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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Gemini Enterprise Agent Platform

    Score8.9 out of 10
    N/AThe Gemini Enterprise Agent Platform is a fully-managed, unified environment designed for the development, orchestration, and governance of Autonomous AI Agents. The platform consolidates AI Studio, Agent Builder, and a diverse Model Garden to support the creation of complex, multi-agent systems grounded in enterprise data and business logic.

    $0

    Starting at

    Microsoft Azure

    Score8.5 out of 10
    N/AMicrosoft Azure is a cloud computing platform and infrastructure for building, deploying, and managing applications and services through a global network of Microsoft-managed datacenters.

    $29

    per month

    Pricing
    Gemini Enterprise Agent PlatformMicrosoft Azure
    Editions & Modules
    Imagen model for image generation
    $0.0001
    Starting at
    Text, chat, and code generation
    $0.0001
    per 1,000 characters
    Text data upload, training, deployment, prediction
    $0.05
    per hour
    Video data training and prediction
    $0.462
    per node hour
    Image data training, deployment, and prediction
    $1.375
    per node hour
    Developer
    $29
    per month
    Standard
    $100
    per month
    Professional Direct
    $1000
    per month
    Basic
    Free
    per month
    Offerings
    Pricing Offerings
    Gemini Enterprise Agent PlatformMicrosoft Azure
    Free Trial
    YesYes
    Free/Freemium Version
    YesYes
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeOptionalNo setup fee
    Additional DetailsPricing is based on the Vertex AI tools and services, storage, compute, and Google Cloud resources used.The free tier lets users have access to a variety of services free for 12 months with limited usage after making an Azure account.
    More Pricing Information
    Community Pulse
    Gemini Enterprise Agent PlatformMicrosoft Azure
    Considered Both Products
    Google
    No answer on this topic
    Microsoft
    No answer on this topic
    Key User Insights
    Would buy again
    93%
    Would buy again
    14 Answers
    92%
    Would buy again
    34 Answers
    Delivers good value for the price
    92%
    Delivers good value for the price
    12 Answers
    94%
    Delivers good value for the price
    31 Answers
    Happy with the feature set
    87%
    Happy with the feature set
    13 Answers
    95%
    Happy with the feature set
    35 Answers
    Lived up to sales and marketing promises
    78%
    Lived up to sales and marketing promises
    7 Answers
    89%
    Lived up to sales and marketing promises
    24 Answers
    Implementation went as expected
    86%
    Implementation went as expected
    12 Answers
    94%
    Implementation went as expected
    34 Answers
    Features
    Gemini Enterprise Agent PlatformMicrosoft Azure
    AI Development
    Comparison of AI Development features of Gemini Enterprise Agent Platform and Microsoft Azure
    Feature
    Gemini Enterprise Agent Platform
    8.6
    2 Ratings
    14% above category average
    Microsoft Azure
    -
    Ratings
    Machine learning frameworks8.62 Ratings00 Ratings
    Data management9.12 Ratings00 Ratings
    Data monitoring and version control8.22 Ratings00 Ratings
    Automated model training9.12 Ratings00 Ratings
    Managed scaling7.72 Ratings00 Ratings
    Model deployment8.62 Ratings00 Ratings
    Security and compliance8.62 Ratings00 Ratings
    Infrastructure-as-a-Service (IaaS)
    Comparison of Infrastructure-as-a-Service (IaaS) features of Gemini Enterprise Agent Platform and Microsoft Azure
    Feature
    Gemini Enterprise Agent Platform
    -
    Ratings
    Microsoft Azure
    8.4
    27 Ratings
    2% above category average
    Service-level Agreement (SLA) uptime00 Ratings8.126 Ratings
    Dynamic scaling00 Ratings8.725 Ratings
    Elastic load balancing00 Ratings8.624 Ratings
    Pre-configured templates00 Ratings8.225 Ratings
    Monitoring tools00 Ratings8.326 Ratings
    Pre-defined machine images00 Ratings8.424 Ratings
    Operating system support00 Ratings8.926 Ratings
    Security controls00 Ratings8.626 Ratings
    Automation00 Ratings8.224 Ratings
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    Gemini Enterprise Agent PlatformMicrosoft Azure
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    Score7.8 out of 10
    IBM Cloud Object Storage
    Score9 out of 10
    Medium-sized Companies
    DataRobot
    Score8.2 out of 10
    IBM Cloud Bare Metal Servers
    Score8.7 out of 10
    Enterprises
    DataRobot
    Score8.2 out of 10
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    Score9 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Gemini Enterprise Agent PlatformMicrosoft Azure
    Likelihood to Recommend
