Aligning AI with human values
RLHF & AI Training
Reinforcement learning from human feedback pipelines to align, improve, and red-team foundation models and LLMs.
Overview
What is RLHF & AI Training?
RLHF is the core technique behind today's most capable AI models. It requires diverse, calibrated human preference data — expert raters who can rank, refine, and evaluate model outputs across complex tasks.
Why it matters: Models trained purely on text learn to predict tokens, not to be helpful or safe. RLHF injects human judgment into training — making models that reflect real human values, preferences, and safety requirements.
Preference Ranking
Side-by-side response comparison with nuanced quality dimensions
Red Teaming
Adversarial testing to identify safety and alignment failures
SFT Data
Supervised fine-tuning examples across diverse task domains
Multilingual
RLHF data in 30+ languages for cross-lingual alignment
Workflow
How We Do It
01
Rater Recruitment
Recruit and train expert raters with domain knowledge matched to your model's use case.
02
Task Design
Custom prompt sets, comparison pairs, and evaluation rubrics aligned to your alignment targets.
03
Preference Collection
Structured ranking, direct scoring, and conversational feedback across diverse demographics.
04
Calibration QA
Regular rater calibration sessions and inter-rater reliability monitoring.
05
Dataset Delivery
RLHF-ready preference pairs and SFT examples in HuggingFace or custom formats.
Case Study
LLM Platform
LLM Platform
Reduce hallucination rate in production LLM by 34%
Solution
2M+ RLHF preference pairs with calibrated expert raters and multi-turn evaluation
Results
2M+
Preference pairs
-34%
Hallucination rate
12 wks
Pipeline runtime
Ready to Get Started with RLHF & AI Training?
Tell us about your project and we'll scope a pilot within 48 hours.