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Compare Appen and Kili 
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At a Glance
Market Segments
Small-Business (54.8% of reviews)
Mid-Market (40.0% of reviews)
Entry-Level Pricing
SaaS subscription pricing dependent on use case and data type
Free Trial 5000 Annotations
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 plansKili
Star Rating
(48)4.7 out of 5
Market Segments
Mid-Market (40.0% of reviews)
Pros & Cons
Entry-Level Pricing
Free Trial 5000 Annotations
Browse all 3 pricing plansSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Appen excels in Ease of Setup with a score of 9.1, making it a preferred choice for those who prioritize quick implementation. In contrast, Kili's score of 8.3 indicates that users may face some challenges during the initial setup process.
- Reviewers mention that Kili shines in Quality of Support, achieving a score of 9.5, which is significantly higher than Appen's 8.2. This suggests that Kili users feel more supported and have better access to assistance when needed.
- G2 users highlight Kili's superior Labeler Quality with a score of 9.1 compared to Appen's 8.5. This indicates that Kili may provide more accurate and reliable labeling, which is crucial for data quality in machine learning projects.
- Users on G2 report that Appen has a strong performance in Human-in-the-Loop processes, scoring 8.3, which is lower than Kili's 9.1. This suggests that Kili may offer a more effective integration of human oversight in data labeling tasks.
- Reviewers mention that Kili's Automatic Data Cleansing feature, with a score of 8.9, is a standout, while Appen's score of 7.8 indicates that users may find Kili's data preparation capabilities more robust and efficient.
- Users say that Kili's Image Segmentation feature, scoring 9.1, is highly praised for its accuracy and effectiveness, while Appen's score of 8.3 suggests that it may not perform as well in this specific area, impacting users who require precise image analysis.
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.
Kili
Free
Free Trial
5000 Annotations
For individual contributors, students and ML enthusiast developing small scale projects
- Image, video, text, PDFs, large images & rich text labeling interfaces
- 5,000 annotations maximum
- 5 users per project maximum
Free Trial
Appen
No trial information availableKili
Free Trial is available
Ratings
Meets Requirements
8.2
28
9.1
26
Ease of Use
8.2
28
8.8
26
Ease of Setup
8.6
12
8.3
9
Ease of Admin
9.2
8
9.3
10
Quality of Support
8.0
27
9.5
25
Has the product been a good partner in doing business?
8.5
8
8.7
9
Product Direction (% positive)
7.8
26
10.0
30
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
Data Science and Machine Learning PlatformsHide 25 FeaturesShow 25 Features
Not enough data
Not enough data
System
Not enough data
Not enough data
Model Development
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 Development
Not enough data
Not enough data
Machine/Deep Learning Services
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Machine/Deep Learning Services
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
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
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
8.5
11
9.2
18
8.7
10
9.1
21
9.0
10
9.1
20
8.3
9
9.1
19
Automation
8.1
9
9.0
18
8.7
9
8.9
12
Image Annotation
8.3
9
9.1
15
8.7
9
9.2
18
8.3
9
8.7
14
8.8
10
9.2
18
Natural Language Annotation
8.8
8
9.0
17
8.8
8
8.9
9
9.0
8
9.0
10
Speech Annotation
8.8
8
8.8
12
8.7
9
8.6
7
Recognition Type
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
Not enough data
Not enough data
Facial Recognition
Not enough data
Not enough data
Not enough data
Not enough data
Labeling
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
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
Appen and Kili are categorized as Data Labeling
Unique Categories
Appen is categorized as Machine Learning Data Catalog
Kili is categorized as MLOps Platforms, Image Recognition, Data Science and Machine Learning Platforms, and Machine Learning
Reviews
Reviewers' Company Size
Appen
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Kili
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
42.2%
Computer Software
15.6%
Research
4.4%
Marketing and Advertising
4.4%
Environmental Services
4.4%
Other
28.9%
Alternatives
Discussions
Appen has no discussions with answers
Kili has no discussions with answers
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