#118
B+
Rank #123
Label Studio
A flexible data labeling tool supporting text, image, audio, and video annotation for ML training data, with configurable labeling interfaces. Standout trait is its template-driven UI that adapts to nearly any annotation task without custom code.
68.8
/ 100
⚙ Full Stack
Django (Python) backend with Postgres for project/task metadata and a React frontend for the labeling canvas; supports pluggable cloud/local storage backends for raw media. Official docker-compose stack ships with the project.
📈 Scaling Analysis
Scales reasonably for team-sized annotation workloads with Postgres as a solid transactional backbone, but large media-heavy projects need external object storage rather than local disk to avoid becoming I/O-bound. RBAC and multi-tenant isolation are more mature in the paid enterprise tier than OSS.
🚀 Running on Nexlayer
Two-pod deploy — app and Postgres (`postgres.pod:5432`) — with object storage for media either mounted as a persistent volume or pointed at an external bucket. Set `LABEL_STUDIO_HOST` to the Nexlayer `<% URL %>` value so exported task/annotation links resolve correctly.