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Gemini Enterprise Agent Platform vs. Wolfram Mathematica

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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

    Mathematica

    Score7 out of 10
    N/AWolfram's flagship product Mathematica is a modern technical computing application featuring a flexible symbolic coding language and a wide array of graphing and data visualization capabilities.

    $1,520

    per year

    Pricing
    Gemini Enterprise Agent PlatformMathematica
    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
    Standard Cloud
    $1,520
    per year
    Standard Desktop
    $3,040
    one-time fee
    Standard Desktop & Cloud
    $3,344
    one-time fee
    Mathematica Enterprise Edition
    $8,150.00
    one-time fee
    Offerings
    Pricing Offerings
    Gemini Enterprise Agent PlatformMathematica
    Free Trial
    YesNo
    Free/Freemium Version
    YesNo
    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.Discounts available for students and educational institutions. The Network Edition reduce per-user license costs through shared deployment across any number of machines on a local-area network.
    More Pricing Information
    Community Pulse
    Gemini Enterprise Agent PlatformMathematica
    Considered Both Products
    Google
    No answer on this topic
    Wolfram
    No answer on this topic
    Key User Insights
    Would buy again
    93%
    Would buy again
    14 Answers
    No answers on this topic
    Delivers good value for the price
    92%
    Delivers good value for the price
    12 Answers
    No answers on this topic
    Happy with the feature set
    87%
    Happy with the feature set
    13 Answers
    No answers on this topic
    Lived up to sales and marketing promises
    78%
    Lived up to sales and marketing promises
    7 Answers
    No answers on this topic
    Implementation went as expected
    86%
    Implementation went as expected
    12 Answers
    No answers on this topic
    Features
    Gemini Enterprise Agent PlatformMathematica
    AI Development
    Comparison of AI Development features of Gemini Enterprise Agent Platform and Wolfram Mathematica
    Feature
    Gemini Enterprise Agent Platform
    8.6
    2 Ratings
    14% above category average
    Wolfram Mathematica
    -
    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
    BI Standard Reporting
    Comparison of BI Standard Reporting features of Gemini Enterprise Agent Platform and Wolfram Mathematica
    Feature
    Gemini Enterprise Agent Platform
    -
    Ratings
    Wolfram Mathematica
    9.9
    6 Ratings
    20% above category average
    Pixel Perfect reports00 Ratings9.84 Ratings
    Customizable dashboards00 Ratings9.94 Ratings
    Report Formatting Templates00 Ratings9.96 Ratings
    Ad-hoc Reporting
    Comparison of Ad-hoc Reporting features of Gemini Enterprise Agent Platform and Wolfram Mathematica
    Feature
    Gemini Enterprise Agent Platform
    -
    Ratings
    Wolfram Mathematica
    9.9
    9 Ratings
    23% above category average
    Drill-down analysis00 Ratings9.98 Ratings
    Formatting capabilities00 Ratings9.98 Ratings
    Integration with R or other statistical packages00 Ratings9.97 Ratings
    Report sharing and collaboration00 Ratings9.99 Ratings
    Report Output and Scheduling
    Comparison of Report Output and Scheduling features of Gemini Enterprise Agent Platform and Wolfram Mathematica
    Feature
    Gemini Enterprise Agent Platform
    -
    Ratings
    Wolfram Mathematica
    9.3
    8 Ratings
    13% above category average
    Publish to Web00 Ratings9.97 Ratings
    Publish to PDF00 Ratings9.08 Ratings
    Report Versioning00 Ratings9.97 Ratings
    Report Delivery Scheduling00 Ratings8.95 Ratings
    Delivery to Remote Servers00 Ratings8.95 Ratings
    Data Discovery and Visualization
    Comparison of Data Discovery and Visualization features of Gemini Enterprise Agent Platform and Wolfram Mathematica
    Feature
    Gemini Enterprise Agent Platform
    -
    Ratings
    Wolfram Mathematica
    9.9
    9 Ratings
    24% above category average
    Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings9.99 Ratings
    Location Analytics / Geographic Visualization00 Ratings9.98 Ratings
    Predictive Analytics00 Ratings9.98 Ratings
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    All AlternativesView all alternativesView all alternatives
    User Ratings
    Gemini Enterprise Agent PlatformMathematica
    Likelihood to Recommend
    7.6
    (15 ratings)
    9.9
    (9 ratings)
    Performance
