Compare Gemini Enterprise Agent Platform and Salesforce Agentforce 
At a Glance
Market Segments
Small-Business (42.2% of reviews)
Mid-Market (44.5% of reviews)
Entry-Level Pricing
Pay As You Go Per Month
Free 200000 Flex Credits
Gemini Enterprise Agent Platform
Star Rating
(652)4.3 out of 5
Market Segments
Small-Business (42.2% of reviews)
Pros & Cons
Entry-Level Pricing
Pay As You Go Per Month
Learn more about Gemini Enterprise Agent PlatformSalesforce Agentforce
Star Rating
(1,095)4.3 out of 5
Market Segments
Mid-Market (44.5% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
Free 200000 Flex Credits
Browse all 3 pricing plansSummary
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
Gemini Enterprise Agent Platform
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
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
Free Trial
Gemini Enterprise Agent Platform
No trial information availableSalesforce Agentforce
Free Trial is available
Ratings
Meets Requirements
8.6
387
8.3
248
Ease of Use
8.1
398
8.1
766
Ease of Setup
8.1
320
7.9
730
Ease of Admin
7.9
150
8.3
136
Quality of Support
8.1
363
8.2
237
Has the product been a good partner in doing business?
8.3
144
8.5
137
Product Direction (% positive)
9.2
381
9.1
246
Features by Category
Deployment
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
Not enough data
Deployment
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
Not enough data
Management
8.2
71
Not enough data
8.5
73
Not enough data
8.0
71
Not enough data
8.1
70
Not enough data
Operations
8.2
70
Not enough data
8.5
71
Not enough data
8.3
71
Not enough data
Management
8.1
69
Not enough data
8.4
72
Not enough data
8.3
70
Not enough data
Generative AI
8.4
37
Not enough data
8.6
37
Not enough data
System
8.2
170
Not enough data
Model Development
8.5
206
Not enough data
7.8
179
Not enough data
8.4
204
Not enough data
8.5
206
Not enough data
Model Development
8.2
164
Not enough data
Machine/Deep Learning Services
8.3
201
Not enough data
8.5
200
Not enough data
8.2
197
Not enough data
8.2
178
Not enough data
Machine/Deep Learning Services
8.5
164
Not enough data
8.5
163
Not enough data
Deployment
8.3
210
Not enough data
8.3
200
Not enough data
8.6
205
Not enough data
Generative AI
8.3
106
Not enough data
8.3
103
Not enough data
8.1
102
Not enough data
Agentic AI - Data Science and Machine Learning Platforms
8.0
35
Not enough data
7.8
34
Not enough data
7.6
36
Not enough data
7.8
32
Not enough data
8.4
34
Not enough data
7.4
33
Not enough data
7.6
33
Not enough data
Scalability and Performance - Generative AI Infrastructure
9.0
31
Not enough data
8.7
32
Not enough data
8.6
31
Not enough data
Cost and Efficiency - Generative AI Infrastructure
8.0
34
Not enough data
7.7
31
Not enough data
8.1
30
Not enough data
Integration and Extensibility - Generative AI Infrastructure
8.5
30
Not enough data
8.3
32
Not enough data
8.5
31
Not enough data
Security and Compliance - Generative AI Infrastructure
8.7
30
Not enough data
8.3
32
Not enough data
8.9
30
Not enough data
Usability and Support - Generative AI Infrastructure
8.2
31
Not enough data
8.5
31
Not enough data
Integration - Machine Learning
8.5
66
Not enough data
Learning - Machine Learning
8.5
64
Not enough data
8.3
63
Not enough data
8.8
64
Not enough data
Large Language Model Operationalization (LLMOps)Hide 15 FeaturesShow 15 Features
9.0
26
Not enough data
Prompt Engineering - Large Language Model Operationalization (LLMOps)
8.8
24
Not enough data
9.0
24
Not enough data
Inference Optimization - Large Language Model Operationalization (LLMOps)
8.8
22
Not enough data
Model Garden - Large Language Model Operationalization (LLMOps)
9.3
25
Not enough data
Custom Training - Large Language Model Operationalization (LLMOps)
9.1
24
Not enough data
Application Development - Large Language Model Operationalization (LLMOps)
