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Google Cloud AI Platform pros and cons

Vendor: Google
3.9 out of 5

Pros & Cons summary

Buyer's Guide

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Prominent pros & cons

PROS

Google Cloud AI Platform offers a vast amount of services, including a load balancer and AI architecture.
It allows for the exposure of API services, accommodating both individual records and batches.
The platform efficiently processes documents with a high accuracy rate.
Models can be trained in hours and deployed within minutes, optimizing the process time.
Google Vision API on the platform is highly valued for its capabilities.

CONS

Initial setup may be straightforward for some but difficult for others.
Customizations are difficult and time-consuming.
Errors are not always clear and understandable.
Azure ML lacks direct feature parity with Google Cloud AI Platform.
Improvements are needed in text extraction accuracy and pricing adjustments.
 

Google Cloud AI Platform Pros review quotes

reviewer2214366 - PeerSpot reviewer
Jun 20, 2023
I think the user interface is quite handy, and it is easy to use as compared to the other cloud platforms.
BC
Jun 12, 2023
The initial setup is very straightforward.
VijayVelpula - PeerSpot reviewer
Apr 30, 2022
On GCP, we are exposing our API services to our clients so that they send us their information. It can be single individual records or it can be a batch of their clients.
Find out what your peers are saying about Google, Microsoft, IBM and others in AI Development Platforms. Updated: December 2024.
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TJ
Sep 16, 2022
The solution is able to read 90% of the documents correctly with a 10% error rate.
Marta Frąckowiak - PeerSpot reviewer
Apr 20, 2023
Since the model could be trained in just a couple of hours and deploying it took only a few minutes, the entire process took less than an hour.
Vipul-Kumar - PeerSpot reviewer
Nov 3, 2023
A range of a a wide range of algorithms, EIM voice mails, which can be plugged in right away into your solution into into into our solution, and then have platform that provides know, to to come up with an operational solution really quick.
HaiPham - PeerSpot reviewer
Jul 25, 2024
The platform's Google Vision API is particularly valuable.
NM
Mar 1, 2021
Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture.
 

Google Cloud AI Platform Cons review quotes

reviewer2214366 - PeerSpot reviewer
Jun 20, 2023
One thing that I found is that Azure ML does not directly provide you with features on Google Cloud AI Platform, whereas Vertex provides some features of the platform.
BC
Jun 12, 2023
Customizations are very difficult, and they take time.
VijayVelpula - PeerSpot reviewer
Apr 30, 2022
At first, there were only the user-managed rules to identify the best attributes of the individual. Then, we came up with a truth set and developed different machine learning models with the help of that truth set, so now it's completely machine learning.
Find out what your peers are saying about Google, Microsoft, IBM and others in AI Development Platforms. Updated: December 2024.
824,067 professionals have used our research since 2012.
TJ
Sep 16, 2022
The solution can be improved by simplifying the process to make your own models.
Marta Frąckowiak - PeerSpot reviewer
Apr 20, 2023
It could be more clear, and sometimes there are errors that I don't quite understand.
Vipul-Kumar - PeerSpot reviewer
Nov 3, 2023
I think it's the it it also has has evolved quite a bit over the last few years, and Google Cloud folks have been getting, more and more services. But I think from a improvement standpoint, so maybe they can look at adding more algorithms, so adding more AI algorithms to their suite.
HaiPham - PeerSpot reviewer
Jul 25, 2024
Improvements in text extraction accuracy and pricing adjustments would be helpful.
NM
Mar 1, 2021
The initial setup was straightforward for me but could be difficult for others.