EPAM launches Frontier AI service for enterprise-grade model training
EPAM Systems has launched a service aimed at helping frontier AI models run complex enterprise workflows more reliably. According to the company, it covers high-fidelity data generation, model evaluation and custom reinforcement learning environments.
- EPAM Systems launched a Frontier AI service offering high-fidelity data generation, model evaluation and custom RL environments.
- RL environments simulate enterprise systems so developers can stress-test multi-turn interactions, reasoning and tool use before production.
- EPAM says it has nearly 10,000 Claude-certified architects, 3,000+ OpenAI-certified FDEs and 5,000+ Gemini-certified specialists.
- Gartner's April 2026 report says 99% of agent platform providers will offer simulation environments by 2028, up from less than 25% in 2026.
What EPAM is offering
EPAM Systems, Inc. (NYSE: EPAM) announced the launch of a strategic offering dedicated to supporting the next generation of frontier AI models. The company describes it as a foundational intelligence layer for the AI ecosystem, built to address an industry bottleneck: getting frontier models to execute specialized enterprise workflows with greater reliability.
EPAM argues that early generative AI models were trained on broad, publicly available data to master general language and coding. As adoption accelerates, it says, attention has moved to complex enterprise workflows, multi-step agentic execution and specialized vertical reasoning that depend on vetted domain knowledge.
To meet that need, EPAM says it will offer specialized competencies in three areas:
- High-fidelity data generation
- Rigorous model evaluation
- The creation of custom reinforcement learning (RL) environments
RL environments as the cornerstone
The company calls the development of RL environments that support scenario simulation a cornerstone of the service. These are controlled virtual environments that mirror complex enterprise systems and workflows. According to EPAM, they let developers stress-test multi-turn interactions, reasoning and tool use before production, while providing secure, closed-loop feedback for reinforcement learning and ongoing model improvement.
EPAM cites a Gartner report from April 2026, titled Emerging Tech: AI Race: Simulation Supercharges Agent Evaluation and Self-Learning Loops for AI Agents. According to that report, by 2028, 99% of agent platform providers will offer simulation environments, up from less than 25% in 2026.
Lab partnerships and certified staff
EPAM says the offering rests on its established partnerships with leading frontier AI labs, including Anthropic, OpenAI, Google and Microsoft. The company describes one of the largest AI engineering initiatives in the industry and says it has trained and invested in nearly 10,000 Claude-certified architects, 3,000+ OpenAI-certified forward-deployed engineers (FDEs), and 5,000+ Gemini-certified specialists to date.
In EPAM's view, this certified proficiency across major model ecosystems, together with firsthand insight into where models succeed and struggle in enterprise deployments, gives labs the collaboration they need to accelerate model development and move enterprises from pilot to measurable business outcomes.
Company view and what it means
Elaina Shekhter, Chief Strategy & Transformation Officer at EPAM, said that "the demand has fundamentally moved from raw compute to specialized domain intelligence." She added that the new offering pairs the company's engineering heritage with its Frontier AI partnerships, positioning it to capture what she called a "massive, high-value market."
For AI labs, the pitch is access to enterprise-grounded data, evaluation and simulation capacity from a services firm that works inside large client systems. For enterprises, the stated goal is more dependable autonomous agents in real workflows. The release gives no pricing, customer names or availability details, and further information is directed to www.epam.com/frontier-ai.
