Dataloop
6.0#4 in active learning toolsWebAPILinuxmacOS
VisitDataloop vs Prodigy
What both publish
| Fact | Dataloop | Prodigy |
|---|---|---|
| Deployment | Dataloop says it supports on-premises or private-storage deployments with custom authentication and role-permission enforcement. | The standard Python web server can be deployed on any cloud provider or entirely on-premise. |
| Headquarters | Tel Aviv, Israel | Berlin, Germany |
| Integrations | The developer guide lists cloud storage integrations for Google Cloud Platform, Amazon S3 and Microsoft Azure Blob, plus container registries including AWS ECR, Google Artifact Registry and Azure Container Registry. | Prodigy has first-class support for spaCy, plugins for Hugging Face models, and integrations with major LLM API providers. |
| Support | The contact page lists a support link and gives the address 2 Sapir st, Herzliya, Israel. | The Personal license includes community forum support; Company licenses include priority forum and email support. |
Dataloop plans
- Custom subscriptionPriced on request
Prodigy plans
- Personal$390, paid once
- Company$490, paid once
Pick Dataloop if…
Dataloop suits teams building or labeling image datasets that need multiple annotation styles and export formats. Model-assisted labeling, collaboration, and API access are also listed capabilities.
Pick Prodigy if…
Prodigy suits developers building machine-learning data workflows, especially those who need local or air-gapped operation. Annotation tasks can be completed in the web app without programming, but the tool assumes basic Python and command-line familiarity.