Encord RLHF is a platform designed to streamline and scale Reinforcement Learning from Human Feedback (RLHF) workflows for AI developers and researchers. Built by Encord, a company focused on data-centric AI solutions, this tool enables teams to train, evaluate, and fine-tune large language models (LLMs) and vision systems by combining automated learning with structured human input.

The platform is aimed at ML teams in enterprises and research labs seeking to implement human-aligned AI, where human feedback is essential to optimizing performance, safety, and alignment. Encord RLHF simplifies the data operations and feedback loop critical to these training pipelines.

Key benefits:

• Full-stack RLHF workflow, from data labeling to reward model training

• Model-agnostic platform, compatible with popular LLM and vision models

• Structured feedback tools, enabling fine-grained preference collection at scale

What are the main features of Encord RLHF?

End-to-end RLHF pipeline support

The platform manages the entire RLHF process, reducing the complexity of orchestration and tooling.

• Dataset creation, annotation, and curation

• Feedback collection interfaces for ranking, comparison, and scoring

• Reward model training and fine-tuning integration

• Suitable for both language and vision applications

Human feedback collection at scale

Encord RLHF enables structured feedback workflows, allowing users to gather high-quality human preferences efficiently.

• UI components for comparison, accept/reject, and ranking tasks

• Task assignment and quality control for labelers

• Audit trails and feedback analytics

Model-agnostic infrastructure

The platform supports integration with a variety of foundation models and fine-tuning frameworks.

• Works with Hugging Face models, OpenAI APIs, and open-source vision models

• Supports LoRA, PEFT, and other parameter-efficient fine-tuning methods

• Can be used in conjunction with custom model pipelines

Reward model and alignment tools

Encord provides tools to train and manage reward models based on collected human feedback.

• Preference modeling and reward signal generation

• Model evaluation tools for alignment, bias, and safety metrics

• Iterative tuning workflows to improve alignment over time

Collaborative and audit-ready

Built for teams, Encord RLHF offers collaboration features and data governance tools.

• Role-based access control and task tracking

• Versioning, reproducibility, and quality review workflows

• Compliance and audit logs for high-stakes applications

Why choose Encord RLHF?

• All-in-one solution for RLHF, covering data, feedback, training, and alignment

• Designed for scalability, enabling large teams to gather and manage human input efficiently

• Supports both vision and language models, including LLMs and foundation vision models

• Model-agnostic and flexible, integrates with modern fine-tuning and evaluation frameworks

• Ideal for responsible AI development, with tools for safety, fairness, and transparency