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User-Friendly AI Solution
March 19, 2024

User-Friendly AI Solution

Anonymous | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with Vertex AI

Vertex AI is Google's Machine Learning Platform that helps to streamline diverse machine learning tasks and help build ML models. Our organization uses Vertex AI to measure project performance and predict customer behavior so as to make more accurate forecasts. It is extremely user-friendly and is accessible to users with different levels of training.
  • It allows for customization of LLMs.
  • It makes machine learning accessible to non-developers.
  • One can create models without extensive coding.
  • It does have lower capacities to digest data compared to other platforms.
  • Many of the features are available only for paid users, which is costly. So it may not make sense for a smaller enterprise.
  • The customer support for the platform can be improved.
  • Since the platform can be used by non-developers, it has made the forecast modelling process in our company far more efficient.
  • Since it is a cloud based platform, it has improved collaboration among colleagues.
  • It has helped marketing to better target customers.
Vertex AI is much more accessible to non-developers than IBM's product. Moreover, Vertex AI integrates well with other Google products, enhancing its capabilities. A big plus is its integration with cloud storage, that allows for better management and access of data. In all honesty, it wasn't much of a difficult choice to choose Vertex AI.

Do you think Vertex AI delivers good value for the price?

Yes

Are you happy with Vertex AI's feature set?

Yes

Did Vertex AI live up to sales and marketing promises?

Yes

Did implementation of Vertex AI go as expected?

Yes

Would you buy Vertex AI again?

Yes

You can user Vertex AI to create predictive models if you are working with smaller data sets. For example, if you want to customize user experiences for a website based on past behavior. However, if you want to make regional or global sales forecasts, predictive models that needs large amounts of data, the platform is not suitable.