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Compare Dataloop and Encord 
Featured Products
At a Glance
Market Segments
Mid-Market (39.8% of reviews)
Small-Business (50.8% of reviews)
Entry-Level Pricing
No pricing available
Contact Us
Dataloop
Star Rating
(90)4.4 out of 5
Market Segments
Mid-Market (39.8% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about DataloopEncord
Star Rating
(64)4.8 out of 5
Market Segments
Small-Business (50.8% of reviews)
Pros & Cons
Entry-Level Pricing
Contact Us
Learn more about EncordDataloop vs Encord
When assessing the two solutions, reviewers found Encord easier to use, and do business with overall. However, reviewers preferred the ease of administration with Dataloop. Reviewers felt that the products are equally easy to set up.
- Reviewers felt that Encord meets the needs of their business better than Dataloop.
- When comparing quality of ongoing product support, reviewers felt that Encord is the preferred option.
- For feature updates and roadmaps, our reviewers preferred the direction of Encord over Dataloop.
Pricing
Entry-Level Pricing
Dataloop
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
Dataloop
No trial information availableEncord
Free Trial is available
Ratings
Meets Requirements
8.7
75
9.3
49
Ease of Use
8.8
76
9.5
50
Ease of Setup
8.5
40
8.5
14
Ease of Admin
8.8
20
8.1
13
Quality of Support
8.9
74
9.9
48
Has the product been a good partner in doing business?
8.8
20
9.5
13
Product Direction (% positive)
8.6
68
9.8
49
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
9.0
8
9.0
5
Model Development
9.3
7
Not enough data
8.8
7
9.7
6
8.8
7
10.0
5
8.3
7
9.7
6
Model Development
8.3
8
Not enough data
Machine/Deep Learning Services
9.4
8
9.5
7
8.3
6
Not enough data
8.1
6
Not enough data
8.3
9
9.7
5
Machine/Deep Learning Services
8.6
6
Not enough data
8.3
9
9.7
5
Deployment
8.9
6
10.0
7
8.5
9
9.8
7
8.3
9
9.5
7
Generative AI
7.9
7
Not enough data
8.5
8
Not enough data
9.2
6
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
8.8
53
9.4
33
9.0
53
9.8
32
9.1
54
9.5
33
8.9
52
9.8
31
Automation
8.8
52
9.5
26
8.7
48
9.5
25
Image Annotation
9.2
51
9.6
32
9.2
52
9.3
28
9.1
50
9.2
24
9.2
51
9.7
25
Natural Language Annotation
9.0
43
9.6
15
8.9
42
9.7
15
8.9
45
9.6
17
Speech Annotation
9.0
40
9.6
15
8.9
39
9.5
14
Recognition Type
8.4
34
Not enough data
9.0
36
Not enough data
8.6
35
Not enough data
8.4
32
Not enough data
8.8
32
Feature Not Available
8.7
33
Not enough data
8.5
33
Not enough data
8.8
33
Not enough data
Facial Recognition
8.8
33
Not enough data
8.6
32
Not enough data
Labeling
8.9
34
Not enough data
9.4
33
Not enough data
8.7
32
Not enough data
Deployment
8.3
33
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
Dataloop and Encord are categorized as Active Learning Tools, Data Labeling, MLOps Platforms, Data Science and Machine Learning Platforms, and Image Recognition
Reviews
Reviewers' Company Size
Dataloop
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
27.3%
Computer Software
26.1%
Retail
2.3%
Research
2.3%
Oil & Energy
2.3%
Other
39.8%
Computer Software
36.5%
Hospital & Health Care
12.7%
Medical Devices
11.1%
Food & Beverages
9.5%
Information Technology and Services
7.9%
Other
22.2%
Alternatives
Discussions
What are data annotations?
1 Comment
Official Response from Dataloop
Data annotations refer to the process of labeling or adding informative tags to raw data, which can include text, images, audio, or video. This process is...Read more
What are data annotations?
1 Comment
Official Response from Dataloop
Data annotations refer to the process of labeling or adding informative tags to raw data, which can include text, images, audio, or video. This process is...Read more
Is Dataloop free?
1 Comment
Official Response from Dataloop
Dataloop operates on a quote-based pricing model and does not currently offer a free plan. Our pricing is tailored to match the specific needs and scale of...Read more
Encord has no discussions with answers
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