The shift toward complex, agentic execution has exposed a significant bottleneck in current AI adoption: the lack of vetted, enterprise-grade domain knowledge. EPAM’s new offering seeks to resolve this by integrating its long-standing engineering expertise with established partnerships at major AI labs including Anthropic, OpenAI, Google, and Microsoft. The service provides a foundational layer for companies to stress-test multi-turn interactions and reasoning within controlled virtual simulations before deployment.
Elaina Shekhter, Chief Strategy and Transformation Officer at EPAM, emphasized that the market demand has moved from raw compute power to specialized intelligence. To support this, the firm has cultivated a massive workforce of certified talent, including nearly 10,000 Claude-certified architects and thousands of specialists trained in OpenAI and Gemini ecosystems. These teams work directly with labs to ensure models are equipped for the rigors of production environments.
This infrastructure is anchored by the development of reinforcement learning environments that simulate complex enterprise systems. According to an April 2026 Gartner report, the use of such simulation environments is expected to grow rapidly, with 99% of agent platform providers projected to adopt the technology by 2028. By providing this closed-loop feedback, EPAM intends to help enterprises transition from experimental pilots to measurable, autonomous business outcomes.

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