Label Studio
Product information, use cases, and access for Label Studio.
Pricing information
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What is Label Studio?
Label Studio is an open-source platform for data labeling, AI evaluation, and human-in-the-loop workflows. It supports work with text, documents, images, audio, video, time series, multimodal data, and agent or LLM evaluation tasks, making it relevant to developers, data teams, and AI groups preparing training data or reviewing model behavior.
Users can import data, configure labeling layouts and templates, and review tasks with model predictions assisting the human workflow. The platform also provides an API, Python SDK, and webhooks for creating projects, streaming predictions, and connecting labeling with training, active learning, benchmarking, and continuous model evaluation pipelines.
Key features of Label Studio
Multimodal data labeling
The platform supports labeling images, video, text, documents, audio, time series, and multimodal content, so teams can organize varied training-data and review tasks in one workspace.
Configurable labeling interfaces
Users can configure tags, layouts, and templates around particular datasets and evaluation criteria, creating task-specific interfaces for classification, detection, segmentation, question answering, and other workflows.
AI evaluation and human review
Label Studio can support custom benchmarks and rubrics, side-by-side comparisons, retrieval-relevance checks, grading of generated answers, and human review of agent traces as part of an evaluation workflow.
Machine-learning pipeline integration
Through its API, Python SDK, and webhooks, the platform can create projects, import tasks, receive model predictions, and connect annotation results with training, active-learning, and ongoing evaluation workflows.