Introducing G2.ai, the future of software buying.Try now
Compare Amazon Sagemaker Ground Truth and Encord 
Featured Products
Sponsored
You’re seeing this ad based on the product’s relevance to this page. Sponsored content does not receive preferential treatment in any of G2’s ratings.
Roboflow
Visit Website
At a Glance
Market Segments
Small-Business (36.8% of reviews)
Small-Business (50.8% of reviews)
Entry-Level Pricing
No pricing available
Contact Us
Amazon Sagemaker Ground Truth
Star Rating
(19)4.1 out of 5
Market Segments
Small-Business (36.8% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about Amazon Sagemaker Ground TruthEncord
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 EncordSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Amazon Sagemaker Ground Truth excels in its Quality of Support, with a score of 9.6, while Encord achieves a perfect score of 10.0, indicating that users find Encord's support to be exceptionally responsive and helpful.
- Reviewers mention that Encord offers a Free Trial, making it more accessible for small businesses looking to test the software before committing, whereas Amazon Sagemaker Ground Truth does not have a similar entry-level pricing option.
- G2 users highlight that Encord shines in Ease of Use with a score of 9.5, compared to Amazon Sagemaker Ground Truth's score of 8.3, suggesting that Encord provides a more intuitive user experience for data labeling tasks.
- Users on G2 report that Amazon Sagemaker Ground Truth has superior Scalability with a score of 9.8, which is crucial for businesses anticipating growth, while Encord's scalability score is slightly lower at 9.5.
- Reviewers mention that Encord's Model Training Efficiency is rated highly, with users appreciating its pre-built algorithms that streamline the model development process, while Amazon Sagemaker Ground Truth also offers strong model training capabilities but lacks the same level of user satisfaction in this area.
- Users say that Encord's Data Quality features, scoring 9.6, are particularly praised for their effectiveness in enhancing labeling accuracy, while Amazon Sagemaker Ground Truth, although strong, does not receive the same level of acclaim in this specific aspect.
Pricing
Entry-Level Pricing
Amazon Sagemaker Ground Truth
No pricing availableEncord
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
Free Trial
Amazon Sagemaker Ground Truth
No trial information availableEncord
Free Trial is available
Ratings
Meets Requirements
8.2
13
9.3
47
Ease of Use
8.3
13
9.5
48
Ease of Setup
7.3
10
8.3
12
Ease of Admin
8.2
11
7.7
11
Quality of Support
9.6
13
9.9
46
Has the product been a good partner in doing business?
8.5
10
9.4
11
Product Direction (% positive)
8.9
11
9.8
47
Features by Category
Deployment
Not enough data
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
Deployment
Not enough data
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
Management
Not enough data
9.8
7
Not enough data
9.8
8
Not enough data
10.0
6
Not enough data
9.8
8
Operations
Not enough data
10.0
6
Not enough data
9.7
6
Not enough data
10.0
9
Management
Not enough data
10.0
7
Not enough data
10.0
8
Not enough data
9.8
7
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
System
Not enough data
9.0
5
Model Development
Not enough data
Not enough data
Not enough data
9.7
6
Not enough data
10.0
5
Not enough data
9.7
6
Model Development
Not enough data
Not enough data
Machine/Deep Learning Services
Not enough data
9.5
7
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
9.7
5
Machine/Deep Learning Services
Not enough data
Not enough data
Not enough data
9.7
5
Deployment
Not enough data
10.0
7
Not enough data
9.8
7
Not enough data
9.5
7
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
Not enough data
9.4
32
Not enough data
9.8
31
Not enough data
9.5
32
Not enough data
9.8
30
Automation
Not enough data
9.5
26
Not enough data
9.5
25
Image Annotation
Not enough data
9.6
31
Not enough data
9.3
28
Not enough data
9.2
24
Not enough data
9.7
25
Natural Language Annotation
Not enough data
9.6
15
Not enough data
9.7
15
Not enough data
9.6
17
Speech Annotation
Not enough data
9.6
15
Not enough data
9.5
14
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
Feature Not Available
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
Amazon Sagemaker Ground Truth and Encord are categorized as Data Labeling
Unique Categories
Amazon Sagemaker Ground Truth has no unique categories
Encord is categorized as Active Learning Tools, MLOps Platforms, Data Science and Machine Learning Platforms, Image Recognition, and Machine Learning
Reviews
Reviewers' Company Size
Amazon Sagemaker Ground Truth
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Encord
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
26.3%
Computer Software
21.1%
Education Management
10.5%
Medical Practice
5.3%
Market Research
5.3%
Other
31.6%
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%
Discussions
Amazon Sagemaker Ground Truth has no discussions with answers
Encord has no discussions with answers
Hunting for software insights?
With over 3 million reviews, we can provide the specific details that help you make an informed software buying decision for your business. Finding the right product is important, let us help.
