Developer Tools

Label Studio

Open source platform for labeling data to train, fine-tune, and evaluate AI models across text, images, audio, and video.

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labelstud.io

Verified API available ~4.6k monthly visits

Quick facts
What is it	Open source platform for labeling data to train, fine-tune, and evaluate AI models across text, images, audio, and video.
Pricing	Unknown
Platform	Web Application
API	Yes
Best for	preparing training data for computer vision models, fine-tuning and evaluating large language models (LLMs)
Domain registered	2019

Data updated Aug. 1, 2026

What does Label Studio do?

Label Studio is an open-source data labeling platform that serves as the foundational tool for preparing datasets used to train and evaluate artificial intelligence models. It provides a unified interface for annotating diverse data types including text, images, audio, video, and time-series data. You can classify documents, detect objects in images, transcribe audio, label entities in text, and track objects in video frames, all within a customizable workflow that adapts to your specific project requirements.

The platform stands out through its extreme flexibility and strong integration capabilities. Instead of forcing a one-size-fits-all approach, Label Studio lets you configure labeling interfaces precisely for your use case. Its ML-assisted labeling feature saves significant time by using model predictions to pre-label data, which annotators can then refine. With a comprehensive Python SDK, REST API, and webhook support, Label Studio seamlessly integrates into existing ML pipelines, allowing automated data import, project management, and prediction handling.

Label Studio is particularly valuable for machine learning teams working on complex AI projects that require high-quality, accurately labeled training data. Real-world applications include fine-tuning LLMs through supervised fine-tuning and RLHF, evaluating RAG (Retrieval-Augmented Generation) systems, developing computer vision models for object detection, and processing multimedia content like call center recordings. Its open-source nature and enterprise-friendly features make it suitable for both research institutions and production AI teams at companies like NVIDIA, Meta, and IBM.

Developer Tools No-Code&Low-Code

#ai training data#data annotation#data labeling#machine learning#ml-ops#open source

Key features

What makes it stand out

Flexible, configurable layouts and templates for any data type

ML-assisted labeling to speed up annotation using model predictions

Python SDK and API for seamless integration into ML pipelines

Connect to cloud storage (S3, GCP) to label data directly

Data Manager with advanced filters to explore and manage datasets

Who is Label Studio for?

Who benefits most from this tool

preparing training data for computer vision models

fine-tuning and evaluating large language models (LLMs)

annotating audio transcripts and time-series sensor data

Trust & presence

Search presence Top 100k site

Domain Domain registered 2019

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