1: They are much more focused on productivity in terms of the overall return to the clients. Remember, we talked about this in the past. So you agree with business people on the ROI, on the total budget versus outcome, and then you go to the DMO and we all break it down by the rate per person.

so what I see and this is quite um quite a promising because when I personally meet with the leaders or clients

And usually when you go to the job, the conversations on a overall spendings and the priorities and budgets come quite uh clearly as a critical path.

Speaker #1: When we are getting right now in a budget discussion over all projects, where the budgets are driven by the fixed bid, by the deliverables, and that model that productivity conversation usually goes on a deployment of the measurable results, before somebody starts looking at productivity.

Especially when those leaders coming from technology organizations which depend to show concrete results to their Business Leaders.

Speaker #1: Because what are you going to ask productivity if it's a total budget being agreed between both sides? So this environment is a little bit better.

Speaker #1: But before, when Surinder was talking about, he acknowledged obviously the question of the risk of the model. But that risk is not related directly to productivity anymore at those new adapted businesses.

Leonard Livschitz: When we are getting right now in a budget discussion over all projects, where the budgets are driven by the fixed bids by the deliverables, and that model, that productivity conversation usually goes on a deployment of the measurable results before somebody start looking productivity. What are you gonna ask productivity if it's a total budget being agreed between both sides? This environment little bit better, but before when Surinder was talking about, he acknowledged obviously the question of the risk of the model. That risk is not related directly to productivity anymore at those new adopted businesses.

They are much more focused on productivity in terms of the overall return to the clients. Remember, we talked about this in the past. So, you agree with business people on the ROI on a total budget versus outcome, and then you go to the VMO and we will break it down by the, um, rate per person.

When we are getting right now and the budget discussion overall projects, where the budgets are driven by the fixed bids by the deliverables.

Speaker #8: Very good. Thank you for all that color. I've got one last one for Raul here since he's on the call. Just Raul, beyond the major hyperscalers, as you think ahead, what other types of partner ecosystems are you focused on?

Speaker #9: So I think there are going to be at least three categories. I already spoke about NVIDIA. I do expect that partnership to take off from here.

Speaker #9: The second category would be specialized partners I talked about on the AI consulting area. But I do expect as technology evolves, there are more specialized AI firms that we will start to partner with.

And that model, that productivity conversation, usually goes on a deployment of the measurable results before somebody start looking at productivity, because what are you going to ask productivity if it's a total budget been agreed between both sides. So this environment will be better. But before when, uh, Serena was talking about, he acknowledged, obviously the question of the risk of the model but the risk is not related directly to productivity anymore at those new adapted businesses.

Bryan Bergin: Okay. Very good. Thank you for all that color. I've got one last one for Rahul here since he's on the call. Just, Rahul, beyond the major hyperscalers, as you think ahead, what other types of partner ecosystems are you focused on?

Okay, very good. Thank you for all that color. I've got 1 last 1 for a role here, since he's on the call, just beyond the major hyperscalers. As you think ahead, what other types of partner ecosystems? Are you focused on

Rahul Bindlish: I think there are going to be at least three categories. I already spoke about NVIDIA. I do expect that partnership to take off from here. The second category would be specialized partners. I talked about on the AI consulting area, but I do expect as technology evolves, there are more specialized AI firms that we will start to partner with, potentially even the likes of your LLM providers, right? As their strategies evolve. The third category is what Leonard had talked about. We are starting to see interest from large consulting business consulting companies, who are looking for technology partners to enable capabilities that they want their clients to have, right? That's the third very interesting partnership area that I see us progressing with.

Speaker #9: Potentially even the likes of your LLM providers, right? As they're strategies evolve. And the third category is what Leonard had talked about. We are starting to see interest from large consulting business consulting companies who are looking for technology partners to enable capabilities that they want their clients to have, right?

So, uh, I think that there are going to be at least three categories. Uh, I already spoke about Nvidia. Uh, I do expect that partnership to, uh, take off from here.

Uh, the second category would be, uh, specialized partners I talked about on the AI consulting area.

Speaker #9: And that's a third very interesting partnership area that I see us progressing with.

Speaker #1: And this is immediate. This is what we're doing.

Speaker #7: We're running right now. Yeah.

Speaker #8: Very good. Thanks.

Speaker #1: Thank you, Mark.

Speaker #7: Thank you, Brian.

Speaker #9: Thank you, Brian. The next questions come from my own tandem of Neelam.

Speaker #10: Great. Thank you. I don't know if there's much to ask left to ask, but I'll go ahead anyway. I'll give it a shot.

