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Compare Appen and Dataloop 
At a Glance
Market Segments
Small-Business (54.8% of reviews)
Mid-Market (39.8% of reviews)
Entry-Level Pricing
SaaS subscription pricing dependent on use case and data type
No pricing available
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 plansDataloop
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 DataloopAppen vs Dataloop
When assessing the two solutions, reviewers found Dataloop easier to use and do business with overall. However, reviewers preferred the ease of set up with Appen, along with administration.
- Reviewers felt that Dataloop meets the needs of their business better than Appen.
- When comparing quality of ongoing product support, reviewers felt that Dataloop is the preferred option.
- For feature updates and roadmaps, our reviewers preferred the direction of Dataloop over Appen.
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.
Dataloop
No pricing availableFree Trial
Appen
No trial information availableDataloop
No trial information availableRatings
Meets Requirements
8.2
28
8.7
75
Ease of Use
8.2
28
8.8
76
Ease of Setup
8.6
12
8.5
40
Ease of Admin
9.2
8
8.8
20
Quality of Support
8.0
27
8.9
74
Has the product been a good partner in doing business?
8.5
8
8.8
20
Product Direction (% positive)
7.8
26
8.6
68
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
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
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Operations
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
System
Not enough data
9.0
8
Model Development
Not enough data
9.3
7
Not enough data
8.8
7
Not enough data
8.8
7
Not enough data
8.3
7
Model Development
Not enough data
8.3
8
Machine/Deep Learning Services
Not enough data
9.4
8
Not enough data
8.3
6
Not enough data
8.1
6
Not enough data
8.3
9
Machine/Deep Learning Services
Not enough data
8.6
6
Not enough data
8.3
9
Deployment
Not enough data
8.9
6
Not enough data
8.5
9
Not enough data
8.3
9
Generative AI
Not enough data
7.9
7
Not enough data
8.5
8
Not enough data
9.2
6
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
8.5
11
8.8
53
8.7
10
9.0
53
9.0
10
9.1
54
8.3
9
8.9
52
Automation
8.1
9
8.8
52
8.7
9
8.7
48
Image Annotation
8.3
9
9.2
51
8.7
9
9.2
52
8.3
9
9.1
50
8.8
10
9.2
51
Natural Language Annotation
8.8
8
9.0
43
8.8
8
8.9
42
9.0
8
8.9
45
Speech Annotation
8.8
8
9.0
40
8.7
9
8.9
39
Recognition Type
Not enough data
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
Facial Recognition
Not enough data
8.8
33
Not enough data
8.6
32
Labeling
Not enough data
8.9
34
Not enough data
9.4
33
Not enough data
8.7
32
Deployment
Not enough data
8.3
33
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
Appen and Dataloop are categorized as Data Labeling
Unique Categories
Appen is categorized as Machine Learning Data Catalog
Dataloop is categorized as Active Learning Tools, MLOps Platforms, Data Science and Machine Learning Platforms, and Image Recognition
Reviews
Reviewers' Company Size
Appen
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Dataloop
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
27.3%
Computer Software
26.1%
Retail
2.3%
Research
2.3%
Oil & Energy
2.3%
Other
39.8%
Alternatives
Discussions
Appen has no discussions with answers
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
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