Google Vertex AI Reviews

Google Vertex AI is praised for its ease of use, facilitating model deployment, and integration capabilities. Users value the Feature Store for centralizing features, monitoring for model performance, and seamless integration with Google and external systems. The use of Gemini enhances model capabilities, while the platform's flexibility supports both low-code and detailed customization. Integration with CRM and ERP systems, ease of use, and end-to-end management make it highly appealing.

• "The best feature of Google Vertex AI is the ease of use, along with the integration with the rest of the Google ecosystem and the way models can be made available outside Google through endpoints."
• "The most useful function of Google Vertex AI for me is the ease of integration, as we can easily create a prompt and integrate it into our current system."
• "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."

Google Vertex AI requires enhancements in user interface, optimization, and accessibility for non-technical users. Documentation is insufficient, potentially hindering user comprehension. Chat activity for queries is limited in scope. Additional features such as image generators, text-to-speech solutions, and integration with BigQuery and enterprise systems are desired. Improved model efficiency through streamlined training and fine-tuning options, better AutoML processing times, and comprehensive customer support are also necessary. Knowledge building with expanded information sources is crucial.

• "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."
• "We used AutoML feature for developing AI models automatically, but we are not comfortable with the performance of those models."
• "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."