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At a Glance
Market Segments
Small-Business (54.8% of reviews)
Small-Business (63.6% of reviews)
Entry-Level Pricing
SaaS subscription pricing dependent on use case and data type
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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 plansSuperAnnotate
Star Rating
(182)4.9 out of 5
Market Segments
Small-Business (63.6% of reviews)
Pros & Cons
Entry-Level Pricing
Contact Us
Browse all 3 pricing plansSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that SuperAnnotate excels in Labeler Quality with a score of 9.8, while Appen's score of 8.5 indicates room for improvement. Reviewers mention that SuperAnnotate's labeling tools are more intuitive and yield higher accuracy in annotations.
- Reviewers mention that SuperAnnotate offers superior Quality of Support with a score of 9.9 compared to Appen's 8.2. Users on G2 highlight the responsiveness and helpfulness of SuperAnnotate's support team, making it easier to resolve issues quickly.
- Users say that SuperAnnotate's Ease of Use is significantly higher at 9.6, while Appen scores 8.1. Reviewers mention that SuperAnnotate's user interface is more user-friendly, which reduces the learning curve for new users.
- G2 users report that SuperAnnotate shines in Data Quality with a score of 9.8, whereas Appen's score of 8.9 suggests it may not meet the same standards. Users mention that SuperAnnotate's data validation features are more robust, ensuring higher quality outputs.
- Reviewers mention that Appen's Dynamic Data Masking and User Access Management features score 8.3, indicating a solid but not exceptional offering. In contrast, SuperAnnotate's features in these areas are noted for being more comprehensive and easier to implement.
- Users on G2 highlight that SuperAnnotate's Automatic Routing of Labeling feature scores 9.6, significantly outperforming Appen's score of 9.0. Reviewers say this feature enhances workflow efficiency by intelligently assigning tasks based on user availability and expertise.
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.
SuperAnnotate
Pro
Contact Us
Get ready to scale your most sophisticated AI projects and MLOps needs
- Fully customizable multimodal editor
- Image, video, text, and audio editors
- Data curation and exploration
Free Trial
Appen
No trial information availableSuperAnnotate
Free Trial is available
Ratings
Meets Requirements
8.2
28
9.6
116
Ease of Use
8.2
28
9.6
121
Ease of Setup
8.6
12
9.6
81
Ease of Admin
9.2
8
9.6
46
Quality of Support
8.0
27
9.7
118
Has the product been a good partner in doing business?
8.5
8
9.7
47
Product Direction (% positive)
7.8
26
9.5
102
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
9.8
10
Not enough data
9.2
11
Not enough data
9.3
9
Not enough data
9.7
10
Not enough data
9.5
10
Deployment
Not enough data
9.4
11
Not enough data
9.5
11
Not enough data
9.5
10
Not enough data
9.4
11
Not enough data
9.3
12
Management
Not enough data
9.3
9
Not enough data
9.0
10
Not enough data
9.2
8
Not enough data
9.6
8
Operations
Not enough data
9.3
9
Not enough data
9.2
8
Not enough data
9.2
8
Management
Not enough data
9.6
8
Not enough data
9.4
8
Not enough data
9.3
7
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Quality
8.5
11
9.7
77
8.7
10
9.6
76
9.0
10
9.6
75
8.3
9
9.7
70
Automation
8.1
9
9.3
58
8.7
9
9.5
48
Image Annotation
8.3
9
9.3
71
8.7
9
9.4
68
8.3
9
9.3
60
8.8
10
9.5
62
Natural Language Annotation
8.8
8
9.4
47
8.8
8
9.2
40
9.0
8
9.6
44
Speech Annotation
8.8
8
9.2
41
8.7
9
9.1
39
Large Language Model Operationalization (LLMOps)Hide 15 FeaturesShow 15 Features
Not enough data
9.5
15
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
9.6
13
Not enough data
9.6
13
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
9.4
12
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
9.6
13
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
9.5
13
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
9.4
13
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
9.5
11
Not enough data
9.4
13
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
9.5
13
Not enough data
9.6
12
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
9.4
12
Not enough data
9.5
11
Security - Large Language Model Operationalization (LLMOps)
Not enough data
9.5
11
Not enough data
9.4
11
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
9.4
12
Categories
Categories
Shared Categories
Appen and SuperAnnotate are categorized as Data Labeling
Unique Categories
Appen is categorized as Machine Learning Data Catalog
SuperAnnotate is categorized as MLOps Platforms and Large Language Model Operationalization (LLMOps)
Reviews
Reviewers' Company Size
Appen
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
SuperAnnotate
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
24.1%
Computer Software
16.0%
Research
6.8%
Higher Education
4.9%
Health, Wellness and Fitness
3.7%
Other
44.4%
Discussions
Appen has no discussions with answers
What is SuperAnnotate?
1 Comment
MM
SuperAnnotate is an end-to-end platform to annotate, version, and manage ground truth data for your AI.Read more
What is your experience with SuperAnnotate for data annotation, and what would you like to see improved?
1 Comment
ST
I have been invited to skill test for a few projects with superannotate over the past year or so, each resulting in the platform being buggy and not allowing...Read more
SuperAnnotate has no more discussions with answers
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