    7.6
    (12 ratings)
    -
    (0 ratings)
    Support Rating
    -
    (0 ratings)
    9.5
    (2 ratings)
    Configurability
    7.8
    (12 ratings)
    -
    (0 ratings)
    User Testimonials
    Gemini Enterprise Agent PlatformMathematica
    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
    Wolfram
    We are the judgement that Wolfram Mathematica is despite many critics based on the paradigms selected a mark in the fields of the markets for computations of all kind. Wolfram Mathematica is even a choice in fields where other bolide systems reign most of the market. Wolfram Mathematica offers rich flexibility and internally standardizes the right methodologies for his user community. Wolfram Mathematica is not cheap and in need of a hard an long learner journey. That makes it weak in comparison with of-the-shelf-solution packages or even other programming languages. But for systematization of methods Wolfram Mathematica is far in front of almost all the other. Scientist and interested people are able to develop themself further and Wolfram Matheamatica users are a human variant for themself. The reach out for modern mathematics based science is deep and a unique unified framework makes the whole field of mathematics accessable comparable to the brain of Albert Einstein. The paradigms incorporated are the most efficients and consist in assembly on the market. The mathematics is covering and fullfills not just education requirements but the demands and needs of experts.
    Mathematica is incompatible with other systems for mCAx and therefore the borders between the systems are hard to overcome. Wolfram Mathematica should be consider one of the more open systems because other code can be imported and run but on the export side it is rathe incompatible by design purposes. A better standard for all that might solve the crisis but there is none in sight. Selection of knowledge of what works will be in the future even more focussed and general system might be one the lossy side. Knowledge of esthetics of what will be in the highest demand in necessary and Wolfram is not a leader in this field of science. Mathematics leves from gathering problems from application fields and less from the glory of itself and the formalization of this.
    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
    Wolfram
    • It allows straightforward integration of analytic analysis of algebraic expressions and their numerical implemented.
    • Supports varying programmatic paradigms, so one can choose what best fits the problem or task: pure functions, procedural programming, list processing, and even (with a bit of setup) object-oriented programming.
    • The extensive and rich tools for graphical rendering make it very easy to not just get 2D and 3D renderings of final output, but also to do quick-and-dirty 2D and 3D rendering of intermediate results and/or debugging results.
    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
    Wolfram
    • Should include more libraries and functions.
    • Should include more functions that can be used in Machine Learning.
    • Should include more functions that can be used in Data Science.
    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
    Wolfram
    No answers on this topic
    Support Rating
    Google
    No answers on this topic
    Wolfram
    Wolfram Mathematica is a nice software package. It has very nice features and easy to install and use in your machine. Besides this, there is a nice support from Wolfram. They come to the university frequently to give seminars in Mathematica. I think this is the best thing they are doing. That is very helpful for graduate and undergraduate students who are using Mathematica in their research.
    Incentivized
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    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
    Wolfram
    We have evaluated and are using in some cases the Python language in concert with the Jupyter notebook interface. For UI, we using libraries like React to create visually stunning visualizations of such models. Mathematica compares favorably to this alternative in terms of speed of development. Mathematica compares unfavorably to this alternative in terms of license costs.
    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
    Wolfram
    • Easy to solve huge mathematical equations, so it saved time there
    • Doing analysis and plotting graphs is also another plus point
    • Learning is very slow, and it took lot of time to learn its scripting language
    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.