Label Studio

Label Studio is an open source multi-modal data labeling and AI evaluation platform for annotations and human-in-the-loop workflows.

Label Studio is a multi-modal data labeling and AI evaluation platform for agent traces, LLM evaluations, reinforcement learning from human feedback, computer vision, document AI, natural language processing, and audio transcription. It offers programmable interfaces with custom layouts and templates that adapt to specific data and evaluation criteria. Users can connect observability tools for agentic traces, collect human preferences for fine-tuning, and evaluate retrieval relevance for retrieval-augmented generation. The platform supports image classification, object detection, semantic segmentation, optical character recognition, named entity recognition, audio transcription, and time series event recognition. It integrates into machine learning pipelines using an API, Python SDK, and webhooks to stream predictions and trigger training, active learning, and evaluation workflows.

Label Studio at a glance

Best for: Software engineer, Researcher
Runs on: Web, API, self-hosted, open source
Pricing: Freemium
Released: June 2019
Category: AI coding tool
Website: labelstud.io

Key features

AI evaluation and LLM benchmarking
Computer vision and object tracking
Document and NLP annotation
Audio transcription and speaker diarization
Time series event recognition
Programmable custom layouts and templates
API and Python SDK integration
Human-in-the-loop review workflows

Use it for

Annotating agent traces and LLM evaluations
Collecting human preferences for RLHF
Performing image classification and object detection
Transcribing audio and diarizing speakers
Classifying and segmenting time series data

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