9.2
23
Not enough data
Model Deployment - Large Language Model Operationalization (LLMOps)
9.0
23
Not enough data
8.7
22
Not enough data
Guardrails - Large Language Model Operationalization (LLMOps)
8.7
23
Not enough data
8.9
22
Not enough data
Model Monitoring - Large Language Model Operationalization (LLMOps)
8.7
21
Not enough data
9.1
22
Not enough data
Security - Large Language Model Operationalization (LLMOps)
9.1
22
Not enough data
9.0
23
Not enough data
Gateways & Routers - Large Language Model Operationalization (LLMOps)
8.9
22
Not enough data
Customization - AI Agent Builders
8.6
28
8.1
163
7.6
27
7.8
151
8.3
26
8.2
159
Functionality - AI Agent Builders
8.1
27
8.1
158
7.3
27
7.9
151
8.2
26
8.0
149
7.2
27
8.0
148
Data and Analytics - AI Agent Builders
7.8
26
8.2
165
7.9
27
7.9
156
8.1
28
8.1
152
Integration - AI Agent Builders
8.8
28
8.6
195
8.2
30
8.2
84
8.1
28
8.2
167
7.5
27
8.7
177
Automation
Not enough data
8.6
17
Not enough data
8.8
18
Not enough data
8.7
17
Not enough data
8.9
18
Not enough data
8.7
18
Autonomy
Not enough data
8.7
18
Not enough data
9.0
18
Not enough data
8.9
18
Not enough data
8.6
18
Outbound Sales
Not enough data
8.9
18
Not enough data
9.4
18
Not enough data
9.2
18
Not enough data
9.0
18
Not enough data
9.1
18
Inbound Sales
Not enough data
8.9
18
Not enough data
9.2
18
Not enough data
8.8
18
Not enough data
8.8
18
Not enough data
8.7
18
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
Natural Language Interaction - Conversational Interface Agents
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Intent & Action Handling - Conversational Interface Agents
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Context & Personalization - Conversational Interface Agents
Not enough data
Not enough data
Not enough data
Not enough data
Enterprise Integration & Deployment - Conversational Interface Agents
Not enough data
Not enough data
Not enough data
Not enough data
Customer Query Resolution - AI Customer Support Agents
Not enough data
8.2
59
Not enough data
8.1
60
Not enough data
8.0
58
Not enough data
8.7
61
Not enough data
7.7
57
Customer Interaction Automation - AI Customer Support Agents
Not enough data
8.2
57
Not enough data
8.5
57
Not enough data
8.2
57
Not enough data
8.3
62
Automation
Not enough data
8.7
66
Not enough data
8.5
59
Not enough data
8.4
60
Autonomy
Not enough data
7.8
59
Not enough data
8.0
58
Not enough data
8.4
60
Not enough data
8.1
59
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
Gemini Enterprise Agent Platform and Salesforce Agentforce are categorized as AI Agent Builders
Unique Categories
Gemini Enterprise Agent Platform is categorized as Large Language Model Operationalization (LLMOps), Generative AI Infrastructure, MLOps Platforms, Data Science and Machine Learning Platforms, Machine Learning, and Low-Code Machine Learning Platforms
Salesforce Agentforce is categorized as AI SDRs, AI Customer Support Agents, and Conversational Interface Agents
Reviews
Reviewers' Company Size
Gemini Enterprise Agent Platform
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Salesforce Agentforce
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
17.6%
Information Technology and Services
14.2%
Financial Services
6.9%
Retail
3.6%
Hospital & Health Care
3.4%
Other
54.2%
Information Technology and Services
12.5%
Financial Services
10.2%
Consulting
7.1%
Computer Software
7.1%
Manufacturing
4.4%
Other
58.8%
Alternatives
Discussions
What is Google Cloud AI Platform used for?
3 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?
3 Comments
SA
Google Cloud ML Engine supports many software libraries, including TensorFlow, scikit-learn, XGBoost, Keras, etc....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
Salesforce Agentforce has no discussions with answers
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