Preference data at training speed.
Collect RLHF preference pairs, human feedback, and judgment signals across demographics and cultures - via API, straight into your training loop.
Teach the model
what good looks like.
Humans rank, choose, and demonstrate - turned into alignment data.
Recruit preference raters
Verified people whose judgment matches your users.
Rank & choose
Pairwise preferences and rankings across your prompts.
RLHF-ready data
Clean preference and demonstration sets, ready to train.
A loop that compounds.
Real human judgment, on a loop.
Improve your models with feedback from real, verified participants.
Recruit, gather human judgment, train, and evaluate - then run it again.
Built for high-quality AI data.
Verified human expertise, quality controls, and the full pipeline - from evaluation to fine-tuning.
Verified human expertise
Domain experts and everyday users - identity-verified across 150+ countries and 100+ languages.
Quality controls built in
Attention checks, inter-rater agreement, and fraud prevention keep every dataset clean.
The full pipeline
Evaluation, preference data, annotation, and fine-tuning - delivered into your stack via API.
One panel for every data need.
Evaluation, alignment, and fine-tuning data - from the same verified human network.
A global network of verified experts.
Wherever your model ships, recruit the real people who can judge it - by domain, language, and culture.
150+ countries
Recruit experts and everyday users wherever your model is used - real local judgment, not a US-only sample.
100+ languages
Multilingual and cross-cultural data from real native speakers - for models that work everywhere.
Verified & fraud-free
Identity-checked participants, sourced directly - never scraped, borrowed, or synthetic.
