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AutoGen vs Gemini Enterprise Agent Platform comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Apr 23, 2026

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Automation Anywhere
Sponsored
Average Rating
8.4
Reviews Sentiment
6.8
Number of Reviews
665
Ranking in other categories
Business Process Management (BPM) (2nd), Robotic Process Automation (RPA) (2nd), Process Mining (1st), Intelligent Document Processing (IDP) (1st), Agentic Automation (1st), Business Orchestration and Automation Technologies (2nd), AI Legal & Compliance (1st), AI Finance & Accounting (2nd), AI Procurement & Supply Chain (1st)
AutoGen
Average Rating
8.0
Number of Reviews
1
Ranking in other categories
AI Agent Builders (11th)
Gemini Enterprise Agent Pla...
Average Rating
8.2
Reviews Sentiment
6.3
Number of Reviews
15
Ranking in other categories
AI Development Platforms (1st), AI Agent Builders (5th)
 

Featured Reviews

Venkat Sivaprakash - PeerSpot reviewer
Management Consultant at Accenture
Has significantly improved document-driven workflows and reduced processing time across finance and HR functions
Automation Anywhere has evolved significantly and upgraded itself to provide agentic AI and AI-based automation solutions for document automation. The product has matured considerably over time. We can create workflows that can call an API. We can include prompts in particular workflows for ChatGPT-related functions, connecting to an LLM and RAG to perform tasks. For document automation, modern features are available to train documents, ensuring high accuracy and repeatability over time. The system is very easy to use. I recently completed a course in document automation, typically designed for people involved in coding and technical aspects. Though I understand coding comprehensively, I don't do actual coding. The course was very accessible. Currently, extensive coding isn't necessary due to the hybrid model incorporating GenAI aspects, low-code, no-code capabilities, APIs, and numerous pre-built objects in Automation Anywhere. The features include GenAI-driven prompting methods and workflow creation capabilities. In these workflows, we can create decision boxes and call APIs without coding. We simply pull objects, drop them, connect them, and add minimal coding when needed. The most crucial aspect isn't coding but rather sizing the automation and fleshing out the details. Automation Co-pilot takes notes and performs automated analysis. It can extract details from videos, summarize conversations, and provide detailed information. During calls, it identifies instructions and performs tasks such as preparing reports and reconciliation. Automation Anywhere can also connect with Microsoft Co-pilot. Through Co-pilot, real-time operations can be executed, allowing direct interaction between vendors and automation through this component.
Marián Lojka - PeerSpot reviewer
Sr. Manager, Data Architect Accenture Technology at Accenture
Framework has streamlined multi-agent monitoring and now delivers clear, actionable log insights
I appreciate the AutoGen Studio team builder, which is good, but it could be even better. I do not understand the versioning from Microsoft; the version is 0.4, which has been available since February 2025. There are already multiple platforms on the internet for creating AI agent systems, and I think AutoGen is not as mature as it could be. The challenges that other customers might encounter while setting up this solution include understanding how the framework works. The documentation is somewhat available, but it is not perfect, and there are not many running examples because it is new. There is no community yet, so you might be dealing with issues specific to how to use the framework properly to achieve the desired outcomes.
Pethuru Chelliah - PeerSpot reviewer
Chief Architect at a energy/utilities company with 10,001+ employees
Developed and deployed AI agents through a unified platform that supports integration with enterprise systems
We used AutoML feature for developing AI models automatically, but we are not comfortable with the performance of those models. We have to do some fine-tuning, hyperparameter optimization, and other optimizations to enhance the performance of the AI models. We are not fully leveraging the automation being provided by Google Vertex AI for building AI models. Google Vertex AI has to be enhanced to support agentic AI system development. AI agents have to be developed through Google Vertex AI. Additionally, RAG support, vector database support, knowledge graph support, integration with enterprise systems such as ERP, CRM, PLM, MES, and other enterprise systems need improvement. Automated workflow generation and automation could also be enhanced. At this point, we are completely satisfied with the features and functionalities of Google Vertex AI platform, but as we move towards autonomous systems through agentic AI paradigm, Google Vertex AI platform needs to be improved to facilitate agentic AI system design, development, deployment, monitoring, observability, governance, and security.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Document Automation is something we are using and have used in the past; it is excellent."
"Automation Anywhere's support has been great since we signed up for gold support last year."
"By automating those processes we achieved high ROI, great customer satisfaction, better STP, reduced manual work, reduced processing time, high accuracy, and 24/7 working capacity with the AA bots."
"Overall, Automation Anywhere is a very user-friendly and easy-to-use tool, and if clients are looking to implement automation into their business, I would definitely recommend Automation Anywhere over other tools because it is well-suited for their purposes and can be easily utilized."
"The OCR is the most valuable feature, though this is a third party feature that we have integrated. It is quite easy to integrate with other solutions."
"It's very easy for business users to learn Automation Anywhere."
"Automation Anywhere is a very good tool because it helps you along the process."
"Our experience with technical support at Automation Anywhere has been great. They have been very helpful, especially during the PoC, processes which are sort of early on in their sales cycle, or when we were just starting with Automation Anywhere a couple of years ago. We got great support for getting it onboarded in-house and getting our team up to speed. So, we have found it to be a great partnership."
"The features contributing most to operational efficiency with AutoGen are part of the framework that allows you to create AI agents in an accelerated way and the communication between those agents in the same manner."
"Google Vertex AI is an out-of-the-box and very easy-to-use solution."
"The support is perfect and fantastic."
"With just one single platform, Google Vertex AI platform, we can achieve everything; we need not switch over to multiple tools, multiple platforms, as everything can be accomplished through this one single platform for integration with existing workflows, systems, tools, and databases."
"We extensively utilize Google Cloud's Vertex AI platform for our machine learning workflows. Specifically, we leverage the IO branch for EDA data in Suresh Live Virtual, employing Forte IT for training machine learning models. The AI model registry in Vertex AI is crucial for cataloging and managing various versions of the models we develop. When it comes to deploying models, we rely on Google Cloud's AI Prediction service, seamlessly integrating it into our workflow for real-time predictions or streaming. For monitoring and tracking the outcomes of model development, we employ Vertex AI Monitoring, ensuring a comprehensive understanding of the model's performance and results. This integrated approach within Vertex AI provides a unified platform for managing, deploying, and monitoring machine learning models efficiently."
"The monitoring feature is a true life-saver for data scientists. I give it a ten out of ten."
"The features I have found most valuable in Google Vertex AI are Gemini's large language models, which are currently among the best, and the vision tool of Gemini, which I consider quite good."
"It provides the most valuable external analytics."
"The integration of AutoML features streamlines our machine-learning workflows."
 

