As frontier AI systems take on increasingly complex, real-world tasks, model performance depends more heavily on high-quality training data, rigorous evaluation and realistic environments that reflect how work actually gets done.
EPAM helps AI labs and enterprises improve model capabilities through expert data, model training, evaluations and RL environments grounded in deep engineering and industry expertise. From advancing frontier models to adapting open-weight models for enterprise use cases, we bring the workflows, domain knowledge and technical depth needed to train, test and improve AI for real-world performance.
Our Services
Expert Data & Post-Training
Expert Data & Post-Training
Our expert data and post-training services help improve model performance on complex, domain-specific tasks. We create expert reasoning, SFT, preference and critique data, then use those inputs to support fine-tuning, alignment and model adaptation. Our teams combine domain expertise with rigorous quality controls and evaluation, helping labs and enterprises generate targeted training signals and improve models against clearly defined performance goals.
Evaluations & Red-Teaming
Evaluations & Red-Teaming
Our evaluation and red-teaming services help you measure model and agent performance across capability, safety and domain-specific tasks. We build tailored benchmarks, test complex workflows and run structured adversarial campaigns to uncover failure modes and weaknesses. These evaluations help teams compare models, validate improvements and make better release decisions, while repeatable test suites support ongoing monitoring as systems continue to evolve.
RL Environments
RL Environments
Our reinforcement learning (RL) environments help models and agents learn through realistic, verifiable tasks. We design software, browser, computer-use, API and tool-use environments with task logic, verifiers, reward signals and anti-gaming controls built in. These environments give teams a controlled way to generate training signals, test increasingly complex behaviors and improve model performance on workflows that more closely reflect real-world work.
Sovereign & Open-Weight AI
Sovereign & Open-Weight AI
Our sovereign and open-weight AI services help organizations adapt models while maintaining greater control over data, deployment and governance. We support in-region data creation, multilingual and culturally grounded training, model adaptation and independent evaluation. Our teams work across open-weight ecosystems and sovereign AI programs, with delivery models designed around residency, security and provenance requirements.
Data Quality & Assurance
Data Quality & Assurance
Our data quality and assurance services help you trust the inputs and evidence behind model training and evaluation. We assess provenance, data quality, contamination, rights and grading quality, while also validating verifiers, benchmarks and reproducibility. We support release gates and continuous evaluation so teams can distinguish real model improvement from noisy or misleading signals and maintain confidence as systems evolve.
