#1 most frequent
United States of America
53.6%2,895 installations of 5,401
What is Gemini Enterprise Agent Platform?
Vertex AI on Google Cloud is an MLOps solution, used to build, deploy, and scale machine learning (ML) models with fully managed ML tools for any use case.
Categories & Use Cases
Media
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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.
Top Performing Features
Data management
Ingested data can be stored and prepped, with structures like data lakehouses available to handle large amounts of data from disparate sources.
Category average: 7.6
Automated model training
After teams begin the process, model training can continue autonomously, enabling faster deployment.
Category average: 7.6
Machine learning frameworks
A wide variety of machine learning frameworks are available and to be used when training models.
Category average: 7.6
Areas for Improvement
Security and compliance
End to end encryption, GDPR compliance, SSO, role-based permissioning, and other precautions are available to protect proprietary business data.
Category average: 7.9
Data monitoring and version control
Teams can track which data is used in training at which point and roll back to previous versions as needed.
Category average: 7
Managed scaling
The platform provides the computing resources needed when they’re needed, allowing users to scale training and use up or down.
Category average: 7.3
Who Buys & Uses Gemini Enterprise Agent Platform
#2 most frequent
India
6.1%330 installations of 5,401
#3 most frequent
United Kingdom of Great Britain and Northern Ireland
5.0%271 installations of 5,401
Pros
- Automates daily operational tasks and security workflows
- Offers comprehensive machine learning tools, including pre-trained and generative AI models
- Provides flexibility and ease of integration with diverse systems
Cons
- Features a steep learning curve for new users
- Has a complex user interface that can be challenging to navigate
- Incurs high costs and token expenses for some operations
A Strong AI Platform for Building Deploying and Scaling ML Models
Use Cases and Deployment Scope
In our organisation we use Vertex AI to develop and deploy the ML models,its is very helpful and useful for our organisation,easy to automate the task and day to day activity,improving decision making and logical thinking,we using this AI different kind of scoop like data integration model training, monitoring and analysis part as well. we have analysed business level problem and strategic as well. reduced our manual works and implemented many automation's task and integrated with our internal product also.using this model agents will be deployed faster.improved our operation effect
Pros
- automatic resource management
- real time working experience
- machine learning management
Cons
- complex for beginners
- step by step real world working
- cost effective
Return on Investment
- productive innovation and devolopment
- cost effective
- reduce infra cost for developing products
- reduce training time
Alternatives Considered
ChatGPT and Anthropic Claude
Other Software Used
Vertex AI, Anthropic Claude, ChatGPT
Vertex AI for Cybersecurity
Use Cases and Deployment Scope
Vertex AI is the best AI, and I am currently using it for automation in Security Platforms, and it has the best accuracy to find vulnerabilities. The special in the Vertex AI is that we can train the model for our daily use case, and it is best in the output without false positives. We can use this to reduce the manpower and it will give the result within a few seconds according to our inputs. The best thing in the Vertex AI is pay as you go. It can be capable for the simple prompts and will give the results in a detailed manner. It will create the workflow for our daily tasks. Best AI with great accuracy.
Pros
- To find the Vulnerabilities in the servers
- To automate the daily checklist in our daily tasks Vertex AI will complete it within a minute
- To create the workflow for the Security automations
Cons
- It is little hard to experience with the Vertex AI
- It has the low testing fields for the Security
- In the SOC area need to be improved, as of now it has low in Defence.
Return on Investment
- Need to automate the more workflow with the different Scenario
- The cost of the Vertex AI is little high
- It has the best to give the results within a seconds
Alternatives Considered
ChatGPT and Perplexity
Other Software Used
Vertex AI, ChatGPT, Perplexity
Google's Vertex AI Is Great For Image Editing
Use Cases and Deployment Scope
We do a lot of image generation for our various areas of marketing (website, social media, graphics for conferences/booth giveaways), and we love using Vertex AI's image editor. We've used other AI image generators in the past (such as Microsoft's and Chat GPT's), but we've found Vertex to be a lot more accurate with less amount of mistakes.
Pros
- Image Editing (especially with minute details)
- Retained Image Crispness around edges of AI's additions
- Amount of menu options Google provides in it's UI
- Google's training modules on Vertex is actually really helpful
Cons
- It's expensive to use. The cost could be a bit lower for tokens.
- The Vertex AI Search isn't bulletproof and sometimes is wrong
- To really master their UI, it does take some training. There's a lot of options.
Return on Investment
- It has helped speed up the process of getting the exact image we need for our various marketing initiatives.
- Images are stored in our Google Cloud, which we use in our business anyways (makes it super easy to find/share)
- Google's security is always top notch. Even though it's just images, we still need the confidentiality of our creations.
Alternatives Considered
ChatGPT, Microsoft Copilot and OpenAI API Platform
Other Software Used
ChatGPT, Microsoft Copilot, OpenAI API Platform
Powerful complex with top of the line feature set
Use Cases and Deployment Scope
We work as experts of this platform and implement it in customers environments. It can range from banks to airlines so business use can vary a lot. Not one business is like the other so flexibility is a must for us, and we can quickly and easily see what platforms are adaptable and useful.
Pros
- Integration to various platforms for multi-purpose
- Flexibility of quick and easy adjustments
- Bot reading from knowledge base
Cons
- Learning curve
- Tutorials
- Labs to learn the tools
Return on Investment
- The steep learning curve is definitely an investment needed to be made
- The partnership program leaves a little bit more to be desired, this process should be made slightly easier
- Product and platform itself is genuinely very powerful
Alternatives Considered
Azure AI Bot Service and ChatGPT
Other Software Used
ChatGPT, Azure AI Studio, Genesys Cloud CX, Webex Contact Center, Google Cloud Dialogflow
Vertex AI Review
Pros
- Python Notebook Scheduling
- Pre-trained ML Models
- Easy access to BigQuery Studio
- In Model-Garden we can directly use GenAI models
Cons
- Computing Power is very less for little more complex scripts
- Notebook scheduling can be improved where we can schedule the notebooks except 2-3 days in each month.
- It'll take so much time to start the instance
Return on Investment
- 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.
Other Software Used
Microsoft Power BI, Google BigQuery, Microsoft Teams