Cons

"The initial setup for the program was not straightforward. It was definitely complex."
"I had an issue lasting for the better part of three years, and it was quite severe."
"What we currently have with Fortress IQ needs to mature more, and I say this since people spend weeks creating PDDs documentation."
"Licensing can also become expensive and rigid as you scale, particularly for unattended bot runners and specialized cognitive add-ons."
"I would like to see more complex use cases coming out for our industry."
"There is definitely some room for improvement there. It is sort of a hit and miss with their support engineers, you have some really good ones and some that aren't."
"Currently, Automation Anywhere's debugging functionality is minimal."
"One way Automation Anywhere can be improved is in ticketing; I have a couple of tickets that have been outstanding for a while, and the support staff have closed tickets without checking with me first, which has been a sore spot."
"I do not understand the versioning from Microsoft; the version is 0.4, which has been available since February 2025. There are already multiple platforms on the internet for creating AI agent systems, and I think AutoGen is not as mature as it could be."
"It takes a considerable amount of time to process, and I understand the technology behind why it takes this long, but this is something that could be reduced."
"The solution is stable, but it is quite slow. Maybe my data is too large, but I think that Google could improve Vertex AI's training time."
"Google Vertex AI is good in machine learning and AI, but it lacks optimization."
"I'm not sure if I have suggestions for improvement."
"It is not completely mature and needs some features and functions. The interface needs to be more user-friendly."
"Google can improve Google Vertex AI in terms of analysis and accuracy. When passing a very large context, instead of receiving vague responses, it would be better if the system could prompt users not to pass overly large prompts and provide clearer guidance on how to fine-tune Gemini for specific use cases."
"I believe that Vertex AI is a robust platform, but its effectiveness depends significantly on the domain knowledge of the developer using it. While Vertex AI does offer support through the console UI in the Google Cloud environment, it is better suited for technical members who have a deeper understanding of machine learning concepts. The platform may be challenging for business process developers (BPDUs) who lack extensive technical knowledge, as it involves intricate customization and handling numerous parameters. Effectively utilizing Vertex AI requires not only familiarity with machine learning frameworks like TensorFlow or PyTorch but also a proficiency in Python programming. The complexity of these requirements might pose challenges for less technically oriented users, making it crucial to have a solid foundation in both machine learning principles and Python coding to extract the full value from Vertex AI. It would be beneficial to have a streamlined process where we can leverage the capabilities of Vertex AI directly through the BigQuery UI. This could involve functionalities such as creating machine learning models within the BigQuery UI, providing a more user-friendly and integrated experience. This would allow users to access and analyze data from BigQuery while simultaneously utilizing Vertex AI to build machine learning models, fostering a more cohesive and efficient workflow."
"I've noticed that using chat activity often presents a broader range of options and insights for a well-constructed question. Improving the knowledge base could be a key aspect for enhancement—expanding the information sources to enhance the generation process."
 

