Overview
Labelbox is a training data platform that helps ML teams create, manage, and improve training datasets. The platform provides tools for data labeling, quality control, model-assisted labeling, and data management. Labelbox is used by companies like Adobe, Genentech, and Walmart for their ML operations.
Unlike Scale AI which provides labeling as a service, Labelbox is primarily a software platform that ML teams use to manage their own labeling workflows, whether done internally or with external labelers. This gives teams more control over their data pipelines.
Key Features
**Data Labeling**: Tools for annotating all data types**Model-Assisted Labeling**: AI helps speed up annotation**Quality Management**: Ensure labeling accuracy**Data Management**: Organize and version datasets**Team Collaboration**: Multi-user workflows**Automation**: Automate repetitive tasks**Integrations**: Connect to ML pipelines**Analytics**: Track labeling performanceWhen to Use Labelbox
Labelbox is ideal for:
ML teams managing their own labelingComputer vision projectsOrganizations wanting labeling software not servicesTeams needing fine-grained control over dataCompanies with internal labeling teamsIterative ML development workflowsPros
Good software platformModel-assisted labeling speeds workMore control than using labeling servicesFree tier availableGood for iterative ML developmentStrong integrationsTeam collaboration featuresActive developmentCons
Still requires human labelersCan be expensive at scaleLearning curve for full platformLess turnkey than labeling servicesRequires managing labeling workforceFree tier is limitedEnterprise features require upgradeMay be complex for simple needsPricing
**Free**: Limited projects and users**Starter**: $39/user/month**Professional**: Custom pricing**Enterprise**: Custom pricing