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Compare CVAT.ai and Encord 
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At a Glance
Market Segments
Small-Business (55.6% of reviews)
Small-Business (51.6% of reviews)
Entry-Level Pricing
No pricing available
Contact Us
CVAT.ai
Star Rating
(18)4.6 out of 5
Market Segments
Small-Business (55.6% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about CVAT.aiEncord
Star Rating
(63)4.8 out of 5
Market Segments
Small-Business (51.6% of reviews)
Pros & Cons
Entry-Level Pricing
Contact Us
Learn more about EncordSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Encord excels in Quality of Support, scoring a perfect 10.0, while CVAT.ai has a solid score of 9.1. Reviewers mention that Encord's support team is highly responsive and knowledgeable, making it easier for small businesses to resolve issues quickly.
- Reviewers mention that Encord offers superior Ease of Use with a score of 9.5 compared to CVAT.ai's 8.8. Users say that Encord's intuitive interface and user-friendly features, such as the Labeling Interface, significantly reduce the learning curve for new users.
- Users on G2 highlight Encord's strong performance in Task Quality, scoring 9.8, while CVAT.ai scores 9.2. Reviewers mention that Encord's Automated Labeling Tools enhance accuracy and efficiency, making it a preferred choice for data annotation tasks.
- Reviewers mention that Encord shines in Data Quality with a score of 9.6, compared to CVAT.ai's 8.9. Users report that Encord's Data Validation Features ensure high-quality outputs, which is crucial for machine learning projects.
- Users say that Encord's Machine Learning Pre-Labeling capabilities, scoring 9.7, outperform CVAT.ai's 8.8. Reviewers mention that this feature significantly speeds up the labeling process, allowing teams to focus on more complex tasks.
- G2 users report that Encord's Human-in-the-Loop functionality scores 9.8, while CVAT.ai scores 9.0. Reviewers mention that Encord's approach to integrating human feedback into the labeling process enhances overall accuracy and reliability.
Pricing
Entry-Level Pricing
CVAT.ai
No pricing availableEncord
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
Free Trial
CVAT.ai
No trial information availableEncord
Free Trial is available
Ratings
Meets Requirements
9.4
17
9.3
48
Ease of Use
8.9
18
9.5
49
Ease of Setup
9.0
15
8.5
13
Ease of Admin
Not enough data
7.9
12
Quality of Support
9.2
16
9.9
47
Has the product been a good partner in doing business?
Not enough data
9.4
12
Product Direction (% positive)
10.0
18
9.8
48
Features by Category
Deployment
Not enough data
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
Deployment
Not enough data
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
Management
Not enough data
9.8
7
Not enough data
9.8
8
Not enough data
10.0
6
Not enough data
9.8
8
Operations
Not enough data
10.0
6
Not enough data
9.7
6
Not enough data
10.0
9
Management
Not enough data
10.0
7
Not enough data
10.0
8
Not enough data
9.8
7
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
System
Not enough data
9.0
5
Model Development
Not enough data
Not enough data
Not enough data
9.7
6
Not enough data
10.0
5
Not enough data
9.7
6
Model Development
Not enough data
Not enough data
Machine/Deep Learning Services
Not enough data
9.5
7
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
9.7
5
Machine/Deep Learning Services
Not enough data
Not enough data
Not enough data
9.7
5
Deployment
Not enough data
10.0
7
Not enough data
9.8
7
Not enough data
9.5
7
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
14
9.4
33
9.2
15
9.8
32
9.0
15
9.5
33
9.0
15
9.8
31
Automation
8.8
15
9.5
26
8.5
14
9.5
25
Image Annotation
9.2
15
9.6
32
9.0
15
9.3
28
8.6
15
9.2
24
8.7
14
9.7
25
Natural Language Annotation
Feature Not Available
9.6
15
Feature Not Available
9.7
15
Feature Not Available
9.6
17
Speech Annotation
7.4
9
9.6
15
7.4
9
9.5
14
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
Not enough data
Feature Not Available
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
CVAT.ai and Encord are categorized as Data Labeling
Unique Categories
CVAT.ai has no unique categories
Encord is categorized as Active Learning Tools, MLOps Platforms, Data Science and Machine Learning Platforms, Image Recognition, and Machine Learning
Reviews
Reviewers' Company Size
CVAT.ai
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Encord
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
Information Technology and Services
16.7%
Retail
11.1%
Research
11.1%
Computer Games
11.1%
Telecommunications
5.6%
Other
44.4%
Computer Software
35.5%
Hospital & Health Care
12.9%
Medical Devices
11.3%
Food & Beverages
9.7%
Information Technology and Services
8.1%
Other
22.6%
Discussions
CVAT.ai has no discussions with answers
Encord has no discussions with answers
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