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Compare RapidCanvas and Vertex AI 
Featured Products
At a Glance
Market Segments
Small-Business (50.0% of reviews)
Small-Business (41.2% of reviews)
Entry-Level Pricing
Contact Us Per Month
Pay As You Go Per Month
RapidCanvas
Star Rating
(35)4.8 out of 5
Market Segments
Small-Business (50.0% of reviews)
Pros & Cons
Entry-Level Pricing
Contact Us Per Month
Learn more about RapidCanvasVertex AI
Star Rating
(638)4.3 out of 5
Market Segments
Small-Business (41.2% of reviews)
Pros & Cons
Entry-Level Pricing
Pay As You Go Per Month
Free Trial is available
Learn more about Vertex AISummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Vertex AI excels in managing complex machine learning workflows, with users appreciating its ability to centralize the entire ML lifecycle. One user highlighted how it simplifies everything from data preparation to deployment, making it a powerful tool for those looking to streamline their processes.
- Users say RapidCanvas stands out for its collaborative features, particularly in brainstorming and project planning. Reviewers noted that it helps teams organize ideas visually, turning discussions into actionable steps, which is especially beneficial for remote teams seeking clarity and coordination.
- According to verified reviews, Vertex AI has a significantly higher overall satisfaction score, indicating that users feel more positively about their experience with the platform. This is reflected in the feedback praising its seamless integration with Google Cloud, which enhances the user experience.
- Reviewers mention that RapidCanvas offers an intuitive drag-and-drop interface, making data visualization accessible without requiring advanced technical skills. Users appreciate how quickly they can turn raw data into interactive dashboards, which is a major plus for teams needing to visualize data efficiently.
- G2 reviewers highlight that while Vertex AI has a robust feature set for model training and deployment, some users find it challenging to match their specific workflow needs, indicating potential configuration hurdles. This contrasts with RapidCanvas, where users report a smoother setup experience and supportive engagement during the initial project phases.
- Users report that RapidCanvas provides excellent support, with high ratings for quality and responsiveness. This level of support is crucial for teams that may need assistance during their project setup, making it a favorable choice for those prioritizing customer service.
Pricing
Entry-Level Pricing
RapidCanvas
Pricing
Contact Us
Per Month
The Best Agentic AI Platform.
Driven to deliver mission critical business outcomes.
- Solution delivery within four weeks
- Built by world's top data scientists
- Guided by experienced network of SMEs
Vertex AI
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
Free Trial
RapidCanvas
Free Trial is available
Vertex AI
Free Trial is available
Ratings
Meets Requirements
9.1
30
8.6
381
Ease of Use
8.7
31
8.2
392
Ease of Setup
9.1
22
8.1
315
Ease of Admin
9.3
15
7.9
147
Quality of Support
9.6
31
8.1
356
Has the product been a good partner in doing business?
9.8
15
8.3
141
Product Direction (% positive)
9.6
29
9.2
375
Features by Category
Deployment
Not enough data
8.4
76
Not enough data
8.1
77
Not enough data
8.3
76
Not enough data
8.4
76
Not enough data
8.8
74
Deployment
Not enough data
8.5
75
Not enough data
8.3
73
Not enough data
8.4
72
Not enough data
8.6
74
Not enough data
8.7
71
Management
Not enough data
8.2
71
Not enough data
8.5
72
Not enough data
8.0
71
Not enough data
8.1
70
Operations
Not enough data
8.2
70
Not enough data
8.5
71
Not enough data
8.3
71
Management
Not enough data
8.1
69
Not enough data
8.4
72
Not enough data
8.3
70
Generative AI
Not enough data
8.3
36
Not enough data
8.5
36
System
8.9
22
8.2
172
Model Development
8.4
23
8.4
205
8.9
24
7.9
180
8.8
24
8.4
203
9.1
24
8.5
208
Model Development
9.0
21
8.2
166
Machine/Deep Learning Services
7.8
23
8.2
202
8.6
22
8.5
200
8.6
22
8.2
197
9.4
21
8.2
179
Machine/Deep Learning Services
8.5
20
8.5
166
8.8
20
8.4
163
Deployment
9.3
20
8.3
207
9.4
18
8.3
198
9.6
19
8.5
202
Generative AI
8.3
20
8.3
107
8.4
19
8.3
104
7.5
19
8.1
104
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
8.1
36
Not enough data
7.8
36
Not enough data
7.7
37
Not enough data
7.8
34
Not enough data
8.4
36
Not enough data
7.5
35
Not enough data
7.6
35
Scalability and Performance - Generative AI Infrastructure
Not enough data
9.0
30
Not enough data
8.6
30
Not enough data
8.6
30
Cost and Efficiency - Generative AI Infrastructure
Not enough data
8.0
33
Not enough data
7.7
30
Not enough data
8.0
29
Integration and Extensibility - Generative AI Infrastructure
Not enough data
8.4
29
Not enough data
8.2
30
Not enough data
8.4
29
Security and Compliance - Generative AI Infrastructure
Not enough data
8.7
29
Not enough data
8.4
30
Not enough data
8.9
29
Usability and Support - Generative AI Infrastructure
Not enough data
8.1
30
Not enough data
8.4
30
Integration - Machine Learning
Not enough data
8.5
68
Learning - Machine Learning
Not enough data
8.5
66
Not enough data
8.3
65
Not enough data
8.8
66
Large Language Model Operationalization (LLMOps)Hide 15 FeaturesShow 15 Features
Not enough data
8.9
26
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
23
Not enough data
8.9
23
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
22
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
9.3
24
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
23
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
9.2
22
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
23
Not enough data
8.7
21
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
8.6
22
Not enough data
8.8
21
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
8.7
21
Not enough data
9.0
21
Security - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
22
Not enough data
8.9
22
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
8.9
22
Customization - AI Agent Builders
Not enough data
8.5
27
Not enough data
7.6
27
Not enough data
8.3
26
Functionality - AI Agent Builders
Not enough data
8.1
27
Not enough data
7.3
27
Not enough data
8.2
26
Not enough data
7.2
27
Data and Analytics - AI Agent Builders
Not enough data
7.7
25
Not enough data
7.9
27
Not enough data
8.0
27
Integration - AI Agent Builders
Not enough data
8.7
27
Not enough data
8.1
28
Not enough data
8.0
27
Not enough data
7.5
27
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
RapidCanvas and Vertex AI are categorized as Data Science and Machine Learning Platforms
Unique Categories
RapidCanvas has no unique categories
Vertex AI is categorized as Large Language Model Operationalization (LLMOps), Generative AI Infrastructure, MLOps Platforms, Machine Learning, AI Agent Builders, and Low-Code Machine Learning Platforms
Reviews
Reviewers' Company Size
RapidCanvas
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Vertex 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
15.6%
Information Technology and Services
12.5%
Financial Services
9.4%
Transportation/Trucking/Railroad
6.3%
Research
6.3%
Other
50.0%
Computer Software
17.8%
Information Technology and Services
14.3%
Financial Services
6.8%
Retail
3.6%
Hospital & Health Care
3.3%
Other
54.2%
Alternatives
Discussions
RapidCanvas has no discussions with answers
What is Google Cloud AI Platform used for?
2 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?
2 Comments
JP
It's supporting approx all trending libraries.Read more
What is Google AI platform?
1 Comment
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
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