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
Likelihood to Recommend
Since we have used this platforms in multiple scenarios we can confidently say that where this excels is when you want to combine free form Q&A bots with structured responses. Gemini shines through and stands tall with it's natural language model and accurate reading of knowledge base to provide the best answers to whatever prompt you can throw at it.
Verified User
Technician in Information Technology (1001-5000 employees)
I have been working on Vertex AI for quite long now, It is one stop all data science solution,I did transformed multiple POCs to projects with Vertex AI only. At the same time, it has lot many bugs google team tough fixes but still it has many bugs
Pros
Kubeflow pipeline
Model building
Cons
Kubeflow pipelines
Jupyter notebook, file upload environment issues
Likelihood to Recommend
It's best tech I have used so far but requires thorough testing before production stage as it has many dependencies in the form of pre-built libraries and bugs
we have used Vertex AI in machien learning models to streamline and accelerate the development. Vertex AI is help us too automate few things in our project as well and we are using google cloud already it's super easy to integrate with big query and dataflow it makes allowing smooth data pipeline and machine learning process
Likelihood to Recommend
our sales team want to predict customer churn but we don't have enough data scientist in organisation so we need some automation tool for ML process so we have used Vertex AI for train model it required minimal configuration and it's handle data processing model selection so we are able to analyse customer engagement and purchase history
I use Vertex AI to solve the problems of finding insight from multiple pdf document using a generative AI chatbot, GCP Document AI used for OCR which is costlier we later realized then we used their Gemini model as a large language model for answer generation but it also failed in generating answer at production, overall i am not satisfied with the Vertex AI services. It is ok for POC but not for production.
Pros
Document AI is good at extracting content from pdf
Model Garden is a good option for exploring different models at one place.
Kubeflow pipeline for automating training and serving model
Cons
their Large language model accuracy
vector index creation time is at least 40 mins which is not good
Model garden should include OpenAI integration
Likelihood to Recommend
I generally don't recommend Vertex AI because of some previous failure experience their large language model is not good enough. i can only recommend their document AI which is quite good but pricing is too high. They should also improve their text to speech model just like elevenlabs.com if it is done then we can use it as a call center bot.
Vertex AI is a very useful tool for us, it simplifies automation by consolidating functionalities for engineers and data scientists, aiding in model deployment, tweaking and monitoring. It also allows gpu allocation for cost management and is compatible with Google Cloud services, plus it has a user friendly interface and robust documentation. Lastly just like any other google service, it is both scalable and ideal for team collaboration which makes it a very valuable tool for AI development.
Pros
It simplifies automation by consolidating functionalities at one place.
Can allocate cpu, gpu and memory for cost management.
Friendly interface and has very good documentation.
Compatible with google cloud services and is scalable.
Cons
Though we can manage our cost by manually allocating resources, it is still very costly and should reduce or change their pricing structure.
Less customization so if you're an advanced user, you may face some limitation.
Likelihood to Recommend
We needed to build some ML models and Vertex AI is one such place where all the functionalities are consolidated for model deployment, tweaking and monitoring. And although it is costly, it is compatible with google cloud services and is scalable which makes it the perfect tool for us.