    7.6
    (15 ratings)
    8.7
    (96 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    10.0
    (17 ratings)
    Usability
    -
    (0 ratings)
    8.3
    (36 ratings)
    Availability
    -
    (0 ratings)
    6.8
    (2 ratings)
    Performance
    7.6
    (12 ratings)
    -
    (0 ratings)
    Support Rating
    -
    (0 ratings)
    9.0
    (27 ratings)
    Implementation Rating
    -
    (0 ratings)
    8.0
    (2 ratings)
    Configurability
    7.8
    (12 ratings)
    -
    (0 ratings)
    User Testimonials
    Gemini Enterprise Agent PlatformMicrosoft Azure
    Likelihood to Recommend
    Google
    we used Vertex AI on our automation process the model very useful and working as expected we have implemented in our monitoring phase this very helpful our analysis part. real time response is very effective and actively provide detailed overview about our products.this phase is well suited in our org. this model could not applicable for small level projects why because this model not needed for small level projects and without related resource of ML this model not useful. strictly on non cloud org not suitable means on pram not suitable
    Incentivized
    Read full review
    Microsoft
    Azure is particularly well suited for enterprise environments with existing Microsoft investments, those that require robust compliance features, and organizations that need hybrid cloud capabilities that bridge on-premises and cloud infrastructure. In my opinion, Azure is less appropriate for cost-sensitive startups or small businesses without dedicated cloud expertise and scenarios requiring edge computing use cases with limited connectivity. Azure offers comprehensive solutions for most business needs but can feel like there is a higher learning curve than other cloud-based providers, depending on the product and use case.
    Read full review
    Pros
    Google
    • Vertex AI comes with support for LOTs of LLMs out of the box
    • MLOps tools are available that help to standardize operational aspects
    • Document AI is an out of the box feature that works just perfectly for our use cases of automating lots to tedious data extraction tasks from images as well as papers
    Incentivized
    Read full review
    Microsoft
    • Microsoft Azure is highly scalable and flexible. You can quickly scale up or down additional resources and computing power.
    • You have no longer upfront investments for hardware. You only pay for the use of your computing power, storage space, or services.
    • The uptime that can be achieved and guaranteed is very important for our company. This includes the rapid maintenance for security updates that are mostly carried out by Microsoft.
    • The wide range of capabilities of services that are possible in Microsoft Azure. You can practically put or create anything in Microsoft Azure.
    Incentivized
    Read full review
    Cons
    Google
    • Customization of AutoML models - A must needed capability to be able to tweak hyperparameters and also working with different models
    • Model Explainability -Providing more comprehensive explanations about how models are utilizing features could be very beneficial
    • Model versioning and experiments tracking - Enhancing the versioning capability could be good for end users
    Incentivized
    Read full review
    Microsoft
    • The cost of resources is difficult to determine, technical documentation is frequently out of date, and documentation and mapping capabilities are lacking.
    • The documentation needs to be improved, and some advanced configuration options require research and experimentation.
    • Microsoft's licensing scheme is too complex for the average user, and Azure SQL syntax is too different from traditional SQL.
    Read full review
    Likelihood to Renew
    Google
    No answers on this topic
    Microsoft
    Moving to Azure was and still is an organizational strategy and not simply changing vendors. Our product roadmap revolved around Azure as we are in the business of humanitarian relief and Azure and Microsoft play an important part in quickly and efficiently serving all of the world. Migration and investment in Azure should be considered as an overall strategy of an organization and communicated companywide.
    Read full review
    Usability
    Google
    No answers on this topic
    Microsoft
    As Microsoft Azure is [doing a] really good with PaaS. The need of a market is to have [a] combo of PaaS and IaaS. While AWS is making [an] exceptionally well blend of both of them, Azure needs to work more on DevOps and Automation stuff. Apart from that, I would recommend Azure as a great platform for cloud services as scale.
    Incentivized
    Read full review
    Reliability and Availability
    Google
    No answers on this topic
    Microsoft
