Business Description

Business Overview Grid Dynamics Holdings, Inc. (“Grid Dynamics,” the “Company,” “we,” “us,” or “our”) is an Enterprise Artificial Intelligence (“AI”) transformation partner for the Fortune 1000. We combine deep AI expertise with proven enterprise-scale delivery to help clients identify where to invest in AI, deliver systems that work at scale, and capture real business value from AI deployments. The building blocks of AI have always been our foundation — distributed systems, real-time data, machine learning algorithms, and natural language processing. What has changed is that these capabilities have now converged into Enterprise AI. This technical heritage is matched with business acumen. We solve the most pressing technical challenges and enable positive business outcomes for enterprise companies. A key differentiator is our nearly two decades of technology leadership and pioneering enterprise AI expertise. This is supported by deep capabilities and ongoing investment in data and machine learning platform engineering, cloud platform and product engineering, Internet of Things (“IoT”) and edge computing, and digital engagement services. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India. Industry Background and Grid Dynamics Strategic Differentiators Grid Dynamics serves as the strategic architect and technical expert for Fortune 1000 companies transitioning into AI-driven enterprises. As the industry moves from automating business processes to automating decision-making itself, we provide the specialized engineering required to navigate this shift. Enterprises are increasingly moving away from off-the-shelf software toward custom-engineered solutions that leverage proprietary data, specific business processes, and competitive differentiators. This evolution drives significant demand for partners that can deliver AI implementations that work at enterprise scale and provide a measurable return on investment. Our market position is defined by several key strategic differentiators: • Preference for AI-Native Partners Over Generalist Consultancies Enterprises increasingly seek partners with deep-rooted AI capabilities rather than general-purpose firms attempting to pivot into the space. Grid Dynamics, as an AI-native firm, is built upon a twenty-year track record of engineering the complex systems that now define Enterprise AI. In addition to those investments and training specialized talent, we have gained experience and insights from complex deployments at Fortune 1000 companies. We have developed over 40 pre-built, production-ready solution accelerators across AI, data platforms, and cloud engineering. This accumulated knowledge — ranging from technical architecture patterns to change management — compresses time-to-value that we believe provides us with a competitive advantage. • Restructuring of the IT Services Workforce The traditional IT services pyramid, which relied on large pools of junior developers, is being fundamentally restructured. Modern AI implementations require the inverse: senior engineers and data scientists who can design sophisticated systems and work alongside AI agents to increase productivity. We believe this structural shift provides us with a competitive advantage, as we prioritize experienced senior talent over volume staffing to handle the complexity of production-grade infrastructure. • Engineering Mastery for the Agentic AI Age The emergence of Agentic AI — systems where multiple AI agents collaborate autonomously to complete complex business processes — represents the next enterprise inflection point. Agentic AI systems must coordinate across workflows, maintain state, handle failures, and operate reliably at scale. Organizations attempting to deploy agentic systems without this foundation encounter the same reliability and scalability challenges associated with distributed enterprise software. Grid Dynamics’ strengths in distributed computing, fault-tolerant design, and high-performance enterprise systems directly address these challenges. The engineering disciplines that enable real-time commerce and mission-critical cloud platforms are essential for production-grade agentic AI. • Rigorous Focus on ROI and Business Outcomes 1 Return on investment (“ROI”) has become a primary decision criterion for AI initiatives.…