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Compare Encord and Segments.ai 
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At a Glance
Market Segments
Small-Business (50.8% of reviews)
Small-Business (95.2% of reviews)
Entry-Level Pricing
Contact Us
Free Trial Per Year
Encord
Star Rating
(62)4.8 out of 5
Market Segments
Small-Business (50.8% of reviews)
Pros & Cons
Entry-Level Pricing
Contact Us
Learn more about EncordSegments.ai
Star Rating
(21)4.6 out of 5
Market Segments
Small-Business (95.2% of reviews)
Pros & Cons
Entry-Level Pricing
Free Trial Per Year
Browse all 4 pricing plansSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Encord excels in Labeler Quality with a score of 9.5, while Segments.ai falls behind at 8.8. Reviewers mention that Encord's labeling tools are intuitive and produce high-quality annotations, making it a preferred choice for teams focused on accuracy.
- Reviewers mention that Encord's Quality of Support is exceptional, scoring a perfect 10.0, compared to Segments.ai's 9.2. Users on G2 appreciate the responsiveness and helpfulness of Encord's support team, which significantly enhances the user experience.
- G2 users highlight that Encord offers superior Model Training Efficiency with a score of 9.7, while Segments.ai's performance in this area is less impressive. Users report that Encord's automated model retraining features streamline the workflow, making it easier to maintain high model performance.
- Users say that Encord's Human-in-the-Loop feature is rated at 9.8, significantly higher than Segments.ai's 8.1. Reviewers mention that this feature allows for better oversight and quality control during the annotation process, which is crucial for complex projects.
- Reviewers mention that Encord's Data Quality score of 9.6 is a standout feature, while Segments.ai's score of 8.6 indicates room for improvement. Users appreciate Encord's robust data management tools that ensure high-quality datasets for training models.
- Users on G2 report that Encord's Automation capabilities, particularly in Machine Learning Pre-Labeling, score 9.7, compared to Segments.ai's 8.1. Reviewers say that this automation significantly reduces the time spent on manual labeling, making Encord a more efficient choice for teams with large datasets.
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
Segments.ai
Free trial
Free Trial
Per Year
- Unlimited seats
- API & SDK Access
- Unlimited image, point cloud and sequence interfaces
Free Trial
Encord
Free Trial is available
Segments.ai
Free Trial is available
Ratings
Meets Requirements
9.3
47
9.0
21
Ease of Use
9.5
48
8.6
21
Ease of Setup
8.3
12
9.2
8
Ease of Admin
7.7
11
Not enough data
Quality of Support
9.9
46
9.2
18
Has the product been a good partner in doing business?
9.4
11
Not enough data
Product Direction (% positive)
9.8
47
10.0
20
Features by Category
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
32
8.9
15
9.8
31
8.7
14
9.5
32
8.7
14
9.8
30
8.3
12
Automation
9.5
26
8.3
11
9.5
25
Feature Not Available
Image Annotation
9.6
31
9.1
15
9.3
28
8.3
14
9.2
24
8.0
11
9.7
25
8.0
11
Natural Language Annotation
9.6
15
Feature Not Available
9.7
15
7.3
10
9.6
17
Feature Not Available
Speech Annotation
9.6
15
Feature Not Available
9.5
14
Feature Not Available
Recognition Type
Not enough data
Feature Not Available
Not enough data
8.7
5
Not enough data
7.7
5
Not enough data
7.7
5
Feature Not Available
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
8.0
5
Facial Recognition
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Labeling
Not enough data
8.7
5
Not enough data
8.3
5
Not enough data
8.7
5
Deployment
Not enough data
7.7
5
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 Segments.ai are categorized as Data Labeling, MLOps Platforms, and Image Recognition
Unique Categories
Encord is categorized as Active Learning Tools, Data Science and Machine Learning Platforms, and Machine Learning
Segments.ai has no unique categories
Reviews
Reviewers' Company Size
Encord
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Segments.ai
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
36.1%
Medical Devices
11.5%
Hospital & Health Care
11.5%
Food & Beverages
9.8%
Information Technology and Services
8.2%
Other
23.0%
Research
33.3%
Computer Software
19.0%
Automotive
9.5%
Information Technology and Services
4.8%
Higher Education
4.8%
Other
28.6%
Alternatives
Discussions
Encord has no discussions with answers
Segments.ai has no discussions with answers
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