Speaker #4: Blank, we expect you to be the best question that.

Speaker #10: I'm sorry. I'm running out of questions here, but I guess just a very quickly, just to keep the call on schedule, the question I had was around your visibility.

Leonard Livschitz: This is immediate.

Rahul Bindlish: We're having right now. Yeah.

And the third category is what, uh, Leonard had talked about. Uh, we are starting to see interest from large consulting, business consulting companies who are looking for technology partners to enable capabilities that they want their clients to have, right? And that's a third very interesting, uh, partnership area that I see as progressing with, and this is immediate, this is what we're doing right now. Yeah.

Bryan Bergin: Very good. Thanks.

Leonard Livschitz: Thank you, Bryan.

Anil Doradla: Thank you, Bryan.

Very good, thanks.

Thank you very much. Thank you, Brian.

Cary Savas: Thank you, Brian. The next questions come from Mayank Tandon, Needham.

Speaker #10: I think you talked about that earlier, Anil. In terms of the revenue, how much of the business would you say is sold versus you have to still go out and win?

Thank you, Brian. The next question's come from Mi tandem of needam.

Mayank Tandon: Great. Thank you. I don't know if there's much to ask, left to ask, but I'll go ahead anyway. I'll give it a shot.

Speaker #10: So what is sort of potentially at risk versus what you already have in the bag in terms of your guidance?

Anil Doradla: Mayank, we expect you to be the best question.

Mayank Tandon: I'm sorry. I'm running out of questions here. I guess just, very quickly, just to keep the call, you know, on schedule. The question I had was around your visibility. I think you talked about that earlier, Anil. In terms of the revenue, how much of the business would you say is sold versus you have to still go out and win? What is sort of potentially at risk versus what you already have in the bag in terms of your guidance?

Speaker #4: Yeah. So you recall, Mike, we have had a very traditional model or a well-established model about 85, 10, and 5, right? Where 85% of our revenue in any given year comes from customers who have been with us two years and beyond.

Speaker #4: 10% comes from over the last 12 months, and 5% comes from new. That framework more or less continues to be intact. There might be some variations, especially as we ramp some of these new customers.

Anil Doradla: You recall, Mayank, we have had a very traditional model or a well-established model, about 85, 10, and 5, right? Where 85% of our revenue in any given year comes from customers who have been with us 2 years and beyond. 10% comes from over the last 12 months, and 5% comes from new. That framework more or less continues to be intact. There might be some variations, especially as we ramp some of these new customers. The way I look at it through this lens. When you look at our whole guidance philosophy and when you look at our whole outlook philosophy, what we know well is potentially where we have some of these downside risks, right?

Speaker #4: So the way I look at it through this lens, now, what when you look at our whole guidance philosophy and when you look at our whole outlook philosophy, what we know well is potentially where we have some of these downside risks.

Great, thank you. I don't know if there's much to ask left to ask, but I'll I'll go ahead and you will give it a shot blank. We expect you to be the best question. I'm, I'm sorry, I'm I'm running out of questions here, but I guess just a very quickly, uh, just to keep the call, um, you know, on schedule. Uh, the question I had was around, um, your visibility. I think you talked about that earlier Anil, in terms of, uh, the revenue, how much of the business would you say is sold versus, you have to still go out and win. So, what is sort of potentially at risk versus what you already have in the bag in terms of your guidance? Yeah, so you recall, um, my we have had a very traditional model or a well established model about 8510 and 5, right? Where 85% of our Revenue in any

Speaker #4: Right? I mean, we're dealing with these customers and these are big customers and we have some sense of what we do. So when we give our guidance, for example, at least in the short term, we're taking that into account.

Given here comes from customers who have been with us 2 years and Beyond 10% comes from over the last 12 months and 5% comes from new uh uh that framework more or less continues to be intact. There might be some variations especially as we ramp some of these uh, new customers. So the way I I, I

Speaker #4: When I switch from my short-term guidance to my long-term guidance, I basically switch from a bottoms-up to a top-down a little bit, right? Where I look at the overall pipeline, I look at the forecast, I look at our customer engagements, and come up with this.

Now.

When you look at our whole guidance philosophy, and when you look at our whole outlook of lawsuit,

what what we know? Well,

Is.

