Amazon Rekognition vs Supervisely
Side-by-side comparison of features, pricing, and integrations.
Quick Verdict
Amazon Rekognition offers fewer features (18 vs 74) and fewer integrations (3 vs 18). Starting price: Amazon Rekognition at Free vs Supervisely at $199/mo. Amazon Rekognition has 18 unique features while Supervisely has 74 unique features, with 0 features in common.
| Amazon Rekognition | Supervisely | |
|---|---|---|
| Category | AI & Machine Learning | AI & Machine Learning |
| Total Features | 18 | 74 |
| AI-Powered Features | 17 | 19 |
| Starting Price | Free | $199/mo |
| Pricing Tiers | 6 | 3 |
| Integrations | 3 | 18 |
| Shared Features | 0 | |
| Shared Integrations | 0 | |
| Data Quality | 70% | 95% |
Feature Comparison by Category
AI (0 vs 5)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| AI-Assisted Labeling | ||
| Automatic Cuboid Adjustment | ||
| Automatic Ground Segmentation | ||
| CLIP Embeddings | ||
| Smart Tools |
AI / Automation (0 vs 1)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Auto Labeling with AI Models |
Analytics (0 vs 1)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Dataset Quality Heatmaps |
Annotation (0 vs 20)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| 3D Cuboid Annotation | ||
| Alpha Matting | ||
| DICOM/Medical Imaging Labeling | ||
| High-Depth Color Range | ||
| High-Resolution Image Support | ||
| Image Labeling | ||
| Key-Value Tags | ||
| Keypoint Annotation | ||
| LiDAR/3D Point Cloud Labeling | ||
| Multi-Camera/Multi-Stream Support | ||
| Multi-spectral Image Support | ||
| Multi-view Annotation | ||
| Nested Ontologies | ||
| Object Detection | ||
| Object Tracking |
Collaboration (0 vs 4)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Issue Tracking | ||
| Labeling Exams | ||
| Labeling Jobs and Queues | ||
| User Collaboration |
Content Moderation (1 vs 0)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Content Moderation Detection |
Customization (0 vs 2)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| AppEngine | ||
| Custom Labeling UI |
Data Management (0 vs 7)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Custom Augmentations | ||
| Data Management | ||
| Import and Export | ||
| Migration Tools | ||
| Pre-processing and Data Augmentation | ||
| Search and Visualize | ||
| Synthetic Data Generation |
Data Storage (1 vs 0)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Face Metadata Storage |
Deployment (0 vs 2)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Cloud-Hosted Deployment | ||
| On-Premise Deployment |
Face Recognition (5 vs 0)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Celebrity Recognition | ||
| Face Detection and Analysis | ||
| Face Liveness Detection | ||
| Face Search | ||
| Facial Comparison and Analysis |
Image Analysis (2 vs 0)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Image Properties Detection | ||
| Label Detection |
Infrastructure (0 vs 4)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| CDN Acceleration | ||
| Custom CDN | ||
| GPU Support | ||
| On-the-fly Transcoding |
Integrations (0 vs 4)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Cloud Storage Integration | ||
| Developer Portal | ||
| Python SDK | ||
| REST API |
Machine Learning (1 vs 0)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Custom Model Training |
Model Deployment (0 vs 4)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Batch Processing | ||
| Custom Inference Pipelines | ||
| Inference API | ||
| Model Deployment |
Model Training (0 vs 9)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Active Learning | ||
| Auto Training Pipelines | ||
| Checkpoint Export | ||
| Cloud Training | ||
| Custom Model Integration | ||
| Foundation Models | ||
| Model Evaluation and Comparison | ||
| Neural Network Training | ||
| Pretrained Models |
Object Detection (3 vs 0)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Custom Labels | ||
| Person Detection | ||
| Protective Equipment Detection |
Quality Control (0 vs 2)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Consensus Labeling | ||
| Quality Assurance and Review |
Security (0 vs 7)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Activity Logging | ||
| Custom SSL Certificates | ||
| Data Anonymization | ||
| Medical HIPAA Compliance | ||
| Offline/Secure Environment | ||
| Role-Based Access Control | ||
| Single Sign-On (SSO) |
Services (0 vs 2)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Consulting Services | ||
| Labeling Services |
Text Recognition (1 vs 0)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Text Detection |
Video Analysis (4 vs 0)
| Feature | Amazon Rekognition | Supervisely |
|---|---|---|
| Shot Detection | ||
| Stored Video Analysis | ||
| Streaming Video Events | ||
| Video Segment Detection |
Unique Features
Only in Amazon Rekognition (18)
Content Moderation Detection
Face Metadata Storage
Celebrity Recognition
Face Detection and Analysis
Face Liveness Detection
Face Search
Facial Comparison and Analysis
Image Properties Detection
Label Detection
Custom Model Training
Custom Labels
Person Detection
Protective Equipment Detection
Text Detection
Shot Detection
Stored Video Analysis
Streaming Video Events
Video Segment Detection
Only in Supervisely (74)
AI-Assisted Labeling
Automatic Cuboid Adjustment
Automatic Ground Segmentation
CLIP Embeddings
Smart Tools
Auto Labeling with AI Models
Dataset Quality Heatmaps
3D Cuboid Annotation
Alpha Matting
DICOM/Medical Imaging Labeling
High-Depth Color Range
High-Resolution Image Support
Image Labeling
Key-Value Tags
Keypoint Annotation
LiDAR/3D Point Cloud Labeling
Multi-Camera/Multi-Stream Support
Multi-spectral Image Support
Multi-view Annotation
Nested Ontologies
+ 54 more unique features
View Amazon Rekognition details View Supervisely details Amazon Rekognition alternatives Supervisely alternatives
Want to build your own alternative to Amazon Rekognition or Supervisely?
Analyze it with Reap