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Compare Appen and V7 Darwin 
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At a Glance
Market Segments
Small-Business (54.8% of reviews)
Small-Business (55.8% of reviews)
Entry-Level Pricing
SaaS subscription pricing dependent on use case and data type
Free
Appen
Star Rating
(32)4.2 out of 5
Market Segments
Small-Business (54.8% of reviews)
Pros & Cons
Entry-Level Pricing
SaaS subscription pricing dependent on use case and data type
Browse all 2 pricing plansV7 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 plansSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Appen excels in Managed Service with a perfect score of 10.0, indicating a strong commitment to customer support and service delivery, while V7 also scores 10.0 but users mention that its Application deployment is particularly user-friendly.
- Reviewers mention that V7's Labeler Quality and Task Quality scores of 9.4 and 9.5 respectively, highlight its superior performance in data labeling tasks, whereas Appen's scores of 8.5 in both areas suggest room for improvement.
- G2 users highlight V7's Human-in-the-Loop feature with a score of 9.4, which enhances the quality of machine learning models, while Appen's score of 8.3 indicates that users feel it could benefit from more robust human oversight capabilities.
- Users on G2 report that V7's Model Training capabilities are top-notch, scoring a perfect 10.0, which reviewers say allows for efficient and effective model development, while Appen's offerings in this area are perceived as less comprehensive.
- Reviewers mention that V7's Data Quality score of 9.3 is a significant advantage, as it ensures high-quality outputs, while Appen's score of 8.9 suggests that users have encountered some inconsistencies in data quality.
- Users say that V7's Automation features, particularly in Machine Learning Pre-Labeling and Automatic Routing of Labeling, with scores of 9.3 and 9.5 respectively, streamline workflows effectively, whereas Appen's scores of 8.1 and 9.0 indicate that its automation tools may not be as efficient.
Pricing
Entry-Level Pricing
Appen
Appen Data Annotation Platform
SaaS subscription pricing dependent on use case and data type
The industry’s most advanced AI-assisted data annotation platform used to collect and annotate data for training both computer vision and natural language processing AI models.
- Data annotation capabilities that support all data types (text, audio, image, video, sensor) and use cases including search relevance, computer vision, and natural language processing (NLP/Speech).
- Create and launch data annotation jobs easily through our plug and play graphical user interface, or programmatically through our API.
- Smart Labeling capabilities have built-in Machine Learning assistance to save customers time, effort and money - delivering high-quality training data and accelerating the ROI and your AI initiatives.
V7 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
Appen
No trial information availableV7 Darwin
Free Trial is available
Ratings
Meets Requirements
8.2
28
9.5
38
Ease of Use
8.2
28
9.5
38
Ease of Setup
8.6
12
9.5
17
Ease of Admin
9.2
8
9.4
15
Quality of Support
8.0
27
9.6
36
Has the product been a good partner in doing business?
8.5
8
9.9
14
Product Direction (% positive)
7.8
26
9.6
32
Features by Category
Data Governance
8.3
13
Not enough data
8.2
12
Not enough data
7.8
12
Not enough data
Data Preparation
8.3
13
Not enough data
8.2
13
Not enough data
7.9
12
Not enough data
7.9
12
Not enough data
Collaboration
8.1
12
Not enough data
8.1
13
Not enough data
8.2
11
Not enough data
8.0
11
Not enough data
Artificial Intelligence
8.3
11
Not enough data
7.2
10
Not enough data
7.4
11
Not enough data
Generative AI
7.6
7
Not enough data
8.3
7
Not enough data
Agentic AI - Machine Learning Data Catalog
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
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
Quality
8.5
11
9.4
21
8.7
10
9.5
24
9.0
10
9.4
21
8.3
9
9.3
22
Automation
8.1
9
9.4
16
8.7
9
9.4
14
Image Annotation
8.3
9
9.3
27
8.7
9
9.4
24
8.3
9
9.1
17
8.8
10
9.2
18
Natural Language Annotation
8.8
8
9.1
13
8.8
8
8.5
9
9.0
8
9.0
10
Speech Annotation
8.8
8
7.7
8
8.7
9
7.5
8
Categories
Categories
Shared Categories
Appen and V7 Darwin are categorized as Data Labeling
Unique Categories
Appen is categorized as Machine Learning Data Catalog
V7 Darwin is categorized as MLOps Platforms
Reviews
Reviewers' Company Size
Appen
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
22.6%
Higher Education
9.7%
Education Management
9.7%
Internet
6.5%
Computer Software
6.5%
Other
45.2%
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
Appen has no discussions with answers
V7 Darwin has no discussions with answers
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