Anil Doradla: I mean, we're dealing with these customers, and these are big customers, and we have some sense of what we do. When we give our guidance, for example, at least in the short term, you know, we're taking that into account. When I switch from my short-term guidance to my long-term guidance, I basically switch from a bottoms up to a top down a little bit, right? Where I look at the overall pipeline, I look at the forecast, I look at our customer engagements and come up with this. Now, if you were to ask me whether I have a number that I believe is at risk, I mean, it's a whole probabilistic distribution, right? On how I look at it.

Potentially, where we have some of these downside risks.

Speaker #4: Now, if you were to ask me whether I have a number that I believe is at risk, I mean, it's a whole probabilistic distribution, right?

Speaker #4: On how I look at it. I would say when I look at the business today, versus three months ago, versus four months ago, things are improving.

Right. I mean, we—we're dealing with these customers, and these are big customers, and we have some sense of, uh, what we do. So, when we give our guidance, for example, at least in the short term, you know, we're taking that into account.

Speaker #4: So qualitatively, I would say that things are improving. Now, there's always that risk that we have with any one particular customer due to circumstances or as someone asks a question on the Iran war, there's a macro issue.

Speaker #4: Consumer-sensitive industries are impacted. That's always there. But as we see right now, I mean, we feel good about what where we see the overall business.

Anil Doradla: I would say when I look at the business today versus three months ago versus, you know, four months ago, things are improving. Qualitatively, I would say that things are improving. Now there's always that risk that we have with any one particular customer due to circumstances or, you know, as someone asked a question on the Iran war, there's a macro issue, you know, consumer sensitive industries are impacted. That's always there. As we see right now, I mean, we feel good about where we see the overall business.

When I switched from my short-term guidance, to my uh, long-term guidance. I basically switched from a bottoms up to a top down a little bit right where I look at the overall pipeline. I look at the forecast. I look at our customer engagements and come up with this. Now, if you were to ask me, whether I have a number that I believe is at risk. I mean, it's a whole probabilistic distribution, right on how I look at it.

Speaker #1: Right. So let me just give you, as always, a direct pointer. After listening to Anil, maybe he needs some guidance on his guidance. There are two areas which I think are very important to understand.

I would say, when I look at the business today versus three months ago, versus, you know, four months ago, things are improving. So, qualitatively, I would say that things are improving. Um,

Speaker #1: Number one, the retail business, which traditionally was the most volatile has been de-risked and continues to be de-risking because it's a smaller contribution. It's not little, but it's smaller.

Speaker #1: So that's area where the variance of uncertainty you were talking about. But the second risk is actually growing as we're going to grow the business is how the AI deployments will actually convert into the measurable profits and gain not grid dynamics, gain platform, but the client gain, right?

Leonard Livschitz: Right. Let me just give you, as always, direct pointers, you know, after listening to Anil Doradla's and guidance and his guidance. There are two areas which I think are very important to understand. Number one, the retail business, which traditionally was the most volatile, has been de-risked and continues to be de-risking because it's a smaller contribution. It's not little, but it's smaller. That's area where the variance or uncertainty you are talking about. The second risk is actually growing as we're gonna grow the business, is how the AI deployments will actually convert into the measurable profits and gain, not Grid Dynamics GAIN platform, but the client gain, right? That business is growing very fast. We're very happy that we can actually forecast a better deployment of these projects.

Now, there's always that risk that we have with any 1 particular customer due to circumstances or, you know, as someone asked a question on the Iran War, there's a macro issue, you know, consumer sensitive, uh, Industries are impacted that that's always there. But as we see right now, I mean, we feel good about what where we see the overall business, right? So let me just give you as always,

Direct pointers, you know, after listening to a new—maybe you need some guidance on his guidance. Uh, there are two areas which I think are very important to understand. Number one,

Speaker #1: And that business is growing very fast. So we're very happy that we can actually forecast a better deployment of these projects. But again, when we talk about Fizzbit, we're talking about outcome-based.

Speaker #1: We're talking about criterion which are before was not that clearly exactly. It's how do you measure that ROI? So this criterion becomes a system of criteria which is going more and more about business.

Speaker #1: So I would say that the business we project is very certain that some essentially de-risking with a retail. However, I see as we grow macro, going forward, we need to make sure we bet on the right partners.

The retail business which traditionally was the most volatile. It has been the richest and continues to be the risking because it's a smaller contribution it's it's not little but it's more. So that's area where the variance of uncertainty you are talking about but the second risk is actually growing as we're going to grow the business is how the AI. Deployments will actually convert into the measurable uh, profits and game. Not great Dynamics game platform, but the client gate, right? And uh, that business is growing very fast.

