NEWTOWN, PA — EPAM Systems Inc. (NYSE: EPAM) is expanding into specialized training data and evaluation services for developers of advanced artificial intelligence models, seeking to capitalize on growing demand for systems capable of executing complex business operations.
The Pennsylvania-based technology services company has introduced an offering focused on generating enterprise-specific training data, evaluating model performance and building simulated environments for reinforcement learning.
The move extends EPAM’s business beyond enterprise AI implementation into services supporting the development and refinement of frontier AI models.
EPAM is targeting a shift in AI development toward specialized reasoning and multistep workflows, where models must interact with business software, execute tasks and produce reliable results across interconnected systems.
The company said its experience designing and maintaining enterprise technology infrastructure provides a basis for creating training scenarios that reflect actual business operations.
A central component of the offering involves reinforcement learning environments that simulate enterprise systems and workflows.
These controlled environments allow AI developers to test how models handle multistep instructions, reasoning tasks and software tools before deploying them in production.
The simulations also generate feedback that can be used to improve model performance through additional training.
EPAM will provide specialized data generation and model evaluation services intended to identify weaknesses in AI systems operating within complex enterprise environments.
The initiative builds on the company’s existing relationships with AI developers, including Anthropic, OpenAI, Google and Microsoft.
EPAM reported investments in training nearly 10,000 Claude-certified architects, more than 3,000 OpenAI-certified forward-deployed engineers and more than 5,000 Gemini-certified specialists.
Those figures reflect the company’s efforts to develop technical expertise across competing AI platforms as enterprise customers adopt systems from multiple providers.
Elaina Shekhter, EPAM’s chief strategy and transformation officer, said demand is shifting toward specialized expertise needed to make AI systems reliable in business applications.
“As frontier AI shifts from general experimentation to complex enterprise workflows, the demand has fundamentally moved from raw compute to specialized domain intelligence,” Shekhter said.
The expansion positions EPAM to serve AI model developers as well as corporate customers implementing AI technology, potentially broadening its role in the market for enterprise AI infrastructure and services.
The company cited an April 2026 Gartner report projecting that 99% of AI agent platform providers will offer simulation environments by 2028, compared with fewer than 25% in 2026.
That forecast suggests simulation and evaluation capabilities could become standard components of AI development platforms as businesses move toward greater automation.
For EPAM, the initiative represents an effort to commercialize its enterprise engineering expertise at an earlier stage of the AI development process, where model developers require specialized data and testing infrastructure.
The company did not provide financial projections for the new offering or identify specific revenue targets.
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