    It has proven to be unreliable in our production environment and services become unavailable without proper notification to system administrators
    Incentivized
    Read full review
    Performance
    Google
    Google is always top notch with their security and user interface performance. We use Google's entire suite in our business anyways, so using Vertex became second nature very quickly. I will say, though, that Google does need to come down on the price somewhat with their token allocation. Also, their UI is very robust, so it does require some time for training to really master it.
    Incentivized
    Read full review
    Microsoft
    No answers on this topic
    Support Rating
    Google
    No answers on this topic
    Microsoft
    We were running Windows Server and Active Directory, so [Microsoft] Azure was a seamless transition. We ran into a few, if any support issues, however, the availability of Microsoft Azure's support team was more than willing and able to guide us through the process. They even proposed solutions to issues we had not even thought of!
    Incentivized
    Read full review
    Implementation Rating
    Google
    No answers on this topic
    Microsoft
    As I have mentioned before the issue with my Oracle Mismatch Version issues that have put a delay on moving one of my platforms will justify my 7 rating.
    Read full review
    Alternatives Considered
    Google
    We tend to adapt and use the platform that suits the customers needs the best. We return to Vertex AI because it is the most in-depth option out there so we can configure it any which way they want. However, it is not quick to market and constantly changing or updating it's feature-set. This makes it suitable for bigger customers that have the capital and time to spend on a bigger project that is well researched and not quick to market like some of the other options that feel like a light-version of this.
    Incentivized
    Read full review
    Microsoft
    As I continue to evaluate the "big three" cloud providers for our clients, I make the following distinctions, though this gap continues to close. AWS is more granular, and inherently powerful in the configuration options compared to [Microsoft] Azure. It is a "developer" platform for cloud. However, Azure PowerShell is helping close this gap. Google Cloud is the leading containerization platform, largely thanks to it building kubernetes from the ground up. Azure containerization is getting better at having the same storage/deployment options.
    Incentivized
    Read full review
    Return on Investment
    Google
    • It is pay as you go model so it'll save more cost of your org. In our case previously we used to incurred 1-2L/Month now we are reduced it to 80k-1L.
    • It'll help you save your model training & model selection time as it provides pre-trained models in autoML.
    • It'll help you in terms of Security wherein we can use row level security access to authorized persons.
    Incentivized
    Read full review
    Microsoft
    • For about 2 years we didn't have to do anything with our production VMs, the system ran without a hitch, which meant our engineers could focus on features rather than infrastructure.
    • DNS management was very easy in Azure, which made it easy to upgrade our cluster with zero downtime.
    • Azure Web UI was easy to work with and navigate, which meant our senior engineers and DevOps team could work with Azure without formal training.
    Incentivized
    Read full review
    ScreenShots

    Gemini Enterprise Agent Platform Screenshots

    Screenshot of an introduction to generative AI on Vertex AI - Vertex AI Studio offers a Google Cloud console tool for rapidly prototyping and testing generative AI models.Screenshot of gen AI for summarization, classification, and extraction - Text prompts can be created to handle any number of tasks with Vertex AI’s generative AI support. Some of the most common tasks are classification, summarization, and extraction. Vertex AI’s PaLM API for text can be used to design prompts with flexibility in terms of their structure and format.Screenshot of Custom ML training overview and documentation - An overview of the custom training workflow in Vertex AI, the benefits of custom training, and the various training options that are available. This page also details every step involved in the ML training workflow from preparing data to predictions.Screenshot of ML model training and creation -  A guide that shows how Vertex AI’s AutoML is used to create and train custom machine learning models with minimal effort and machine learning expertise.Screenshot of deployment for batch or online predictions - When using a model to solve a real-world problem, the Vertex AI prediction service can be used for batch and online predictions.