Encord
5.6#8 in ai image segmentation softwareWebAPISelf-hosted
VisitEncord vs Supervisely
Supervisely
6.9#4 in ai image segmentation softwareFrom €199 a monthFree planWebAPISelf-hosted
VisitWhat both publish
| Fact | Encord | Supervisely |
|---|---|---|
| Annotation | The platform supports human-in-the-loop labeling and review for image, video, audio, text, DICOM, LiDAR, geospatial, ECG, and other data. | Its labeling tools include image, video, LiDAR and DICOM workflows, with AI-assisted labeling and tracking. |
| Integrations | 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. | Supervisely offers a JSON API, Python SDK and AppEngine for automating workflows and building integrations. |
| Intended users | 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. | The Community plan is described for open-source projects, individuals, ML researchers and small teams. |
| Product | Encord describes itself as a multimodal data infrastructure layer for AI teams, spanning pre- and post-training through deployment. | Supervisely is a computer vision platform for curating data, labeling images, videos, 3D and medical imagery, and building production models. |
| Security | The security page says data at rest is encrypted with AES-256 and data in transit uses HTTPS over TLS, including TLS 1.3 support. | The security page describes role-based access permissions, SSL certificates and optional verification of uploaded assets with threat scanners. |
Encord plans
- EnterprisePriced on request
- StarterPriced on request
- TeamPriced on request
Supervisely plans
- CommunityFree
- Pro€199 a month
- EnterprisePriced on request
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.
Pick Supervisely if…
The Community plan is described for open-source projects, individuals, ML researchers, and small teams. Supervisely also suits teams that need annotation and model workflows or enterprise deployment options.