Compare Salesforce Agentforce and Vertex AI 
At a Glance
Market Segments
Mid-Market (43.6% of reviews)
Small-Business (42.0% of reviews)
Entry-Level Pricing
Free 200000 Flex Credits
Pay As You Go Per Month
Salesforce Agentforce
Star Rating
(855)4.4 out of 5
Market Segments
Mid-Market (43.6% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
Free 200000 Flex Credits
Browse all 3 pricing plansVertex AI
Star Rating
(652)4.3 out of 5
Market Segments
Small-Business (42.0% of reviews)
Pros & Cons
Entry-Level Pricing
Pay As You Go Per Month
Learn more about Vertex AISummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Salesforce Agentforce excels in user-friendliness, with many users highlighting its intuitive interface that requires minimal training. This ease of use allows teams to work faster and organize tasks more effectively, making daily operations simpler.
- Users say that Vertex AI stands out for its comprehensive management of the machine learning lifecycle. Reviewers appreciate how it centralizes everything from data preparation to model deployment, significantly reducing the complexity of managing ML workflows.
- According to verified reviews, Salesforce Agentforce offers robust support during implementation and post-launch, with users noting the availability of assistance for deploying agents across various customer-facing and employee portals. This support is crucial for ensuring a smooth transition.
- Reviewers mention that while Vertex AI provides a powerful platform for building and deploying machine learning models, some users have encountered challenges with configuration, indicating that it may require a steeper learning curve for those unfamiliar with ML processes.
- G2 reviewers highlight that Salesforce Agentforce's ability to reference real customer data enhances the relevance of its responses, making it a valuable tool for teams that need contextually aware interactions. This feature is particularly beneficial for improving customer service efficiency.
- Users report that Vertex AI's seamless integration with Google Cloud is a significant advantage, allowing for efficient management of complex ML tasks. However, some users feel that it may not cater as effectively to specific workflow needs compared to Salesforce Agentforce's more tailored approach.
Pricing
Entry-Level Pricing
Salesforce Agentforce
Salesforce Foundations
Free
200000 Flex Credits
Get started with Agentforce for free, for any use case.
- Agent Builder
- Prompt Builder
- 200k Flex Credits
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
Salesforce Agentforce
Free Trial is available
Vertex AI
No trial information availableRatings
Meets Requirements
8.3
222
8.6
389
Ease of Use
8.1
673
8.2
400
Ease of Setup
7.9
642
8.1
322
Ease of Admin
8.4
134
7.9
149
Quality of Support
8.1
211
8.1
364
Has the product been a good partner in doing business?
8.5
134
8.3
143
Product Direction (% positive)
9.3
226
9.2
383
Features by Category
Deployment
Not enough data
8.4
76
Not enough data
8.1
78
Not enough data
8.3
76
Not enough data
8.4
76
Not enough data
8.8
75
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
73
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
8.4
37
Not enough data
8.6
37
System
Not enough data
8.2
173
Model Development
Not enough data
8.5
208
Not enough data
7.9
181
Not enough data
8.4
206
Not enough data
8.5
209
Model Development
Not enough data
8.2
167
Machine/Deep Learning Services
Not enough data
8.3
203
Not enough data
8.5
202
Not enough data
8.2
200
Not enough data
8.3
181
Machine/Deep Learning Services
Not enough data
8.5
167
Not enough data
8.5
166
Deployment
Not enough data
8.3
213
Not enough data
8.3
203
Not enough data
8.6
207
Generative AI
Not enough data
8.3
110
Not enough data
8.3
106
Not enough data
8.1
105
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
8.1
38
Not enough data
7.8
37
Not enough data
7.7
38
Not enough data
7.9
35
Not enough data
8.5
37
Not enough data
7.5
36
Not enough data
7.7
36
Scalability and Performance - Generative AI Infrastructure
