Reinforcement Learning from Human Feedback (RLHF) is a process that uses human feedback to guide AI models toward more helpful, accurate, relevant, and aligned responses. Human evaluators review and compare model outputs, helping the system learn which responses better meet defined quality and behavioural standards.

RLHF Services support the development of AI systems that respond more naturally and consistently to real-world user needs. By combining human preferences with model training and evaluation, RLHF can improve response quality, instruction following, safety, and overall user experience.