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- IBM Decision Optimization-vs-Vertex AI
Compare IBM Decision Optimization and Vertex AI 
At a Glance
Market Segments
Enterprise (60.0% of reviews)
Small-Business (38.4% 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
(512)4.3 out of 5
Market Segments
Small-Business (38.4% 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 Model Training Scalability with a score of 8.5, allowing for efficient handling of large datasets, while IBM Decision Optimization scores lower at 7.4, indicating potential limitations in scaling model training.
- Reviewers mention that Vertex AI's AI Inference Speed is rated at 8.6, which contributes to faster decision-making processes, whereas IBM Decision Optimization's performance in this area is not as strong, reflecting a need for improvement in inference capabilities.
- G2 users highlight that Vertex AI offers superior Data Ingestion & Wrangling features with a score of 8.3, making it easier to prepare data for analysis, while IBM Decision Optimization's score of 7.2 suggests it may not be as user-friendly in this aspect.
- Users on G2 appreciate Vertex AI's comprehensive support for Natural Language Processing, scoring 8.6, which enhances its usability for text-based applications, compared to IBM Decision Optimization's lower score of 7.4 in the same category.
- Reviewers say that Vertex AI's AI Data Encryption feature is rated highly at 9.2, ensuring robust security measures, while IBM Decision Optimization's security features, although decent, do not match this level of assurance, indicating a potential gap in data protection.
- Users report that Vertex AI's documentation quality is rated at 8.5, which aids in user onboarding and troubleshooting, while IBM Decision Optimization's documentation, although helpful, does not receive the same level of praise, suggesting room for improvement in user support resources.
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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
286
Ease of Use
8.7
30
8.2
293
Ease of Setup
8.3
14
8.1
215
Ease of Admin
8.7
14
7.9
121
Quality of Support
8.6
30
8.1
267
Has the product been a good partner in doing business?
9.2
14
8.1
116
Product Direction (% positive)
8.0
29
9.1
279
Features by Category
Deployment
Not enough data
8.4
59
Not enough data
8.4
60
Not enough data
8.4
60
Not enough data
8.4
56
Not enough data
8.8
56
Deployment
Not enough data
8.6
60
Not enough data
8.4
59
Not enough data
8.4
58
Not enough data
8.6
58
Not enough data
8.8
56
Management
Not enough data
8.4
56
Not enough data
8.5
55
Not enough data
8.2
56
Not enough data
8.2
56
Operations
Not enough data
8.3
56
Not enough data
8.6
57
Not enough data
8.5
57
Management
Not enough data
8.3
55
Not enough data
8.5
56
Not enough data
8.4
55
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
System
7.2
9
8.2
111
8.0
9
8.2
113
7.8
9
7.9
108
Model Development
7.9
7
8.4
139
8.3
7
7.8
116
8.3
7
8.4
137
7.4
7
8.4
140
Model Development
8.0
9
8.4
106
7.8
9
8.3
110
7.4
9
8.4
106
Machine/Deep Learning Services
7.9
7
8.3
138
7.4
7
8.6
134
6.9
7
8.3
133
6.9
7
8.3
116
Machine/Deep Learning Services
7.7
8
8.4
109
7.3
8
8.6
106
8.1
8
8.4
104
7.5
8
8.4
105
Deployment
8.3
7
8.2
132
8.1
7
8.3
133
7.6
7
8.5
132
Deployment
8.3
7
8.3
105
8.3
7
8.3
105
8.8
7
8.4
106
Generative AI
Feature Not Available
Feature Not Available
Feature Not Available
Feature Not Available
Feature Not Available
Feature Not Available
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
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Scalability and Performance - Generative AI Infrastructure
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Cost and Efficiency - Generative AI Infrastructure
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Integration and Extensibility - Generative AI Infrastructure
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Security and Compliance - Generative AI Infrastructure
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Usability and Support - Generative AI Infrastructure
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Integration - Machine Learning
Not enough data
8.4
33
Learning - Machine Learning
Not enough data
8.5
33
Not enough data
8.6
33
Not enough data
8.9
33
Large Language Model Operationalization (LLMOps)Hide 15 FeaturesShow 15 Features
Not enough data
9.5
101
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
9.3
7
Not enough data
9.3
7
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
7
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
9.3
7
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
9.5
7
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
9.8
7
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
9.8
7
Not enough data
9.5
7
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
9.4
6
Not enough data
9.4
6
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
9.7
6
Not enough data
9.7
6
Security - Large Language Model Operationalization (LLMOps)
Not enough data
9.8
7
Not enough data
9.3
7
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
7
Customization - AI Agent Builders
Not enough data
8.6
6
Not enough data
7.2
6
Not enough data
8.6
6
Functionality - AI Agent Builders
Not enough data
8.6
6
Not enough data
6.4
6
Not enough data
9.4
6
Not enough data
6.7
6
Data and Analytics - AI Agent Builders
Not enough data
8.1
6
Not enough data
8.6
6
Not enough data
8.6
6
Integration - AI Agent Builders
Not enough data
9.4
6
Not enough data
8.3
6
Not enough data
7.5
6
Not enough data
8.1
6
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, and AI Agent Builders
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
16.5%
Information Technology and Services
13.6%
Financial Services
7.1%
Retail
4.1%
Consulting
3.5%
Other
55.1%
Most Helpful Reviews
IBM Decision Optimization
Most Helpful Favorable Review
MUSTAFA V.
Verified User in Education Management
Helpfull to collect and analyze decision data. I find it usefull
Most Helpful Critical Review
Verified User in Financial Services
Blackbox solution that does not meet regulatory requirements.
Vertex AI
Most Helpful Favorable Review
Verified User in Construction
Unified Platform: Vertex AI brings together various ML components into a single platform, making it easier to manage and monitor the entire process. Scalability: It effortlessly handles large datasets and complex models, allowing for efficient scaling...
Most Helpful Critical Review
Verified User in Computer Software
It is not very user friendly, and does not have a GUI to submit my training job.
MUSTAFA V.
Verified User in Education Management
Helpfull to collect and analyze decision data. I find it usefull
Verified User in Construction
Unified Platform: Vertex AI brings together various ML components into a single platform, making it easier to manage and monitor the entire process. Scalability: It effortlessly handles large datasets and complex models, allowing for efficient scaling...
Verified User in Financial Services
Blackbox solution that does not meet regulatory requirements.
Verified User in Computer Software
It is not very user friendly, and does not have a GUI to submit my training job.
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