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Compare IBM Decision Optimization and Vertex AI 
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At a Glance
Market Segments
Enterprise (60.0% of reviews)
Small-Business (41.0% of reviews)
Entry-Level Pricing
Free
Pay As You Go Per Month
IBM Decision Optimization
Star Rating
(41)4.5 out of 5
Market Segments
Enterprise (60.0% of reviews)
Entry-Level Pricing
Free
Browse all 2 pricing plansVertex AI
Star Rating
(593)4.3 out of 5
Market Segments
Small-Business (41.0% of reviews)
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.
- Users report that Vertex AI excels in AI High Availability with a score of 9.2, which reviewers mention significantly enhances their operational reliability compared to IBM Decision Optimization's lower performance in this area.
- Reviewers mention that Vertex AI's AI Model Training Scalability, rated at 8.5, allows for more efficient handling of large datasets, while IBM Decision Optimization's score of 7.4 indicates challenges in scaling model training effectively.
- G2 users highlight that Vertex AI's integration capabilities, particularly with AI Data Pipeline Integration rated at 8.2, provide a smoother workflow, whereas IBM Decision Optimization's integration features are perceived as less flexible, scoring 7.2 in Data Ingestion & Wrangling.
- Users on G2 report that Vertex AI's pre-built algorithms, rated at 8.4, offer a robust starting point for model development, while IBM Decision Optimization's score of 8.0 suggests it may not provide as comprehensive a library for users looking to jumpstart their projects.
- Reviewers mention that Vertex AI's AI Cost per API Call, rated at 8.0, is more favorable for budget-conscious users, while IBM Decision Optimization's lower score of 7.9 indicates potential cost concerns for users scaling their operations.
- Users say that Vertex AI's documentation quality, rated at 8.5, is superior, making it easier for teams to onboard and utilize the platform effectively, while IBM Decision Optimization's documentation, although decent, does not match the clarity and comprehensiveness of Vertex AI's resources.
Pricing
Entry-Level Pricing
IBM Decision Optimization
IBM ILOG CPLEX Optimization Studio Free edition
Free
Explore and learn optimization and constraint programming modeling with our free edition. Try free edition:
https://www.ibm.com/account/reg/signup?formid=urx-20028
- Limited to 1000 variables and 1000 constraints, but models can be edited
- Use both the OPL/IDE and API modeling/solving
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
IBM Decision Optimization
Free Trial is available
Vertex AI
Free Trial is available
Ratings
Meets Requirements
8.4
30
8.6
359
Ease of Use
8.7
30
8.2
368
Ease of Setup
8.3
14
8.1
291
Ease of Admin
8.7
14
7.9
142
Quality of Support
8.6
30
8.1
335
Has the product been a good partner in doing business?
9.2
14
8.2
136
Product Direction (% positive)
8.0
29
9.2
353
Features by Category
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
7.2
9
8.2
170
Model Development
7.9
7
8.5
202
8.3
7
7.9
179
8.3
7
8.4
200
7.4
7
8.5
202
Model Development
7.4
9
8.3
165
Machine/Deep Learning Services
7.9
7
8.2
200
7.4
7
8.4
196
6.9
7
8.2
195
6.9
7
8.2
178
Machine/Deep Learning Services
7.3
8
8.5
165
7.5
8
8.5
163
Deployment
8.3
7
8.2
193
8.1
7
8.3
194
7.6
7
8.5
193
Generative AI
Not enough data
8.3
102
Not enough data
8.3
102
Not enough data
8.1
103
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
8.1
34
Not enough data
7.9
34
Not enough data
7.7
34
Not enough data
7.9
34
Not enough data
8.5
34
Not enough data
7.8
34
Not enough data
8.0
34
Integration
Not enough data
Not enough data
Not enough data
Not enough data
Business Logic
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Analytics
Not enough data
Not enough data
Not enough data
Not enough data
Deployment
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Decision Management 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
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
9.0
23
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
23
Not enough data
9.0
23
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
23
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
9.3
23
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
9.1
23
Not enough data
8.7
22
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
22
Not enough data
8.9
22
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
22
Not enough data
9.1
22
Security - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
23
Not enough data
9.0
23
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
8.9
23
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
Categories
Categories
Shared Categories
IBM Decision Optimization and Vertex AI are categorized as Data Science and Machine Learning Platforms
Unique Categories
IBM Decision Optimization is categorized as Decision Management Platforms
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
IBM Decision Optimization
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
Financial Services
14.3%
Education Management
11.4%
Computer Software
11.4%
Transportation/Trucking/Railroad
5.7%
Research
5.7%
Other
51.4%
Computer Software
17.7%
Information Technology and Services
13.9%
Financial Services
7.0%
Retail
3.8%
Hospital & Health Care
3.4%
Other
54.2%
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