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Compare Dataloop and V7 Darwin 
At a Glance
Market Segments
Mid-Market (39.8% of reviews)
Small-Business (55.8% of reviews)
Entry-Level Pricing
No pricing available
Free
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 DataloopV7 Darwin
Star Rating
(54)4.8 out of 5
Market Segments
Small-Business (55.8% of reviews)
Pros & Cons
Entry-Level Pricing
Free
Browse all 4 pricing plansDataloop vs V7 Darwin
When assessing the two solutions, reviewers found V7 Darwin easier to use, set up, and administer. Reviewers also preferred doing business with V7 Darwin overall.
- Reviewers felt that V7 Darwin meets the needs of their business better than Dataloop.
- When comparing quality of ongoing product support, reviewers felt that V7 Darwin is the preferred option.
- For feature updates and roadmaps, our reviewers preferred the direction of V7 Darwin over Dataloop.
Pricing
Entry-Level Pricing
Dataloop
No pricing availableV7 Darwin
Free Plan
Free
Try out the core functionalities and set up your workflow for free.
- 1 Workspace
- 10 User Licenses
- 3 Integrated Models
Free Trial
Dataloop
No trial information availableV7 Darwin
Free Trial is available
Ratings
Meets Requirements
8.7
75
9.5
38
Ease of Use
8.8
76
9.5
38
Ease of Setup
8.5
40
9.5
17
Ease of Admin
8.8
20
9.4
15
Quality of Support
8.9
74
9.6
36
Has the product been a good partner in doing business?
8.8
20
9.9
14
Product Direction (% positive)
8.6
68
9.6
32
Features by Category
Deployment
Not enough data
Not enough data
Not enough data
9.4
6
Not enough data
9.7
5
Not enough data
9.0
7
Not enough data
9.8
7
Deployment
Not enough data
Not enough data
Not enough data
9.3
5
Not enough data
9.7
6
Not enough data
9.2
6
Not enough data
9.8
7
Management
Not enough data
9.3
5
Not enough data
10.0
6
Not enough data
Not enough data
Not enough data
Not enough data
Operations
Not enough data
9.7
6
Not enough data
Not enough data
Not enough data
10.0
6
Management
Not enough data
10.0
5
Not enough data
9.7
5
Not enough data
9.3
5
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
System
9.0
8
Not enough data
Model Development
9.3
7
Not enough data
8.8
7
Not enough data
8.8
7
Not enough data
8.3
7
Not enough data
Model Development
8.3
8
Not enough data
Machine/Deep Learning Services
9.4
8
Not enough data
8.3
6
Not enough data
8.1
6
Not enough data
8.3
9
Not enough data
Machine/Deep Learning Services
8.6
6
Not enough data
8.3
9
Not enough data
Deployment
8.9
6
Not enough data
8.5
9
Not enough data
8.3
9
Not enough data
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
21
9.0
53
9.5
24
9.1
54
9.4
21
8.9
52
9.3
22
Automation
8.8
52
9.4
16
8.7
48
9.4
14
Image Annotation
9.2
51
9.3
27
9.2
52
9.4
24
9.1
50
9.1
17
9.2
51
9.2
18
Natural Language Annotation
9.0
43
9.1
13
8.9
42
8.5
9
8.9
45
9.0
10
Speech Annotation
9.0
40
7.7
8
8.9
39
7.5
8
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
Not enough data
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
Categories
Categories
Shared Categories
Dataloop and V7 Darwin are categorized as Data Labeling and MLOps Platforms
Unique Categories
Dataloop is categorized as Active Learning Tools, Data Science and Machine Learning Platforms, and Image Recognition
V7 Darwin has no unique categories
Reviews
Reviewers' Company Size
Dataloop
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
V7 Darwin
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%
Information Technology and Services
25.0%
Computer Software
19.2%
Research
7.7%
Hospital & Health Care
5.8%
Industrial Automation
3.8%
Other
38.5%
Alternatives
Discussions
What are the industries that Dataloop supports?
1 Comment
Official Response from Dataloop
Dataloop is designed to be data agnostic, which enables us to support a broad spectrum of industries. Our platform's flexibility and advanced AI capabilities...Read more
What are the industries that Dataloop supports?
1 Comment
Official Response from Dataloop
Dataloop is designed to be data agnostic, which enables us to support a broad spectrum of industries. Our platform's flexibility and advanced AI capabilities...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
V7 Darwin has no discussions with answers
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