Dataloop
6.0#4 in active learning toolsWebAPILinuxmacOS
VisitDataloop vs Encord
What both publish
| Fact | Dataloop | Encord |
|---|---|---|
| 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. | Cloud storage integrations named on the site include AWS S3, Azure Data Lake Storage, and Google Cloud Storage; users can access projects, datasets, and annotations through API/SDK. |
| Intended users | The site presents Dataloop for data engineers, data scientists, software engineers, AI and data leaders, and human reviewers. | The pricing page positions Starter for individuals and small teams prototyping AI applications, Team for teams scaling a few applications, and Enterprise for companies shipping multiple applications across teams. |
| Product | Dataloop describes itself as an enterprise-first AI development platform for building AI applications. | Encord describes itself as a multimodal data infrastructure layer for AI teams, spanning pre- and post-training through deployment. |
| Support | The contact page lists a support link and gives the address 2 Sapir st, Herzliya, Israel. | The listed plans include self-serve support for Starter, onboarding support for Team, and enterprise SLA and support for Enterprise. |
Dataloop plans
- Custom subscriptionPriced on request
Encord plans
- EnterprisePriced on request
- StarterPriced on request
- TeamPriced on request
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 Encord if…
Encord suits AI individuals, teams, and enterprises managing multimodal labeling, curation, and evaluation. It is relevant when API access, varied deployments, and specialized annotation types are needed.