Human Feedback & Post-Training Data
We help clients design and operate the human feedback workflows that support model improvement, from response ranking and correction to practitioner-created demonstrations and evaluation sets.
DataSea provides the human-generated data and evaluation layer — we don't operate model-training infrastructure. The deliverable is ranked, graded, or created data that your team feeds into whatever training pipeline you already run.
What We Produce
Feedback and post-training data created by contributors matched to the difficulty of the judgment involved.
Preference Ranking
Side-by-side comparison of model responses to train and validate reward signals.
Ideal-Answer Creation
Practitioner-written reference responses that reflect what a correct answer actually looks like.
Targeted Correction Data
Fixes to specific failure patterns, built from cases where the model actually went wrong.
SFT Demonstrations
Practitioner-created example conversations and completions for supervised fine-tuning.
Rubric Development
Scoring criteria that make grading consistent across reviewers and batches.
Safety & Quality Review
Domain-specific feedback aimed at reducing harmful or low-quality outputs.
Ready to Improve Your Model?
Tell us what your model gets wrong, and we'll help design the feedback workflow to fix it.