Labelbox

Labelbox is a specialized data platform designed specifically for AI teams building and post-training large language models and other AI systems. The platform excels at three core functions: generating reinforcement learning data with expert-crafted rubrics and tuned environments, building custom evaluation benchmarks to assess model capabilities before public release, and managing robotics training data with multimodal annotations. Rather than being a general data labeling tool, Labelbox positions itself as infrastructure for frontier AI development, partnering with leading AI labs to provide high-value training data including preference pairs, reward signals, and complex reasoning tasks. The platform includes Alignerr, an expert network of 1M+ knowledge workers with advanced credentials (PhDs, licensed professionals) across 40+ countries, enabling access to specialized human intelligence for nuanced annotation tasks that standard crowdsourcing cannot handle.

AI analysis from Feb 23, 2026

• Reinforcement learning data generation with knowledge work rubrics and tuned environments for optimal reward gradients
• Custom evaluation framework with arena-style model comparisons and rubric-based multimodal assessment across text, vision, and reasoning
• Alignerr expert network providing access to credentialed professionals across 40+ countries and 200+ specialized domains
• Robotics data collection with full-stack multimodal annotation (video, trajectories, sensor data) and purpose-built hardware infrastructure
• AI-powered data diversity engine that ensures broad task and environment coverage for robotics and RL applications

• 1Generating preference pair data for RLHF (Reinforcement Learning from Human Feedback) to fine-tune large language models at scale
• 2Building custom evaluation benchmarks to test frontier model capabilities in coding, science, finance, and reasoning before release
• 3Collecting and annotating robotics training data including video trajectories, sensor data, and environmental annotations for embodied AI systems
• 4Creating specialized datasets for domain-specific applications (scientific research, financial modeling, medical imaging) with expert-level annotators
• 5Conducting head-to-head model comparison studies with structured human preference judgments across multimodal inputs

Pricing details not publicly available. Website includes 'Start for free' and 'Contact us' CTAs but does not display plan tiers, feature limits, per-unit costs, or free tier boundaries.

AI research labs, frontier AI companies, and large enterprises building custom LLMs or robotics systems. Best suited for teams with dedicated data infrastructure budgets who need frontier-grade training data, expert annotation, and evaluation benchmarking. Not positioned for small teams, individual researchers with limited budgets, or companies building standard applications.

Write a Review