Not enough data
9.0
31
Not enough data
8.7
32
Not enough data
8.6
31
Cost and Efficiency - Generative AI Infrastructure
Not enough data
8.0
34
Not enough data
7.7
31
Not enough data
8.1
30
Integration and Extensibility - Generative AI Infrastructure
Not enough data
8.5
30
Not enough data
8.3
32
Not enough data
8.5
31
Security and Compliance - Generative AI Infrastructure
Not enough data
8.7
30
Not enough data
8.3
32
Not enough data
8.9
30
Usability and Support - Generative AI Infrastructure
Not enough data
8.2
31
Not enough data
8.5
31
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
9.0
26
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
24
Not enough data
9.0
24
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
25
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
24
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
9.2
23
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
23
Not enough data
8.7
22
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
8.7
23
Not enough data
8.9
22
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
8.7
21
Not enough data
9.1
22
Security - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
22
Not enough data
9.0
23
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
8.9
22
Customization - AI Agent Builders
8.1
154
8.6
28
7.9
153
7.6
27
8.3
153
8.3
26
Functionality - AI Agent Builders
8.0
151
8.1
27
7.9
150
7.3
27
8.0
148
8.2
26
7.9
147
7.2
27
Data and Analytics - AI Agent Builders
8.1
150
7.8
26
7.8
145
7.9
27
8.2
146
8.1
28
Integration - AI Agent Builders
8.3
152
8.8
28
8.1
75
8.2
30
8.1
141
8.1
28
8.5
145
7.5
27
Automation
8.5
16
Not enough data
8.7
17
Not enough data
8.6
16
Not enough data
8.8
17
Not enough data
8.6
17
Not enough data
Autonomy
8.6
17
Not enough data
8.9
17
Not enough data
8.8
17
Not enough data
8.5
17
Not enough data
Outbound Sales
8.8
17
Not enough data
9.3
17
Not enough data
9.1
17
Not enough data
8.9
17
Not enough data
9.0
17
Not enough data
Inbound Sales
8.8
17
Not enough data
9.1
17
Not enough data
8.7
17
Not enough data
8.7
17
Not enough data
8.6
17
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
Customer Query Resolution - AI Customer Support Agents
8.2
58
Not enough data
8.1
59
Not enough data
8.0
58
Not enough data
8.7
59
Not enough data
7.8
57
Not enough data
Customer Interaction Automation - AI Customer Support Agents
8.2
57
Not enough data
8.5
57
Not enough data
8.3
56
Not enough data
8.2
59
Not enough data
Automation
8.6
61
Not enough data
8.5
59
Not enough data
8.4
59
Not enough data
Autonomy
7.8
58
Not enough data
8.0
57
Not enough data
8.4
57
Not enough data
8.1
58
Not enough data
Agentic AI - AI Agents
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
Categories
Categories
Shared Categories
Salesforce Agentforce and Vertex AI are categorized as AI Agent Builders
Unique Categories
Salesforce Agentforce is categorized as AI Customer Support Agents and AI SDRs
Reviews
Reviewers' Company Size
Salesforce Agentforce
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
Information Technology and Services
11.7%
Financial Services
10.4%
Computer Software
6.6%
Consulting
6.3%
Hospital & Health Care
4.6%
Other
60.4%
Computer Software
17.9%
Information Technology and Services
14.3%
Financial Services
6.8%
Retail
3.6%
Hospital & Health Care
3.3%
Other
54.1%
Alternatives
Discussions
Salesforce Agentforce has no discussions with answers
What is Google Cloud AI Platform used for?
3 Comments
AO
Vertex AI is Google Cloud’s managed machine learning platform. It’s used to build, train, and deploy ML models at scale. It unifies data, AutoML, and custom...Read more
What software libraries does cloud ML engine support?
3 Comments
AO
Cloud ML Engine (now part of Vertex AI) supports popular ML frameworks and libraries such as TensorFlow, PyTorch, Scikit‑learn, and XGBoost. This flexibility...Read more
What is Google AI platform?
2 Comments
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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