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At a Glance
Market Segments
Small-Business (41.1% of reviews)
Enterprise (44.4% of reviews)
Entry-Level Pricing
Pay As You Go Per Month
No pricing available
Vertex AI
Star Rating
(591)4.3 out of 5
Market Segments
Small-Business (41.1% of reviews)
Pros & Cons
Entry-Level Pricing
Pay As You Go Per Month
Free Trial is available
Learn more about Vertex AIWipro Holmes
Star Rating
(10)3.8 out of 5
Market Segments
Enterprise (44.4% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Wipro HolmesVertex AI vs Wipro Holmes
- Reviewers felt that Vertex AI meets the needs of their business better than Wipro Holmes.
- When comparing quality of ongoing product support, Vertex AI and Wipro Holmes provide similar levels of assistance.
- For feature updates and roadmaps, our reviewers preferred the direction of Vertex AI over Wipro Holmes.
Pricing
Entry-Level Pricing
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
Wipro Holmes
No pricing availableFree Trial
Vertex AI
Free Trial is available
Wipro Holmes
No trial information availableRatings
Meets Requirements
8.6
358
7.7
8
Ease of Use
8.2
367
7.7
8
Ease of Setup
8.1
290
8.1
7
Ease of Admin
7.9
141
Not enough data
Quality of Support
8.1
334
8.1
8
Has the product been a good partner in doing business?
8.2
135
Not enough data
Product Direction (% positive)
9.2
352
8.5
8
Features by Category
Deployment
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
Not enough data
Deployment
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
Not enough data
Management
8.3
70
Not enough data
8.5
69
Not enough data
8.0
69
Not enough data
8.1
69
Not enough data
Operations
8.2
69
Not enough data
8.4
70
Not enough data
8.3
70
Not enough data
Management
8.1
68
Not enough data
8.4
69
Not enough data
8.3
68
Not enough data
Generative AI
8.2
34
Not enough data
8.4
34
Not enough data
System
8.2
170
6.9
7
Model Development
8.4
202
7.4
7
7.9
179
Feature Not Available
8.4
200
Feature Not Available
8.5
202
7.6
7
Model Development
8.2
165
7.6
7
Machine/Deep Learning Services
8.2
200
6.4
7
8.4
196
8.6
7
8.2
195
7.4
7
8.2
178
7.9
7
Machine/Deep Learning Services
8.5
165
7.6
7
8.4
163
7.6
7
Deployment
8.2
193
Feature Not Available
8.3
194
8.1
7
8.5
193
8.1
7
Generative AI
8.3
102
Not enough data
8.2
102
Not enough data
8.1
103
Not enough data
Agentic AI - Data Science and Machine Learning Platforms
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
Not enough data
Scalability and Performance - Generative AI Infrastructure
8.9
28
Not enough data
8.6
28
Not enough data
8.5
28
Not enough data
Cost and Efficiency - Generative AI Infrastructure
8.2
28
Not enough data
7.8
28
Not enough data
7.9
28
Not enough data
Integration and Extensibility - Generative AI Infrastructure
8.4
28
Not enough data
8.1
28
Not enough data
8.3
28
Not enough data
Security and Compliance - Generative AI Infrastructure
8.6
28
Not enough data
8.5
28
Not enough data
8.9
28
Not enough data
Usability and Support - Generative AI Infrastructure
8.2
28
Not enough data
8.3
28
Not enough data
Integration - Machine Learning
8.5
67
Not enough data
Learning - Machine Learning
8.5
66
Not enough data
8.3
65
Not enough data
8.8
66
Not enough data
Large Language Model Operationalization (LLMOps)Hide 15 FeaturesShow 15 Features
8.9
23
Not enough data
Prompt Engineering - Large Language Model Operationalization (LLMOps)
8.8
22
Not enough data
8.9
22
Not enough data
Inference Optimization - Large Language Model Operationalization (LLMOps)
8.8
22
Not enough data
Model Garden - Large Language Model Operationalization (LLMOps)
9.2
22
Not enough data
Custom Training - Large Language Model Operationalization (LLMOps)
9.0
22
Not enough data
Application Development - Large Language Model Operationalization (LLMOps)
9.2
22
Not enough data
Model Deployment - Large Language Model Operationalization (LLMOps)
9.1
22
Not enough data
8.7
21
Not enough data
Guardrails - Large Language Model Operationalization (LLMOps)
9.0
21
Not enough data
8.8
21
Not enough data
Model Monitoring - Large Language Model Operationalization (LLMOps)
8.7
21
Not enough data
9.0
21
Not enough data
Security - Large Language Model Operationalization (LLMOps)
9.1
22
Not enough data
8.9
22
Not enough data
Gateways & Routers - Large Language Model Operationalization (LLMOps)
8.9
22
Not enough data
Customization - AI Agent Builders
8.5
27
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
7.7
25
Not enough data
7.9
27
Not enough data
8.0
27
Not enough data
Integration - AI Agent Builders
8.7
27
Not enough data
8.0
27
Not enough data
8.0
27
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
Vertex AI and Wipro Holmes are categorized as Data Science and Machine Learning Platforms
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
Wipro Holmes has no unique categories
Reviews
Reviewers' Company Size
Vertex AI
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Wipro Holmes
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
17.5%
Information Technology and Services
13.9%
Financial Services
7.0%
Retail
3.8%
Hospital & Health Care
3.4%
Other
54.3%
Information Technology and Services
44.4%
Logistics and Supply Chain
22.2%
Computer Software
22.2%
Financial Services
11.1%
‐
Other
0.0%
Alternatives
Discussions
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
What is Wipro Holmes used for?
1 Comment
AO
AI and Machine Learning, Automation, Data Analytics, Supply Chain Optimization.Read more
Wipro Holmes has no more discussions with answers
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