# Label Studio

- Category: AI platforms
- Official site: https://labelstud.io/
- HTML: https://www.88z.ai/en/tools/label-studio
- Markdown: https://www.88z.ai/en/tools/label-studio.md

Label Studio is an open-source platform developed by HumanSignal, designed for data labeling, AI evaluation, and human-in-the-loop workflows.

## What is Label Studio?

Label Studio is an open-source platform developed by HumanSignal, designed for data labeling, AI evaluation, and human-in-the-loop workflows.It supports a wide range of data types including agent traces, LLM evaluations, RLHF, computer vision, document AI, NLP, and audio transcription.

The platform offers highly customizable interfaces and templates that adapt to complex data structures and evaluation criteria.With native API, Python SDK, and webhooks, users can seamlessly integrate Label Studio into existing ML pipelines to enable real-time prediction streaming, active learning, and continuous model evaluation.

Suitable for both startups and enterprises, Label Studio meets diverse needs through flexible deployment options, including local installation and Docker.Trusted by over 1 million AI practitioners globally, it serves as essential infrastructure for building high-quality training data and evaluating production-grade AI models.

## Key features

- **All-Modal Suppor**：Covers computer vision (image classification, object detection, semantic segmentation), NLP (NER, sentiment analysis), audio (transcription, speaker diarization), and time series data.
- **LLM & Agent Eval**：Supports RLHF, side-by-side comparison, custom benchmarks, and rubrics for evaluating LLM outputs, RAG retrieval relevance, and agent traces.
- **Highly Customiza**：Programmable interfaces and custom label templates allow flexible adaptation to any data format, task type, and specific evaluation criteria.
- **Seamless Integra**：Provides API, Python SDK, and webhooks to sync data from any storage source and connect any model to drive AI-assisted labeling.
- **Enterprise Featu**：Enterprise edition supports native DICOM medical imaging reading, LiDAR point cloud annotation, and camera fusion, preserving full geometric structure and windowing data.
- **Open Source & Co**：Backed by an active GitHub community and Slack channel, offering rich tutorials, templates, and academic program support for quick onboarding.

## How to use it

1. 1.Install Label Studio: Quickly deploy via pip install -U label-studio, Brew, or Docker.
2. 2.Launch Service: Run the label-studio command in the terminal and visit http://localhost:8080/ to access the interface.
3. 3.Create Project: Select the data modality (e.g., image, text, or audio) and configure labeling templates and tag sets.
4. 4.Import Data: Upload datasets from local files or connected cloud storage.
5. 5.Start Labeling: Invite team members for manual labeling or connect models for pre-labeling and active learning.
6. 6.Export Data: Export labeling results as JSON, CSV, or other formats for model training or evaluation.

## Where it fits

- **LLM Fine-tuning**：Collect human preference rankings and corrections for RLHF training; evaluate RAG system answer quality through side-by-side comparison and custom rubrics.
- **Computer Vision**：Perform object detection bounding boxes, polygon segmentation, or keypoint annotation on images, supporting ML model pre-labeling to boost efficiency.
- **Medical Imaging**：Native support for DICOM format allows doctors to annotate professionally without losing windowing settings and slice geometry.
- **Audio Data Proce**：Transcribe call center recordings, perform speaker diarization and emotion recognition, supporting waveform and spectrogram views for higher precision.

## Pricing and free quota

Pricing and any free quota follow the official site.

## Who it is for

- AI Researchers & Data Scientists
- Machine Learning Engineers
- Enterprise teams needing high-quality training data
- LLM Application Developers

## FAQ

### What data types does Label Studio support?

It supports images, text, audio, video, time series, PDF documents, and multi-modal data, with specific optimizations for LLM evaluation and agent traces.

### How do I install Label Studio?

You can install it via Python pip, Homebrew (macOS), or Docker.The official site provides a detailed quick start guide.

### Does it integrate with other ML tools?

Yes, it offers API, Python SDK, and webhooks to easily connect to any data storage and models, supporting active learning workflows.

### What is the difference between Community and Enterprise editions?

The Community edition is open-source and free, suitable for most basic labeling tasks; the Enterprise edition offers advanced features like native DICOM support, LiDAR annotation, SSO, and admin controls.

## Tags

Data Labeling · AI Evaluation · Open Source · Human-in-the-Loop

Features, pricing and availability follow the official site. Except for 88z.ai’s own API pages, this is a third-party product; 88z.ai only provides a directory introduction.