Talk to a researcher about your post-training stack
Connect with the team that builds evaluation data, RL environments, and QA loops used across frontier labs on work that defines post-training maturity.
Together, we’ll work on the challenges slowing your model’s progress:
Gaps in benchmarks and QA coverage
Ambiguity and rubric drift before scale
Proprietary data pipelines for coding, STEM, or multimodality improvements