Compare Encord and Prolific 
Featured Products
At a Glance
Market Segments
Small-Business (51.6% of reviews)
Enterprise (41.5% of reviews)
Entry-Level Pricing
Contact Us
No pricing available
Encord
Star Rating
(65)4.8 out of 5
Market Segments
Small-Business (51.6% of reviews)
Pros & Cons
Entry-Level Pricing
Contact Us
Learn more about EncordProlific
Star Rating
(236)4.6 out of 5
Market Segments
Enterprise (41.5% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about ProlificSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Encord excels in customer support, with users highlighting the team's responsiveness and commitment to incorporating feedback into product development. One user noted the effectiveness of their customer success manager, who comes prepared with technical examples to address specific needs.
- Users say that Encord's integration capabilities, particularly with AWS S3, significantly enhance their data curation and annotation processes. Reviewers appreciate how seamlessly they can connect their existing infrastructure, making it a preferred choice for those with in-house development.
- According to verified reviews, Prolific stands out for its user-friendly interface and effective participant recruitment features. Users commend the platform for its ability to quickly connect researchers with a diverse pool of participants, making it easy to define target demographics for studies.
- Reviewers mention that while Prolific offers a solid experience for participant recruitment, it may not match the advanced data labeling capabilities of Encord. Users have pointed out that Prolific's features, while effective, lack the depth and quality seen in Encord's machine learning and data annotation tools.
- G2 reviewers highlight that Encord's focus on quality is evident in its high ratings for task and data quality. Users have praised the platform for its robust labeling features, which include advanced options like image segmentation and object detection, making it a strong contender for machine learning projects.
- Users report that while both platforms have their strengths, Encord's overall satisfaction ratings are higher, particularly in areas like ease of use and support quality. This suggests that users find Encord to be a more reliable partner in their data projects compared to Prolific, which has received mixed feedback in these areas.
Pricing
Entry-Level Pricing
Encord
Simple and scalable pricing
Contact Us
Our pricing scales with your organization. Start building out your data annotation & active learning pipelines today.
- Computer vision labeling toolkit
- Model assisted labeling using your own models or our proprietary micro-models
- Automated object tracking and interpolation
Prolific
No pricing availableFree Trial
Encord
Free Trial is available
Prolific
No trial information availableRatings
Meets Requirements
9.3
50
8.9
183
Ease of Use
9.5
51
8.9
188
Ease of Setup
8.3
15
8.9
113
Ease of Admin
8.1
14
9.1
34
Quality of Support
9.9
49
7.8
153
Has the product been a good partner in doing business?
9.5
14
9.4
32
Product Direction (% positive)
9.8
50
8.7
183
Features by Category
User Response Methods
Not enough data
8.8
154
Not enough data
5.6
126
Not enough data
5.4
122
Not enough data
5.7
124
Not enough data
7.2
135
Participant Selection
Not enough data
6.7
129
Not enough data
4.8
118
Not enough data
5.5
118
Not enough data
8.2
145
Insights
Not enough data
7.0
127
Not enough data
6.8
132
Not enough data
6.5
126
Generative AI
Not enough data
5.8
74
Functionality
Not enough data
8.6
22
Not enough data
7.4
20
Not enough data
7.6
21
Not enough data
7.2
20
Not enough data
6.9
20
Admin
Not enough data
6.7
19
Deployment
9.4
6
Not enough data
9.5
7
Not enough data
9.8
7
Not enough data
9.8
8
Not enough data
9.8
8
Not enough data
Deployment
10.0
6
Not enough data
9.5
7
Not enough data
9.5
7
Not enough data
9.6
8
Not enough data
10.0
8
Not enough data
Management
9.8
7
Not enough data
9.8
8
Not enough data
10.0
6
Not enough data
9.8
8
Not enough data
Operations
10.0
6
Not enough data
9.7
6
Not enough data
10.0
9
Not enough data
Management
10.0
7
Not enough data
10.0
8
Not enough data
9.8
7
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
System
9.0
5
Not enough data
Model Development
Not enough data
Not enough data
9.7
6
Not enough data
10.0
5
Not enough data
9.7
6
Not enough data
Model Development
Not enough data
Not enough data
Machine/Deep Learning Services
9.5
7
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
9.7
5
Not enough data
Machine/Deep Learning Services
Not enough data
Not enough data
9.7
5
Not enough data
Deployment
10.0
7
Not enough data
9.8
7
Not enough data
9.5
7
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
9.4
33
8.1
9
9.8
32
7.4
7
9.5
33
8.3
9
9.8
31
7.9
8
Automation
9.5
26
5.3
6
9.5
25
5.0
6
Image Annotation
9.6
32
4.4
6
9.3
28
5.3
5
9.2
24
4.7
5
9.7
26
5.7
5
Natural Language Annotation
9.6
15
6.7
6
9.7
15
7.2
6
9.6
17
5.8
6
Speech Annotation
9.6
15
5.3
5
9.5
14
5.7
5
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
Feature Not Available
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
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
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
Encord and Prolific are categorized as Data Labeling and Machine Learning
Unique Categories
Encord is categorized as Active Learning Tools, MLOps Platforms, Data Science and Machine Learning Platforms, and Image Recognition
Prolific is categorized as User Research and Crowd Testing Tools
Reviews
Reviewers' Company Size
Encord
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Prolific
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
Computer Software
37.5%
Hospital & Health Care
12.5%
Medical Devices
10.9%
Food & Beverages
9.4%
Information Technology and Services
7.8%
Other
21.9%
Research
40.5%
Higher Education
37.4%
Education Management
5.6%
Mental Health Care
1.5%
Marketing and Advertising
1.5%
Other
13.3%
Discussions
Encord has no discussions with answers
Prolific has no discussions with answers
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