Tools/HumanSignal/label-studio

Label Studio

Multi-type data labeling and annotation

28.3k ★+41/wkgrowthTypeScriptApache License 2.0 →trending
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The Lens

By Erik Loyd, SaaS CEO and former COO/CFO of an AWS Premier Partner.

Updated Jun 2026

Draw bounding boxes on images, highlight entities in text, transcribe audio, or create custom labeling interfaces with a template system. It's the Swiss Army knife of data labeling.

The community edition is free under Apache 2.0. You get multi-user support, a project system, customizable labeling interfaces, and import/export in every format (COCO, YOLO, spaCy, etc.). Self-host it with Docker and you're labeling data in 10 minutes.

The catch: the free version is single-node only. Label Studio Enterprise (now called HumanSignal) adds team management, active learning, model-assisted labeling, RBAC, SSO, and analytics, but pricing requires a sales call. The community edition handles small-to-medium labeling projects well, but once you have 5+ annotators who need quality control and agreement metrics, you'll feel the feature gap.

Free vs Self-Hosted vs Paid

open core

Community Edition (free): Full labeling interface, multi-format support, ML backend integration, API access. Self-hosted under Apache 2.0.

Enterprise (HumanSignal): Pricing requires a sales call. Based on public information and industry comparisons, expect $200-500/month minimum for team features:

  • Role-based access control
  • Active learning and model-assisted labeling
  • Quality agreement metrics
  • SSO/SAML
  • Priority support

Compared to alternatives:

  • CVAT (free): Strong for computer vision specifically, weaker for text/audio
  • Labelbox: Enterprise-focused, $5K+/year
  • Scale AI: Managed labeling service, pay-per-label ($0.08-2.00/label depending on complexity)
  • Prodigy: $490 one-time license, Python-native, excellent for NLP

The community edition is genuinely capable for teams under 5 annotators.

Community edition free. Enterprise requires a sales call; expect $200-500+/month for team features.

What to do by team size

Solo
Great for labeling your own datasets. Docker Compose setup takes 10 minutes.
Small team
Community edition handles 2-4 annotators well. You'll want quality metrics before scaling.
Medium team
Evaluate Enterprise for RBAC and quality control. The community edition gets painful without team management.
Large team
Enterprise or managed labeling services (Scale AI). At this scale, annotator management and quality control aren't optional.
Self-hosting ops:moderate

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Score
88/100 · A
Adoption27/30
Maintenance25/25
Community11/20
License15/15
Analysis10/10

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High adoption: 27,039 starsActive community: 3,492 forksPermissive license (Apache-2.0)

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