A data pipeline that structures proprietary domain information and expert knowledge into training-ready assets for advanced AI models.

Expert-verified reasoning and preference datasets with solutions and structured trajectories for reinforcement learning and post-training.

Sandboxed enterprise simulations with reproducible tasks, delayed consequences, and long-horizon planning for reinforcement learning.

Adaptive benchmarks, adversarial stress tests, reward-hack detection, and human adjudication for model performance and safety evaluation.

Custom, evolving benchmarks and evaluation workflows that provide ongoing performance signal as models improve.