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Compare Azure Machine Learning and SuperAnnotate 
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At a Glance
Market Segments
Enterprise (38.8% of reviews)
Small-Business (63.5% of reviews)
Entry-Level Pricing
No pricing available
Contact Us
Azure Machine Learning
Star Rating
(88)4.3 out of 5
Market Segments
Enterprise (38.8% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Azure Machine LearningSuperAnnotate
Star Rating
(172)4.9 out of 5
Market Segments
Small-Business (63.5% of reviews)
Entry-Level Pricing
Contact Us
Browse all 3 pricing plansSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Azure Machine Learning offers robust integration with other Microsoft services, which is beneficial for enterprises already using the Microsoft ecosystem, while SuperAnnotate shines with its user-friendly interface and intuitive annotation tools, making it a favorite among small businesses.
- Reviewers mention that Azure Machine Learning has a steeper learning curve, particularly when utilizing advanced features like automated machine learning, whereas SuperAnnotate is praised for its ease of use, especially with features like collaborative annotation and real-time feedback.
- G2 users highlight that Azure Machine Learning's support is reliable but can be slow at times, while SuperAnnotate users rave about the quality of support, noting quick response times and helpful resources that enhance their experience.
- Users on G2 report that Azure Machine Learning meets requirements well, particularly for complex enterprise-level projects, but SuperAnnotate excels in meeting the needs of small businesses with its flexible pricing and free trial, allowing users to test features before committing.
- Reviewers say that Azure Machine Learning's setup process can be cumbersome, especially for those unfamiliar with cloud services, while SuperAnnotate is noted for its straightforward setup, allowing users to get started quickly with minimal hassle.
- Users mention that while Azure Machine Learning has a solid product direction, SuperAnnotate's commitment to continuous improvement and user feedback is evident, with frequent updates that enhance functionality and user experience.
Pricing
Entry-Level Pricing
Azure Machine Learning
No pricing availableSuperAnnotate
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
Azure Machine Learning
No trial information availableSuperAnnotate
Free Trial is available
Ratings
Meets Requirements
8.5
81
9.6
113
Ease of Use
8.5
80
9.6
118
Ease of Setup
8.3
57
9.6
78
Ease of Admin
8.3
49
9.6
46
Quality of Support
8.6
74
9.7
115
Has the product been a good partner in doing business?
8.6
47
9.7
47
Product Direction (% positive)
9.0
80
9.5
99
Features by Category
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
System
8.6
22
Not enough data
Model Development
8.6
51
Not enough data
8.9
54
Not enough data
8.3
53
Not enough data
8.7
52
Not enough data
Model Development
8.4
21
Not enough data
Machine/Deep Learning Services
8.1
45
Not enough data
7.9
45
Not enough data
7.8
38
Not enough data
8.2
42
Not enough data
Machine/Deep Learning Services
8.7
21
Not enough data
8.5
21
Not enough data
Deployment
8.8
50
Not enough data
8.7
51
Not enough data
8.9
51
Not enough data
Generative AI
8.5
10
Not enough data
8.2
10
Not enough data
7.5
10
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
9.7
76
Not enough data
9.6
74
Not enough data
9.7
74
Not enough data
9.7
68
Automation
Not enough data
9.3
57
Not enough data
9.5
47
Image Annotation
Not enough data
9.3
70
Not enough data
9.4
67
Not enough data
9.3
59
Not enough data
9.5
61
Natural Language Annotation
Not enough data
9.3
46
Not enough data
9.2
39
Not enough data
9.6
43
Speech Annotation
Not enough data
9.2
40
Not enough data
9.0
38
Scalability and Performance - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Cost and Efficiency - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration and Extensibility - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Security and Compliance - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Usability and Support - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Large Language Model Operationalization (LLMOps)Hide 15 FeaturesShow 15 Features
Not enough data
9.5
13
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
Data Ingestion & Preparation - Low-Code Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Model Construction & Automation - Low-Code Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Azure Machine Learning and SuperAnnotate are categorized as MLOps Platforms and Large Language Model Operationalization (LLMOps)
Unique Categories
Azure Machine Learning is categorized as Data Science and Machine Learning Platforms, Generative AI Infrastructure, and Low-Code Machine Learning Platforms
SuperAnnotate is categorized as Data Labeling
Reviews
Reviewers' Company Size
Azure Machine Learning
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
28.2%
Computer Software
14.1%
Management Consulting
8.2%
Education Management
5.9%
Higher Education
4.7%
Other
38.8%
Information Technology and Services
22.6%
Computer Software
16.4%
Research
6.9%
Higher Education
5.0%
Health, Wellness and Fitness
3.8%
Other
45.3%
Discussions
What is Azure Machine Learning Studio used for?
1 Comment
AR
In short, to build, deploy, and manage high-quality models faster and with confidence.Read more
Azure Machine Learning has no more 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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