Compare Gemini Enterprise Agent Platform and SuperAnnotate 
Featured Products
At a Glance
Market Segments
Small-Business (42.3% of reviews)
Small-Business (61.2% of reviews)
Entry-Level Pricing
Pay As You Go Per Month
Contact Us
Gemini Enterprise Agent Platform
Star Rating
(653)4.3 out of 5
Market Segments
Small-Business (42.3% of reviews)
Pros & Cons
Entry-Level Pricing
Pay As You Go Per Month
Learn more about Gemini Enterprise Agent PlatformSuperAnnotate
Star Rating
(283)4.9 out of 5
Market Segments
Small-Business (61.2% of reviews)
Pros & Cons
Entry-Level Pricing
Contact Us
Browse all 3 pricing plansSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Vertex AI excels in providing a comprehensive solution for the entire machine learning lifecycle, with features like data preparation, model training, and deployment all integrated into one platform. Users appreciate the ability to experiment with different models, such as Gemini 3 for complex tasks and Nano Banana for image editing, making it a versatile choice for various needs.
- Users say that SuperAnnotate stands out for its exceptional customer support, with many highlighting the quick and effective assistance they received when facing issues. This level of support has been a significant factor in their overall satisfaction, as users feel valued and supported throughout their experience.
- Reviewers mention that while Vertex AI has a higher overall satisfaction score, SuperAnnotate boasts a slightly better star rating, indicating that users find it easier to use and set up. This ease of use is particularly beneficial for teams looking to get started quickly without extensive training.
- According to verified reviews, SuperAnnotate's AI-powered automation tools, such as smart polygon and auto-annotate, have significantly reduced manual labeling time, making it a powerful tool for data labeling tasks. Users appreciate how these features streamline their workflows and enhance productivity.
- G2 reviewers highlight that Vertex AI's recent updates, including the introduction of a playground for testing models, have made it easier for users to experiment without coding. This feature has been particularly praised for helping users understand model behavior and optimize their inputs effectively.
- Users report that while both platforms have strong capabilities, Vertex AI's higher G2 Score reflects its robust feature set and overall user satisfaction. However, SuperAnnotate's focus on customer support and ease of use makes it a compelling option for teams prioritizing quick implementation and assistance.
Pricing
Entry-Level Pricing
Gemini Enterprise Agent Platform
Try Vertex AI Free
Pay As You Go
Per Month
New customers get $300 in free credits to spend on Vertex AI.
- A unified UI for the entire ML workflow
- Pre-trained APIs for vision, video, natural language, and more
- End-to-end integration for data and AI
SuperAnnotate
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
Gemini Enterprise Agent Platform
No trial information availableSuperAnnotate
Free Trial is available
Ratings
Meets Requirements
8.6
388
9.5
166
Ease of Use
8.1
399
9.5
172
Ease of Setup
8.1
321
9.4
130
Ease of Admin
7.9
150
9.6
51
Quality of Support
8.1
364
9.5
164
Has the product been a good partner in doing business?
8.3
144
9.7
52
Product Direction (% positive)
9.2
382
9.7
151
Features by Category
Deployment
8.4
76
9.7
12
8.1
78
9.3
12
8.3
76
9.3
10
8.4
76
9.6
12
8.8
75
9.5
11
Deployment
8.5
75
9.4
13
8.3
73
9.6
13
8.4
72
9.4
12
8.6
74
9.4
12
8.7
71
9.4
13
Management
8.2
71
9.3
10
8.5
73
9.0
12
8.0
71
9.3
9
8.1
70
9.6
9
Operations
8.2
70
9.3
10
8.5
71
9.3
9
8.3
71
9.4
11
Management
8.1
69
9.6
9
8.4
72
9.4
9
8.3
70
9.4
8
Generative AI
8.4
37
9.2
6
8.6
37
9.0
5
System
8.2
170
Not enough data
Model Development
8.5
206
Not enough data
7.8
179
Not enough data
8.4
204
Not enough data
8.5
206
Not enough data
Model Development
8.2
164
Not enough data
Machine/Deep Learning Services
8.3
201
Not enough data
8.5
200
Not enough data
8.2
197
Not enough data
8.2
178
Not enough data
Machine/Deep Learning Services
8.5
164
Not enough data
8.5
163
Not enough data
Deployment
8.3
210
Not enough data
8.3
200
Not enough data
8.6
205
Not enough data
Generative AI
8.3
106
Not enough data
8.3
103
Not enough data
8.2
103
Not enough data
Agentic AI - Data Science and Machine Learning Platforms
8.0
35
Not enough data
7.8
34
Not enough data
7.6
36
Not enough data
7.8
32
Not enough data
8.4
34
Not enough data
