Human feedback pipelines that align and red-team models.
Overview
What is RLHF & AI training?
RLHF is the core technique behind today's most capable models. It runs on diverse, calibrated preference data from expert raters who can rank, refine and evaluate model outputs.
Models trained purely on text learn to predict tokens, not to be helpful or safe. RLHF puts human judgment into training, so models reflect real values, preferences and safety requirements.
Side-by-side response comparison across nuanced quality dimensions.
Adversarial testing that surfaces safety and alignment failures.
Supervised fine-tuning examples across diverse task domains.
RLHF data in 40+ languages for cross-lingual alignment.
Workflow
How we do it
- 01Rater recruitment
We recruit and train expert raters with domain knowledge matched to your use case.
- 02Task design
Custom prompt sets, comparison pairs and rubrics aligned to your targets.
- 03Preference collection
Structured ranking, direct scoring and conversational feedback across demographics.
- 04Calibration QA
Regular calibration sessions and inter-rater reliability monitoring.
- 05Dataset delivery
RLHF-ready preference pairs and SFT examples in HuggingFace or custom formats.
Case study
Reduce hallucination rate in a production LLM by 34%
2M+ RLHF preference pairs from calibrated expert raters, with multi-turn evaluation.
Ready to get startedwith RLHF & AI training?
Tell us about your project and we will scope a pilot within 48 hours.