Compare Gemini Enterprise Agent Platform and Microsoft Copilot Studio 
At a Glance
Market Segments
Small-Business (42.2% of reviews)
Small-Business (42.1% of reviews)
Entry-Level Pricing
Pay As You Go Per Month
$1.00 2000 Sessions Month
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 PlatformMicrosoft Copilot Studio
Star Rating
(149)4.4 out of 5
Market Segments
Small-Business (42.1% of reviews)
Pros & Cons
Entry-Level Pricing
$1.00 2000 Sessions Month
Learn more about Microsoft Copilot StudioSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Vertex AI excels in managing complex machine learning workflows, with users appreciating its ability to centralize the entire ML lifecycle. One user highlighted how it simplifies everything from data preparation to deployment, making it a robust choice for those focused on machine learning.
- Users say Microsoft Copilot Studio shines in its integration capabilities, particularly with enterprise knowledge sources and Microsoft Graph data. Recent feedback noted that the tool allows for seamless actions through Power Automate, which enhances its utility in business environments.
- Reviewers mention that Vertex AI has a slight edge in meeting specific workflow needs, with a higher satisfaction score in this area. Users have expressed that it effectively reduces the effort required to build and deploy models, making it a preferred option for those heavily invested in machine learning.
- According to verified reviews, Microsoft Copilot Studio is praised for its user-friendly interface and configuration options. Users have described it as an "extremely brilliant agentic AI tool," which makes it easy to modify LLM models to meet client needs, showcasing its adaptability.
- G2 reviewers highlight that while both platforms offer solid support, Vertex AI has received slightly higher ratings for quality of support. Users appreciate the assistance provided, which is crucial for navigating the complexities of machine learning projects.
- Users report that Microsoft Copilot Studio offers detailed responses and more options for queries, which can enhance user experience in day-to-day tasks. This feature is particularly beneficial for teams looking for comprehensive answers and flexibility in their interactions with the AI.
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
Microsoft Copilot Studio
Power Virtual Agents
$1.00
2000 Sessions Month
NA
- Create and maintain intelligent chatbots - 1,000 bots Sessions - 2,000 per month3 Use Common Data Service} - 10 GB database capacity } 420 GB file capacity4 Enable your bot to take action - Power Automate use rights5 Sessions add-on - Sessions add-on$450
Free Trial
Gemini Enterprise Agent Platform
No trial information availableMicrosoft Copilot Studio
No trial information availableRatings
Meets Requirements
8.6
387
8.2
129
Ease of Use
8.1
398
8.7
132
Ease of Setup
8.1
320
8.6
112
Ease of Admin
7.9
150
8.6
36
Quality of Support
8.1
363
8.2
122
Has the product been a good partner in doing business?
8.3
144
8.5
36
Product Direction (% positive)
9.2
381
9.3
127
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
Generative AI
Not enough data
8.1
36
Not enough data
8.5
36
Agentic AI - Bot Platforms
Not enough data
8.0
27
Not enough data
7.7
27
Not enough data
7.8
28
Not enough data
7.8
27
Not enough data
7.9
26
Not enough data
7.6
26
Not enough data
7.3
26
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
8.2
65
7.6
27
7.6
61
8.3
26
8.0
64
Functionality - AI Agent Builders
8.1
27
7.8
57
7.3
27
7.8
56
8.2
26
7.9
55
7.2
27
8.1
55
Data and Analytics - AI Agent Builders
7.8
26
7.8
54
7.9
27
7.7
56
8.1
28
8.2
56
Integration - AI Agent Builders
8.8
28
8.4
66
8.2
30
8.1
55
8.1
28
8.1
65
7.5
27
8.0
55
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
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 Microsoft Copilot Studio 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
Microsoft Copilot Studio is categorized as Bot Platforms 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.)
Microsoft Copilot Studio
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
21.7%
Computer Software
11.6%
Financial Services
5.1%
Automotive
4.3%
Computer & Network Security
4.3%
Other
52.9%
Alternatives
Discussions
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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
What can power virtual agents do?
1 Comment
AD
Power Virtual Agent is a no-code chatbot deployment software that helps you set up a chatbot on your website with the predefined topics that you configure in...Read more
How soon will this bot be able to answer customer questions flawlessly?
1 Comment
RJ
It depends on the question being asked.For example, if we ask the hi/hello the response will be faster.If the api are used then based on the time it takes to...Read more
Microsoft Copilot Studio has no more discussions with answers
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