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Compare JMP and Vertex AI 
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At a Glance
Market Segments
Enterprise (42.2% of reviews)
Small-Business (41.0% of reviews)
Entry-Level Pricing
$1,320.00 1 Users Per Year
Pay As You Go Per Month
JMP
Star Rating
(214)4.5 out of 5
Market Segments
Enterprise (42.2% of reviews)
Pros & Cons
Entry-Level Pricing
$1,320.00 1 Users Per Year
Free Trial is available
Browse all 2 pricing plansVertex AI
Star Rating
(592)4.3 out of 5
Market Segments
Small-Business (41.0% of reviews)
Pros & Cons
Entry-Level Pricing
Pay As You Go Per Month
Free Trial is available
Learn more about Vertex AIJMP vs Vertex AI
When assessing the two solutions, reviewers found JMP easier to use, set up, and administer. Reviewers also preferred doing business with JMP overall.
- Reviewers felt that JMP meets the needs of their business better than Vertex AI.
- When comparing quality of ongoing product support, reviewers felt that JMP is the preferred option.
- For feature updates and roadmaps, our reviewers preferred the direction of Vertex AI over JMP.
Pricing
Entry-Level Pricing
JMP
JMP
$1,320.00
1 Users Per Year
JMP for Windows or Mac.
Corporate licenses available at bulk discounts.
Key features include:
- Data Acquisition and Cleanup
- Design of Experiments
- Reliability Analysis
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
JMP
Free Trial is available
Vertex AI
Free Trial is available
Ratings
Meets Requirements
8.8
176
8.6
359
Ease of Use
8.3
177
8.2
368
Ease of Setup
8.6
53
8.1
291
Ease of Admin
8.6
28
7.9
141
Quality of Support
8.7
152
8.1
335
Has the product been a good partner in doing business?
8.9
29
8.2
135
Product Direction (% positive)
8.3
171
9.2
353
Features by Category
Reports
8.2
81
Not enough data
7.9
78
Not enough data
8.6
103
Not enough data
8.0
58
Not enough data
8.1
80
Not enough data
Self Service
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
Advanced Analytics
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Building Reports
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Platform
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
Reports
8.2
81
Not enough data
7.9
78
Not enough data
8.6
103
Not enough data
8.0
58
Not enough data
8.1
80
Not enough data
Reports
8.2
54
Not enough data
8.0
48
Not enough data
8.5
52
Not enough data
Generative AI
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Visualization
8.9
63
Not enough data
Feature Not Available
Not enough data
8.4
56
Not enough data
8.2
53
Not enough data
Data Updates
8.1
45
Not enough data
7.9
49
Not enough data
Collaboration
7.9
49
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Data Updates
7.9
45
Not enough data
Feature Not Available
Not enough data
8.1
42
Not enough data
Administration
8.7
92
Not enough data
8.8
95
Not enough data
8.1
77
Not enough data
Capabilities
9.0
107
Not enough data
8.7
73
Not enough data
8.2
74
Not enough data
8.0
65
Not enough data
Methodology
9.0
95
Not enough data
9.2
101
Not enough data
8.6
90
Not enough data
Generative AI
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Deployment
Not enough data
8.3
73
Not enough data
8.1
74
Not enough data
8.3
74
Not enough data
8.3
70
Not enough data
8.8
70
Deployment
Not enough data
8.4
73
Not enough data
8.3
72
Not enough data
8.4
71
Not enough data
8.5
71
Not enough data
8.7
69
Management
Not enough data
8.3
70
Not enough data
8.5
69
Not enough data
8.0
69
Not enough data
8.1
69
Operations
Not enough data
8.2
69
Not enough data
8.4
70
Not enough data
8.3
70
Management
Not enough data
8.1
68
Not enough data
8.4
69
Not enough data
8.3
68
Generative AI
Not enough data
8.2
34
Not enough data
8.4
34
System
Not enough data
8.2
170
Model Development
Not enough data
8.4
202
Not enough data
7.9
179
Not enough data
8.4
200
Not enough data
8.5
202
Model Development
Not enough data
8.2
165
Machine/Deep Learning Services
Not enough data
8.2
200
Not enough data
8.4
196
Not enough data
8.2
195
Not enough data
8.2
178
Machine/Deep Learning Services
Not enough data
8.5
165
Not enough data
8.4
163
Deployment
Not enough data
8.2
193
Not enough data
8.3
194
Not enough data
8.5
193
Generative AI
Not enough data
8.3
102
Not enough data
8.2
102
Not enough data
8.1
103
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
8.1
34
Not enough data
7.8
34
Not enough data
7.7
34
Not enough data
7.8
34
Not enough data
8.4
34
Not enough data
7.8
34
Not enough data
7.9
34
Scalability and Performance - Generative AI Infrastructure
Not enough data
8.9
28
Not enough data
8.6
28
Not enough data
8.5
28
Cost and Efficiency - Generative AI Infrastructure
Not enough data
8.2
28
Not enough data
7.8
28
Not enough data
7.9
28
Integration and Extensibility - Generative AI Infrastructure
Not enough data
8.4
28
Not enough data
8.1
28
Not enough data
8.3
28
Security and Compliance - Generative AI Infrastructure
Not enough data
8.6
28
Not enough data
8.5
28
Not enough data
8.9
28
Usability and Support - Generative AI Infrastructure
Not enough data
8.2
28
Not enough data
8.3
28
Integration - Machine Learning
Not enough data
8.5
67
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
23
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
22
Not enough data
8.9
22
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
22
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
9.2
22
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
22
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
9.2
22
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
22
Not enough data
8.7
21
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
21
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
8.0
27
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
Statistical Tool
8.7
23
Not enough data
9.0
27
Not enough data
8.7
25
Not enough data
Data Analysis
9.3
28
Not enough data
9.1
29
Not enough data
Decision Making
8.8
26
Not enough data
9.4
29
Not enough data
8.5
28
Not enough data
9.1
23
Not enough data
Generative AI
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Categories
Categories
Shared Categories
JMP and Vertex AI share no categories
Unique Categories
Reviews
Reviewers' Company Size
JMP
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
Higher Education
12.6%
Information Technology and Services
9.7%
Research
9.2%
Pharmaceuticals
6.8%
Semiconductors
5.8%
Other
55.8%
Computer Software
17.5%
Information Technology and Services
13.9%
Financial Services
7.0%
Retail
3.8%
Hospital & Health Care
3.4%
Other
54.4%
Alternatives
Discussions
Who uses JMP?
3 Comments
FF
Statisticians, Data Scientists, Engineers, Statistics Teachers.Read more
Is there a free/trial version of JMP that i can utilize during my facilitation in a training?
1 Comment
WL
JMP has a trial version - go to JMP.com and you'll see something about a trial in the upper-right.
They also have a free course called Statistical...Read more
How can PhD Student learn uses of JMP pro for research purpose?
1 Comment
WL
They have a free course called Statistical Thinking for Industrial Problem Solving - that provides JMP - but only works with the data in the course. I'm not...Read more
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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