EPAM Unveils New Frontier AI Service, Bridging the Enterprise Intelligence Gap for GenAI and Autonomous Agents
EPAM Systems (EPAM) launched a frontier AI service offering focused on training and evaluating models for complex enterprise workflows.
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Rhea-AI Summary
EPAM Systems (EPAM) launched a frontier AI service offering focused on training and evaluating models for complex enterprise workflows. The offering covers specialized data generation, model evaluation and reinforcement learning environments, where models learn from feedback in simulated settings.
These environments mirror enterprise systems so developers can test multi-step interactions, reasoning and tool use before production. EPAM's established AI lab partnerships include Anthropic, OpenAI, Google and Microsoft. Its training investments include nearly 10,000 Claude-certified architects, 3,000+ OpenAI-certified forward-deployed engineers and 5,000+ Gemini-certified specialists to date.
Key Figures
- Claude-certified architects
- nearly 10,000
- EPAM's current stated workforce scale
- OpenAI-certified forward-deployed engineers
- 3,000+
- EPAM's current stated workforce scale
- Gemini-certified specialists
- 5,000+
- EPAM's current stated workforce scale
Previous AI Reports
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Partnership set a 10,000+ Claude architect target, with 1,300 certified at the time.
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Key Terms
reinforcement learning (rl) technical
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New offering leverages EPAM's decades of enterprise engineering depth and established AI lab partnerships to supply advanced data and evaluation services
While early generative AI models were trained on broad, publicly available data to master general language and coding, the industry has entered a new era. As adoption accelerates, the focus has shifted toward complex enterprise workflows, multi-step agentic execution and specialized vertical reasoning that require vetted domain knowledge. By leveraging its deep, multi-decade experience in designing, integrating and maintaining complex enterprise workflows, EPAM will offer specialized competencies in high-fidelity data generation, rigorous model evaluation and the creation of custom reinforcement learning (RL) environments.
"As frontier AI shifts from general experimentation to complex enterprise workflows, the demand has fundamentally moved from raw compute to specialized domain intelligence," said Elaina Shekhter, Chief Strategy & Transformation Officer at EPAM. "Our new offering bridges that critical gap by pairing our decades of deep engineering heritage with our established Frontier AI partnerships, uniquely positioning us to capture this massive, high-value market. We aren't just participating in the GenAI wave, we're actively building infrastructure that makes enterprise-grade autonomy possible."
These capabilities are further anchored by EPAM's established partnerships with the leading frontier AI labs, including Anthropic, OpenAI, Google and Microsoft. With one of the largest AI engineering initiatives in the industry, EPAM 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. This certified proficiency across major model ecosystems, combined with firsthand insight into where models succeed and struggle in enterprise deployments, provides labs with the trusted, high-caliber collaboration required to accelerate model development and drive enterprises from pilot to measurable business outcomes.
A cornerstone of the service is the development of RL environments that support scenario simulation. These sophisticated, controlled virtual environments mirror complex enterprise systems and workflows, enabling developers to rigorously stress-test multi-turn interactions, reasoning and tool use before production while providing secure, closed-loop feedback for reinforcement learning and ongoing model improvement. According to research from Gartner® in its April 2026 report, titled Emerging Tech: AI Race: Simulation Supercharges Agent Evaluation and Self-Learning Loops for AI Agents, by 2028,
To learn more about EPAM's latest AI capabilities and enterprise engineering services, visit: www.epam.com/frontier-ai
Source: Gartner Report, Emerging Tech: AI Race: Simulation Supercharges Agent Evaluation and Self-Learning Loops for AI Agents, By Radu Miclaus, Danielle Casey, etc., April 2026. Gartner is a trademark of Gartner, Inc. and/or its affiliates
About EPAM Systems
EPAM (NYSE: EPAM) is a global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. With over thirty years of expertise in custom software, product and platform engineering, EPAM empowers organizations to become AI-Native enterprises, driving measurable value from innovation and digital investments. Recognized by industry benchmarks and leading analysts as a leader in AI, EPAM delivers globally while engaging locally, making the future real for clients, partners, and employees.
We are proud to be recognized by Forbes, Glassdoor, Newsweek, Time Magazine, Great Place to Work and kununu as a Most Loved Workplace around the world.
Learn more at www.epam.com and follow us on LinkedIn.
Forward-Looking Statements
This press release includes estimates and statements which may constitute forward-looking statements made pursuant to the safe harbor provisions of the Private Securities Litigation Reform Act of 1995, the accuracy of which are necessarily subject to risks, uncertainties, and assumptions as to future events that may not prove to be accurate. Our estimates and forward-looking statements are mainly based on our current expectations and estimates of future events and trends, which affect or may affect our business and operations. These statements may include words such as "may," "will," "should," "believe," "expect," "anticipate," "intend," "plan," "estimate" or similar expressions. Those future events and trends may relate to, among other things, developments relating to the war in Ukraine and escalation of the war in the surrounding region, political and civil unrest or military action in the geographies where we conduct business and operate, difficult conditions in global capital markets, foreign exchange markets, global trade, and the broader economy, the adoption and implementation of artificial intelligence technologies by EPAM and its clients, and the effect that these events may have on client demand and our revenues, operations, access to capital, and profitability. Other factors that could cause actual results to differ materially from those expressed or implied include general economic conditions, the risk factors discussed in the Company's most recent Annual Report on Form 10-K and the factors discussed in the Company's Quarterly Reports on Form 10-Q, particularly under the headings "Management's Discussion and Analysis of Financial Condition and Results of Operations" and "Risk Factors" and other filings with the Securities and Exchange Commission. Although we believe that these estimates and forward-looking statements are based upon reasonable assumptions, they are subject to several risks and uncertainties and are made based on information currently available to us. EPAM undertakes no obligation to update or revise any forward-looking statements, whether as a result of new information, future events, or otherwise, except as may be required under applicable securities law.
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SOURCE EPAM Systems, Inc.