7.4
33
Not enough data
7.6
33
Not enough data
Quality
Not enough data
9.6
90
Not enough data
9.6
104
Not enough data
9.7
86
Not enough data
9.7
95
Automation
Not enough data
9.3
68
Not enough data
9.6
54
Image Annotation
Not enough data
9.3
81
Not enough data
9.4
75
Not enough data
9.3
66
Not enough data
9.6
69
Natural Language Annotation
Not enough data
9.4
53
Not enough data
9.2
44
Not enough data
9.6
48
Speech Annotation
Not enough data
9.3
48
Not enough data
9.1
43
Scalability and Performance - Generative AI Infrastructure
9.0
31
Not enough data
8.7
32
Not enough data
8.6
31
Not enough data
Cost and Efficiency - Generative AI Infrastructure
8.0
34
Not enough data
7.7
31
Not enough data
8.1
30
Not enough data
Integration and Extensibility - Generative AI Infrastructure
8.5
30
Not enough data
8.3
32
Not enough data
8.5
31
Not enough data
Security and Compliance - Generative AI Infrastructure
8.7
30
Not enough data
8.3
32
Not enough data
8.9
30
Not enough data
Usability and Support - Generative AI Infrastructure
8.2
31
Not enough data
8.5
31
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
8.5
66
Not enough data
Learning - Machine Learning
8.5
64
Not enough data
8.3
63
Not enough data
8.8
64
Not enough data
Prompt Engineering - Large Language Model Operationalization (LLMOps)
8.8
24
9.7
16
9.0
24
9.7
15
Inference Optimization - Large Language Model Operationalization (LLMOps)
8.8
22
9.5
13
Model Garden - Large Language Model Operationalization (LLMOps)
9.3
25
9.7
15
Custom Training - Large Language Model Operationalization (LLMOps)
9.1
24
9.6
16
Application Development - Large Language Model Operationalization (LLMOps)
9.2
23
9.4
15
Model Deployment - Large Language Model Operationalization (LLMOps)
9.0
23
9.6
12
8.7
22
9.4
14
Guardrails - Large Language Model Operationalization (LLMOps)
8.7
23
9.6
16
8.9
22
9.7
15
Model Monitoring - Large Language Model Operationalization (LLMOps)
8.7
21
9.5
14
9.1
22
9.6
13
Security - Large Language Model Operationalization (LLMOps)
9.1
22
9.6
12
9.0
23
9.5
13
Gateways & Routers - Large Language Model Operationalization (LLMOps)
8.9
22
9.5
13
Customization - AI Agent Builders
8.6
28
Not enough data
7.6
27
Not enough data
8.3
26
Not enough data
Functionality - AI Agent Builders
8.1
27
Not enough data
7.3
27
Not enough data
8.2
26
Not enough data
7.2
27
Not enough data
Data and Analytics - AI Agent Builders
7.8
26
Not enough data
7.9
27
Not enough data
8.1
28
Not enough data
Integration - AI Agent Builders
8.8
28
Not enough data
8.2
30
Not enough data
8.1
28
Not enough data
7.5
27
Not enough data
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
Gemini Enterprise Agent Platform and SuperAnnotate are categorized as Large Language Model Operationalization (LLMOps) and MLOps Platforms
Unique Categories
Gemini Enterprise Agent Platform is categorized as Generative AI Infrastructure, Data Science and Machine Learning Platforms, Machine Learning, AI Agent Builders, and Low-Code Machine Learning Platforms
SuperAnnotate is categorized as Data Labeling and Active Learning Tools
Reviews
Reviewers' Company Size
Gemini Enterprise Agent Platform
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
Computer Software
17.6%
Information Technology and Services
14.2%
Financial Services
6.9%
Retail
3.6%
Hospital & Health Care
3.4%
Other
54.3%
Information Technology and Services
24.4%
Computer Software
15.0%
Research
5.2%
Higher Education
3.8%
Computer & Network Security
3.3%
Other
48.4%
Alternatives
Discussions
What is Google Cloud AI Platform used for?
3 Comments
KS
Google cloud AI Platform enables us to build Machine learning models, that works on any type and any size of data. Read more
What software libraries does cloud ML engine support?
3 Comments
SA
Google Cloud ML Engine supports many software libraries, including TensorFlow, scikit-learn, XGBoost, Keras, etc....Read more
What is Google AI platform?
2 Comments
ZM
The Google AI Platform is a comprehensive set of tools and services provided by Google Cloud to develop, deploy, and manage artificial intelligence. It...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
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
SuperAnnotate has no more 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.
Your software and services insights are valuable.
Your peers come to G2 to get an inside look at and other business solutions. Adding perspective on will help others pick the right solution based on real user experience.