Leonard Livschitz: Again, when we're talking about fixed bids, we're talking about outcome-based, we're talking about criterion which are before was not that clearly executed. It's how you measure that ROI. This criterion becomes a system of criteria, which is growing more and more of our business. I would say that the business we project is very certain. There were some successfully de-risking with retail. However, I see as we grow macro going forward, we need to make sure we bank bet on the right partners. That's where the actually, the ecosystem of the partners also evolves. Remember Bryan's question, who is gonna be the next level partners beside my, you know, micro scale, you know, hyperscalers. Then Rahul mentioned two parts. Of course, GAIN is very clear GAIN.

Speaker #1: And that's where the actually the ecosystem of the partners also evolves. Remember, Brian's question, who is going to be the next-level partners beside MicroScale?

Speaker #1: Hyperscalers and then Rahul mentioned two parts. Of course, consultants are a clear game. But then which of the other elements of the LLMs on the other six substantial guys who will provide us data centers for provide us the material traffic of these deployments, the cost of these models, is going to play a much bigger role.

Speaker #1: So we are in the we are tuned to the system. We're selected to be preferred in many cases. We're confident. But the whole dynamics of AI deployed deliverable value, it's still something we have to prove on the major scale.

Leonard Livschitz: Which of the other elements of the LLMs on the other six substantial guys who will provide us data centers, who provide us the, you know, material traffic of these deployments, the cost of these models, is going to play a much bigger role. We are tuned to the system. We're selected to be preferred in many cases. We're confident, but the whole dynamics of AI deployed deliverable value is still something we have to prove on a major scale for everyone.

Speaker #1: For everyone.

Speaker #10: Got it. And then just to close out, Anil, you mentioned that M&A is still a priority for you. So just wanted to get some context in terms of what you might be looking for.

Speaker #10: And then have private companies maybe sort of recognize that valuations have come down a lot and maybe are more inclined to sell versus resisting a potential sale to a company like GRID.

Speaker #4: Yeah. So as you rightly pointed out, yes, we're very focused. Fingers crossed. We hope to close some deals in the and most of them are tuck-ins.

Right partners. And that's where the actually, uh, the ecosystem of the practice. Also evolves remember, Brian's question, who is going to be the next level Partners beside my, you know, microscale, you know, hyperscalers and then Rahul mentioned, uh, 2 parts. Of course, Conformity is very clear gain, but then which of the other elements of the llms on the, on the other 6 substantial guys who will provide us data centers for provide us the you know the um material traffic of these uh deployments the cost of these models is going to play a much bigger role. So we are in the, we are tuned to the system. We're selected to be preferred. In many cases, we're confident but the whole dynamics of AI deployed deliverable value. It's still something we have to prove on the major scale for everyone.

Mayank Tandon: Got it. Just to close out, Anil, you mentioned that M&A is still a priority for you. Just wanted to get some context in terms of what you might be looking for, and then have private companies maybe sort of recognize that valuations have come down a lot and maybe are more inclined to sell versus resisting a potential sale to a company like Grid.

Speaker #4: What we're looking at right now are tuck-ins from a capability point of view. So obviously, technology has elevated to be very important. Data AI and certain and markets tied to our strategy.

Anil Doradla: Yeah. As you rightly pointed out, yes, we're very focused. Fingers crossed, you know, we hope to, you know, close some deals. Most of them are tuck-ins. What we're looking at right now are tuck-ins from a capability point of view. Obviously, technology has elevated to be very important. Data, AI, and certain end markets tied to our strategy. Now when it comes to the valuation, you will always have to pay a premium for good companies. For good, capable companies, you will always have to pay some level of premium. Overall, you're right, they have come in, and things are looking better from a valuation point of view.

Got it, and then just to close out, I know you mentioned that M&A is still a priority for you. So I just wanted to get some context in terms of what you might be looking for. And then, have private companies maybe sort of recognized that valuations have come down a lot, and are maybe more inclined to sell versus resisting a potential sale to a company like Grid?

Speaker #4: So now when it comes to the valuation, you will always have to pay a premium for good companies. For good, capable companies, you will always have to pay some level of premium.

Yeah, uh, so as you rightly pointed out, uh, yes, we're very focused. Um,

Speaker #4: But overall, you're right. They have come in. And things are looking better from a valuation point of view. But at the end of the day, if someone has some true differentiation, you do have to pay upfront.

Um, fingers crossed, you know, we hope to uh you know, close some deals um in the in the in and most of them are taken what we're looking at right now are uh tuck-ins uh from a capability point of view. So obviously technology has elevated. Uh to be very important data, Ai and certain end markets tied to our strategy.