Pricing and Cost Advice

"We were paying approximately $30,000 for a year license."
"The price for Automation Anywhere is reasonable."
"It's cheaper than other similar solutions."
"My only suggestion in terms of pricing is very generic and that is to consider that as much as RPA saves cost and does automation, please get a realistic estimation done on whether you are really achieving any ROI over your investment with RPA."
"It's cheapest among the competition, although bargaining is a must."
"We were required to purchase licenses and bot runners, which determined the permissible run times for the bots."
"The licensing cost is approximately $4,000 USD, which is a seed license."
"The licensing cost for Automation Anywhere is high."
Information not available
"I think almost every tool offers a decent discount. In terms of credits or other stuff, every cloud provider provides a good number of incentives to onboard new clients."
"The price structure is very clear"
"The solution's pricing is moderate."
"The Versa AI offers attractive pricing. With this pricing structure, I can leverage various opportunities to bring value to my business. It's a positive aspect worth considering."
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Top Industries

By visitors reading reviews
Outsourcing Company
15%
Financial Services Firm
12%
Comms Service Provider
12%
Manufacturing Company
11%
No data available
Outsourcing Company
11%
Manufacturing Company
9%
Financial Services Firm
8%
Comms Service Provider
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business161
Midsize Enterprise86
Large Enterprise561
No data available
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise4
Large Enterprise7
 

Questions from the Community

How good is Automation Anywhere for RPA processes?
It depends on your use case. Is it simply to automate a couple of processes? Is it to augment a human team? AA is ver...
How good is Automation Anywhere for RPA processes?
From my experience using AA tool, it depends on the applications that you want to automate, because there some applic...
How good is Automation Anywhere for RPA processes?
It is a highly preferred RPA tool. You can check my Automation Anywhere Review to know more.
What needs improvement with AutoGen?
I appreciate the AutoGen Studio team builder, which is good, but it could be even better. I do not understand the ver...
What is your primary use case for AutoGen?
My use cases for AutoGen involve using it as the framework for building agentic AI systems. AutoGen is a framework fo...
What is your experience regarding pricing and costs for Google Vertex AI?
I purchased Google Vertex AI directly from Google, as we are a partner of Google. I would rate the pricing for Google...
What needs improvement with Google Vertex AI?
Google Vertex AI is quite complex to navigate and to start services with, as I need to do a lot of iterations to fina...
What is your primary use case for Google Vertex AI?
Google Vertex AI has been utilized for Vertex Pipelines. I have not utilized the pre-trained APIs in Google Vertex AI...
 

Also Known As

Automation Anywhere, Testing Anywhere, Automation Anywhere Enterprise, Agentic Process Automation System (Now Certified for WorkSpaces)
No data available
Vertex, Google Vertex AI
 

Interactive Demo

Demo not available
Demo not available
 

Overview

 

Sample Customers

Google, Linkedin, Cisco, Juniper Networks, DellEMC, Comcast, Mastercard, Quest Diagnostics
Information Not Available
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