Supervisely
End-to-end platform combining data annotation, AI-powered labeling, and neural network training for computer vision
- Also known as
- supervisely
What is Supervisely?
Supervisely is a web-based platform for labeling images, videos, 3D point clouds, and medical images, with built-in AI-assisted annotation, neural network training, and model deployment capabilities. It supports on-premise and cloud deployments with Python SDK and REST API integration.
What Supervisely does
The capabilities that matter for data labeling, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.
- Model assisted labeling
- ✓
- Programmatic labeling
- ✓
- Rlhf preference data
- -
- On prem private cloud
- ✓
- Open source
- ✓
- SOC2
- -
Platform & deployment
Independently observed- CLI
- Web
- Cloud / SaaS
- On-premise
- Self-hosted
Integrations (6)
Independently observed- Github
- Gitlab
- AWS
- Azure
- OpenID
- LDAP
Supervisely alternatives
Other data labeling we track, ranked by the same independent score.
- Scale AIDataset preparation and AI model assurance platform for enterprise systemslow · 45%
- CVATA comprehensive data annotation platform designed for computer vision teams to convert raw visual data into training-ready datasetslow · 26%
- iMeritData labeling and model fine-tuning platformlow · 14%
- AppenDeliver human-validated data to train advanced AI systems with nuance and contextual understanding at scalelow · 13%
- Kili TechnologyPlatform for building high-quality training datasets through collaborative annotation and labelingmedium · 55%
- Amazon SageMaker Ground TruthService that helps organizations customize AI models through human feedback and expert guidance to improve accuracy and performance for specific use casesmedium · 54%
The Vioscale score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for Supervisely, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Capabilities | 67 | 0.05 | 3.3 | ✓ |
| Security posture | 40 | 0.07 | 2.9 | ✓ |
| Integrations | 24 | 0.04 | 1.0 | ✓ |
| Price level | 0 | 0.05 | 0.0 | - |
| Reliability | 0 | 0.07 | 0.0 | - |
| Pricing transparency | 0 | 0.08 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | Open source, On prem private cloud, Programmatic labeling, Model assisted labeling | mediumsource · 2026-08-25 · 60% |
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 6 | mediumsource · 2026-08-25 · 60% |
Pricing
| Attribute | Value | Evidence |
|---|---|---|
| Model | commercial | mediumsource · 2026-08-21 · 60% |
Security
| Attribute | Value | Evidence |
|---|---|---|
| Soc2 | Yes | lowsource · 2026-08-21 · 48% |