Speaker #1: Well, the bottom line is accretiveness of these acquisitions have been the vital point. And we're very close to prove that the market we can still come back and do our M&As because, again, you're right, the appetite for them has been a little bit more modest.

uh,

So, now, when it comes to the valuation, uh,

You will always have to pay a premium for good companies.

Speaker #1: But it's not as critical as our broader net, which we threw around the world, related to the two elements, really, two elements. AI-related technologies, especially the cutting-edge technologies, we can benefit more as a congruent business than the particular company on themselves.

For good, capable companies, you will always have to pay some level of premium, but overall you're right. They have come in. Um,

and um,

Anil Doradla: At the end of the day, if someone has some true differentiation, you do have to pay up for it.

Leonard Livschitz: Well, the bottom line is, the accretiveness of these acquisitions have been the vital point, and we're very close to prove to the market we can still come back and do our M&As because, again, you're right. The appetite for them have been a little bit more modest, but that's not as critical as our broader net which we threw around the world related to the two elements, really two elements. AI-related technologies, especially the cutting-edge technologies. We can benefit more as a congruent business than the particular company on themselves. The second part is looking for the partnership outside of the traditional path, which we're enhancing. Stay tuned. We're in good shape there.

Speaker #1: And the second part is looking for the partnership outside of the traditional path, which we're enhancing. So stay tuned. We're in good shape there.

Speaker #10: Great. Thank you, guys. Appreciate it.

Speaker #4: Thank you.

Speaker #1: Thank you. Okay.

Speaker #11: Ladies and gentlemen, this concludes the Q&A portion of our call. I will now turn it over to Leonard for closing.

Things are looking better from from a valuation point of view. But at the end of the day, if someone has some true differentiation, you do have to pay them, right? Well, the bottom line is, uh, creativeness of these Acquisitions have been the vital point, and we're very, very close to prove to the market where you can still come back and do our Manas. Because again, you're right, uh, the appetite, uh, for them to be a little bit more modest but that's not as critical as our broader net, which we threw around the world related to the 2 elements really 2 elements, AI related Technologies, especially The Cutting Edge Technologies, we we can benefit.

Speaker #1: Q1 2026 is through that our AI transformation is working. Our revenue reached 29.3% of total revenue. Gain has matured from a framework to platforms with forward-deployed engineers.

More as a congruent business than the particular company on themselves. And the second part is looking for the partnership outside of the traditional path which were enhancing. So stay tuned, we're in good shape there.

Mayank Tandon: Great. Thank you, guys. Appreciate it.

Leonard Livschitz: Thank you.

Leonard Livschitz: Thank you, Ankit.

Cary Savas: Ladies and gentlemen, this concludes the Q&A portion of our call. I will now turn it over to Leonard for closing state-.

Great. Thank you, guys. Appreciate it. Thank you. Okay.

Speaker #1: Our agentic AI solutions are now in production, across a range of industry verticals, and are generating measurable ROI at commercial scale. The pipeline entering Q2 is the strongest it has ever been.

Ladies and gentlemen, this concludes the Q&A portion of our call, I will now turn it over to Leonard for closing state.

Leonard Livschitz: Q1 2026 is proof that our AI transformation is working. AI revenue reached 29.3% of total revenue. GAIN has matured from a framework to platforms with forward-deployed engineers. Our Agentic AI solutions are now in production across a range of industry verticals and are generating measurable ROI at commercial scale. The pipeline entering Q2 is the strongest it has ever been. AI consulting and hyperscale partnerships are expanding. We're executing on our strategic roadmap, including AI-native delivery, productized GAIN platforms, consulting, and internal automation. We look forward to updating you next quarter. Thank you.

Speaker #1: AI consulting and hyperscale partnerships are expanding. We're executing on our strategic roadmap, including AI-native delivery, productized gain platforms, consulting, and internal automation. We look forward to updating you next quarter.

Q1 2026.

Is proof that our AA transformation is working.

iRevenue reached 29.3% of total revenue. Gain has matured from a framework to platforms with Forward. Deployed engineers—our Agenda Solutions are now in production across a range of industry verticals and are generating measurable ROI at commercial scale.

The pipeline entering Q2 is the strongest it has ever been.

A Consulting at. Hyperscale Partnerships are expending we are executing on our strategic road map, including AI native delivery, productized, game platforms Consulting. And internal automation. We look forward to updating you next quarter. Thank you.

Operator: Goodbye

Goodbye.

Q1 2026 Grid Dynamics Holdings Inc Earnings Call

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