Data labeling & annotation · HumanSignal, Inc. (open-source project)
Label Studio
Open-source, self-hosted annotation tool supporting images, text, audio, video and time-series data through a configurable UI.
Label Studio is an open-source annotation tool that a team installs and runs itself: a configurable, XML-based labeling-interface layer sits over a wide range of data types — images, text/NLP, audio, video, time-series and multi-modal combinations — so the same tool can be reconfigured per project rather than needing a different app per data type. It supports importing pre-annotations or model predictions to speed up review, webhook-based integration with ML pipelines, and multi-user projects with role-based access. Because it is self-hosted (or used via HumanSignal's managed cloud offering), there is no per-seat vendor cost for the open-source core, and data never has to leave infrastructure a team controls unless they choose the managed version.
At a glance
| Vendor | HumanSignal, Inc. (open-source project) |
|---|---|
| Pricing model | Open source + paid options |
| Free tier | Yes |
| Deployment | Self-hosted, Cloud |
| Open source | Yes (Apache-2.0) |
| Best for | Teams that want a free, self-hosted, reconfigurable annotation tool across multiple data types. |
Pricing
The open-source core is free and self-hosted; HumanSignal also sells a managed cloud/enterprise version.
Pricing has not been verified yet — see the vendor's site.
Features
- Configurable labeling UI across image, text, audio, video and time-series data
- Pre-annotation and model-prediction import for review-based labeling
- Webhook integration into ML training pipelines
- Multi-user projects with role-based permissions
- Active-learning loop support via ML backend connections
- Self-hosted deployment via Docker
- Managed cloud/enterprise version available from HumanSignal
Integrations
Profile last reviewed September 21, 2026