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Compare Encord and Supervisely Computer Vision Platform 
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At a Glance
Market Segments
Small-Business (50.8% of reviews)
Mid-Market (44.4% of reviews)
Entry-Level Pricing
Contact Us
No pricing available
Encord
Star Rating
(62)4.8 out of 5
Market Segments
Small-Business (50.8% of reviews)
Pros & Cons
Entry-Level Pricing
Contact Us
Learn more about EncordSupervisely Computer Vision Platform
Star Rating
(10)4.7 out of 5
Market Segments
Mid-Market (44.4% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about Supervisely Computer Vision PlatformSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Supervisely Computer Vision Platform excels in ease of use, achieving a perfect score of 10.0, while Encord, although still strong, scores slightly lower at 9.5. Reviewers mention that the intuitive interface of Supervisely makes it easier for teams to adopt quickly.
- Reviewers mention that Encord offers superior quality of support, with a perfect score of 10.0 compared to Supervisely's 9.0. Users on G2 highlight the responsiveness and helpfulness of Encord's support team as a key advantage.
- G2 users report that Encord shines in the area of model training, particularly with its pre-built algorithms scoring a perfect 10.0, while Supervisely's model training efficiency scores 9.7. Reviewers say that the availability of pre-built algorithms in Encord significantly speeds up the development process.
- Users say that both platforms provide strong data quality, but Encord edges out with a score of 9.6 compared to Supervisely's 9.5. Reviewers mention that Encord's focus on actionable insights for data quality enhances the overall effectiveness of their projects.
- Reviewers mention that Supervisely's deployment flexibility is impressive, scoring 9.8 in both ease of deployment and scalability, while Encord also performs well but scores slightly lower in scalability at 9.7. Users report that Supervisely's deployment options make it easier to integrate into existing workflows.
- Users on G2 report that Encord's automation features, particularly in machine learning pre-labeling, score 9.7, outperforming Supervisely's score of 9.3. Reviewers say that Encord's automation capabilities significantly reduce the time spent on data labeling tasks.
Pricing
Entry-Level Pricing
Encord
Simple and scalable pricing
Contact Us
Our pricing scales with your organization. Start building out your data annotation & active learning pipelines today.
- Computer vision labeling toolkit
- Model assisted labeling using your own models or our proprietary micro-models
- Automated object tracking and interpolation
Supervisely Computer Vision Platform
No pricing availableFree Trial
Encord
Free Trial is available
Supervisely Computer Vision Platform
No trial information availableRatings
Meets Requirements
9.3
47
9.3
7
Ease of Use
9.5
48
10.0
7
Ease of Setup
8.3
12
Not enough data
Ease of Admin
7.7
11
Not enough data
Quality of Support
9.9
46
9.0
7
Has the product been a good partner in doing business?
9.4
11
Not enough data
Product Direction (% positive)
9.8
47
10.0
7
Features by Category
Deployment
9.4
6
Not enough data
9.5
7
Not enough data
9.8
7
Not enough data
9.8
8
Not enough data
9.8
8
Not enough data
Deployment
10.0
6
Not enough data
9.5
7
Not enough data
9.5
7
Not enough data
9.6
8
Not enough data
10.0
8
Not enough data
Management
9.8
7
Not enough data
9.8
8
Not enough data
10.0
6
Not enough data
9.8
8
Not enough data
Operations
10.0
6
Not enough data
9.7
6
Not enough data
10.0
9
Not enough data
Management
10.0
7
Not enough data
10.0
8
Not enough data
9.8
7
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
System
9.0
5
Not enough data
Model Development
Not enough data
Not enough data
9.7
6
Not enough data
10.0
5
Not enough data
9.7
6
Not enough data
Model Development
Not enough data
Not enough data
Machine/Deep Learning Services
9.5
7
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
9.7
5
Not enough data
Machine/Deep Learning Services
Not enough data
Not enough data
9.7
5
Not enough data
Deployment
10.0
7
Not enough data
9.8
7
Not enough data
9.5
7
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Quality
9.4
32
9.0
7
9.8
31
9.3
7
9.5
32
9.5
7
9.8
30
8.6
7
Automation
9.5
26
9.3
7
9.5
25
8.8
7
Image Annotation
9.6
31
8.6
7
9.3
28
8.3
7
9.2
24
8.3
7
9.7
25
9.3
7
Natural Language Annotation
9.6
15
8.8
7
9.7
15
7.9
7
9.6
17
8.1
7
Speech Annotation
9.6
15
8.1
6
9.5
14
8.3
7
Recognition Type
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Feature Not Available
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Facial Recognition
Not enough data
Not enough data
Not enough data
Not enough data
Labeling
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Deployment
Not enough data
Not enough data
Model Training & Optimization - Active Learning Tools
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Data Management & Annotation - Active Learning Tools
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Model Performance & Analysis - Active Learning Tools
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration - Machine Learning
Not enough data
Not enough data
Learning - Machine Learning
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Encord and Supervisely Computer Vision Platform are categorized as Data Labeling
Unique Categories
Encord is categorized as Active Learning Tools, MLOps Platforms, Data Science and Machine Learning Platforms, Image Recognition, and Machine Learning
Supervisely Computer Vision Platform has no unique categories
Reviews
Reviewers' Company Size
Encord
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Supervisely Computer Vision Platform
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Computer Software
36.1%
Medical Devices
11.5%
Hospital & Health Care
11.5%
Food & Beverages
9.8%
Information Technology and Services
8.2%
Other
23.0%
Information Technology and Services
44.4%
Logistics and Supply Chain
11.1%
Education Management
11.1%
Computer Software
11.1%
Apparel & Fashion
11.1%
Other
11.1%
Discussions
Encord has no discussions with answers
Supervisely Computer Vision Platform has no discussions with answers
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