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Labelbox delivers a comprehensive AI data factory solution combining managed services and industry-leading software for generating high-quality training data and evaluating models. The platform serves AI teams building frontier models and enterprise applications by providing expert labeling services through the exclusive Alignerr network and powerful tools for data annotation, curation, and quality control.
The company's applied research team pioneers advanced methods including reinforcement learning with verifiable rewards, which provides clean automatic reward signals for tasks like math and code where correctness can be programmatically verified. Rubric-based evaluations enable fine-grained feedback on subjective tasks by scoring outputs against human-defined criteria, while solvers and verifiers deliver automated checks for complex multi-step outputs.
Labelbox supports diverse AI applications across robotics, complex reasoning, multimodal reasoning, audio processing, coding tasks, multilingual systems, and autonomous agents. The platform enables teams to create custom data labeling workflows, leverage model-assisted labeling, and conduct multimodal evaluations with live chat editors. AI critics and auto-labeling tools accelerate data generation while maintaining high quality standards backed by quality guarantees.
The software includes natural language search for data curation, customizable workflows, collaboration tools for annotators and reviewers, and integrated analytics for tracking progress and ensuring consistency. Enterprise features include multiple workspaces, SSO authentication, custom embeddings, HIPAA compliance, and dedicated technical support. Labelbox also publishes leaderboards that reveal performance insights of leading AI models across topics like complex reasoning, agentic search, and multimodal reasoning, bringing precision to evaluating subjective AI capabilities.
- Generate training data for frontier AI models using expert human labelers and AI-assisted tools
- Evaluate large language models with rubric-based assessments and human expert feedback
- Create labeled datasets for computer vision applications including image and video annotation
- Develop training data for natural language processing models with text annotation workflows
- Build reinforcement learning systems using verifiable rewards for math, code, and task completion
- Conduct multimodal model evaluations combining text, image, audio, and video inputs
- Train autonomous agents with agentic trajectory data and complex reasoning examples
- Label audio data for speech recognition, text-to-speech, and voice assistant applications
- Accelerate coding model development with verified code generation and completion datasets
- Create multilingual training data with expert annotators for global AI applications
- Benchmark model performance using standardized leaderboards and expert evaluations
- Manage end-to-end data labeling operations with quality control and team collaboration tools
