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Compare Datature and Encord 
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At a Glance
Market Segments
Small-Business (63.2% of reviews)
Small-Business (50.8% of reviews)
Entry-Level Pricing
Free Trial Per Year
Contact Us
Datature
Star Rating
(38)4.9 out of 5
Market Segments
Small-Business (63.2% of reviews)
Pros & Cons
Entry-Level Pricing
Free Trial Per Year
Learn more about DatatureEncord
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 EncordSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Encord excels in Labeler Quality with a score of 9.5, while Datature matches this score but lacks the same level of user feedback on the overall quality of the labeling process. Reviewers mention that Encord's labeling tools are intuitive and efficient, making it easier for teams to manage their data annotation tasks.
- Reviewers mention that Encord's Human-in-the-Loop feature scores 9.8, indicating a strong emphasis on collaborative data labeling, whereas Datature's score of 9.6 suggests it is slightly less effective in this area. Users on G2 appreciate how Encord facilitates seamless collaboration between human annotators and AI, enhancing the overall data quality.
- G2 users highlight that Encord's Model Training Efficiency is rated at 9.7, which is superior to Datature's performance in this category. Reviewers say that Encord's active learning tools significantly reduce the time required for model training, allowing teams to iterate quickly and improve model accuracy.
- Users report that Encord offers better Data Quality management with a score of 9.6 compared to Datature's 9.2. Reviewers mention that Encord's actionable insights for data quality help teams identify and rectify issues more effectively, leading to higher-quality datasets.
- Reviewers mention that Encord's Monitoring capabilities are rated at 10.0, showcasing its robust features for tracking model performance over time. In contrast, Datature's score of 9.4 indicates it may not provide the same level of comprehensive monitoring tools, which users find essential for maintaining model accuracy.
- Users on G2 report that Encord's Scalability is rated at 10.0, making it a preferred choice for growing businesses, while Datature's score of 9.7 suggests it may not scale as effectively. Reviewers say that Encord's architecture allows for seamless expansion as data needs increase, which is crucial for small businesses looking to grow.
Pricing
Entry-Level Pricing
Datature
Team / Professional Plan
Free Trial
Per Year
- Team Collaboration Features
- Unlimited Management API
- Unlimited Inference API
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
Free Trial
Datature
Free Trial is available
Encord
Free Trial is available
Ratings
Meets Requirements
9.4
34
9.3
47
Ease of Use
9.5
34
9.5
48
Ease of Setup
9.3
12
8.3
12
Ease of Admin
Not enough data
7.7
11
Quality of Support
9.7
34
9.9
46
Has the product been a good partner in doing business?
Not enough data
9.4
11
Product Direction (% positive)
10.0
34
9.8
47
Features by Category
Deployment
8.2
19
9.4
6
8.8
21
9.5
7
9.3
20
9.8
7
9.6
22
9.8
8
9.5
22
9.8
8
Deployment
Feature Not Available
10.0
6
8.9
22
9.5
7
9.5
21
9.5
7
9.5
21
9.6
8
9.3
23
10.0
8
Management
8.8
19
9.8
7
9.2
20
9.8
8
8.9
18
10.0
6
9.2
21
9.8
8
Operations
9.3
23
10.0
6
8.8
20
9.7
6
9.2
21
10.0
9
Management
8.9
18
10.0
7
9.3
19
10.0
8
8.6
17
9.8
7
Generative AI
4.0
13
Not enough data
4.0
13
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
9.5
21
9.4
32
9.2
23
9.8
31
9.0
22
9.5
32
9.5
22
9.8
30
Automation
9.1
22
9.5
26
9.2
19
9.5
25
Image Annotation
9.3
23
9.6
31
9.9
23
9.3
28
8.3
20
9.2
24
8.9
23
9.7
25
Natural Language Annotation
5.8
21
9.6
15
4.5
17
9.7
15
5.8
19
9.6
17
Speech Annotation
Feature Not Available
9.6
15
Feature Not Available
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
Datature and Encord are categorized as Data Labeling and MLOps Platforms
Unique Categories
Datature has no unique categories
Encord is categorized as Active Learning Tools, Data Science and Machine Learning Platforms, Image Recognition, and Machine Learning
Reviews
Reviewers' Company Size
Datature
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
Computer Software
21.1%
Research
15.8%
Higher Education
10.5%
Electrical/Electronic Manufacturing
7.9%
Industrial Automation
5.3%
Other
39.5%
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%
Alternatives
Discussions
Datature has no discussions with answers
Encord has no discussions with answers
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