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Google Cloud AI

Score8.6 out of 10

88 Reviews and Ratings

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What is Google Cloud AI?

Google Cloud AI provides modern machine learning services, with pre-trained models and a service to generate tailored models.

Categories & Use Cases

Reviews

What users are saying about Google Cloud AI.
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Best ratio tool/price

Luis DoroView profile
Director of Accounting in Finance and Accounting at SWORD Health (501-1000 employees employees)

Use Cases and Deployment Scope

It´s used to archive of all fundamental data of the company, so it´s crucial to have one source of truth through all the group. It´s individual member can access there, all the necessary data to perform his work.

Pros

  • Storage of information
  • Facility to share info with others
  • Although you can easily share data you can also maintain the proper controls

Cons

  • Use AI for recognizing documents in several languages
  • Use AI to help properly storage docs

Return on Investment

  • Avoiding storage in paper
  • Ease to share docs with internal/external stakeholders

Usability

Other Software Used

LinkedIn Sales Navigator for Gmail, Google Ads, Google Analytics

Leader of AI APIs and Tools Google Cloud AI

Incentivized
Narender SharmaView profile
Founder in Information Technology at Blue Particle Solutions (11-50 employees employees)

Use Cases and Deployment Scope

I am working on different AI projects for Voice, Sound, Speech, and Images. Google Cloud AI Speech recognition and Image content analysis is the most useful AI API that I have worked with. Benefits are Auto machine learning, easy to train your modules so as the interface is easy to understand, response is quick. That's what we know Google for. Quick and Quality.

Pros

  • Easy to Train your model
  • Auto machine learning
  • Vetrex is Cool
  • Support wide range of platforms

Cons

  • My billing account keeps suspending cause of Indian Mendate. So that's the only thing that is frustrating to me.

Most Important Features

  • Speech Recognition
  • Image Analysis

Return on Investment

  • It's all good not that expensive.
  • I am using many cloud APIs from Roadmetrix to AI all of them are more than what I am spending.

Alternatives Considered

Speechpad, ListNote Speech-to-Text Notes, Speechnotes and ImageKit.io

Other Software Used

Speechnotes, Speechpad, ImageKit.io

Hard to onboard, great API product from Google!

Incentivized
Fedor ParetskyView profile
Co-Founder/CEO in Engineering at aspace, Inc. (1-10 employees employees)

Pros

  • New products - Google is constantly releasing and adding new products to this API, it seems to be on of the fastest-growing products for this.
  • Speed - The API is a lot faster than most of the alternative Computer Vision and general-use Machine Learning APIs out there.
  • Comprehensive results - The results the API returns for most of the products don't require recurring API requests for processing. Everything is included and organized exactly in the JSON response as mentioned in their documentation for most of these Cloud AI products.
  • The documentation format for this API is much better than some of Google's other documentation.

Cons

  • Hard to find what to use - To find the right products, you need look closely at the details of each API, and find which suits your purposes. This can be easily fixed by creating a main page that details all of the products simply.
  • Expensive - The API costs can quickly add up, especially during the setup process and as engineers figure out the usage of the API.
  • No playground or training - There is a lack of an "API playground" or training sessions that could make onboarding engineers to this API much easier.

Return on Investment

  • Positive - We offset the processing power we needed locally by moving Cloud Vision and ML processing to cloud APIs.
  • Negative - Pricing. This was expensive to setup at the beginning, but later, the price of this API became more constant.
  • Negative - There was quite a difficult learning curve for this product, one that took a lot of time to figure out.

Alternatives Considered

Microsoft Azure Machine Learning Workbench

Other Software Used

IBM Watson IoT, IBM Watson Explorer, TensorFlow

The right technology can help your business!

Incentivized
Marlon SeijasView profile
analista in Finance and Accounting at Consejo Federal de Gobierno (201-500 employees employees)

Pros

  • good conversion from the voice to the text
  • speed in the conversion from voice to text
  • time-saving in the conversion activity
  • analysis of the results of the conversion in real time

Cons

  • really this application so far has been very useful.
  • we believe that it could be better using other forms apart from the microphone.
  • I believe that this application can be merged with another in a way that throws general data on the topics investigated.

Return on Investment

  • the first results to take into account is the significant saving of time in our laborious activities
  • this tool has allowed us to optimize our work by duplicating our effort to develop statistics so that our research department can throw the solutions to the problems posed
  • when we save time and we can use this time lapse to respond more immediately to the environment of our business everything becomes profit
  • something that we can not ignore is that with the Google application we have adjusted for the benefit of all the lifeline of the project and its objectives

Alternatives Considered

Amazon Cloud Drive and Microsoft Azure

Other Software Used

Workplace by Facebook (Formerly Facebook at Work), IBM Cognos, Alteryx Analytics, Dropbox

Usability

Google Cloud AI Review

Incentivized
Verified User
Analyst in Information Technology (51-200 employees employees)

Pros

  • Google Cloud AI was easy to set-up without need for lot of customization and configuration.
  • It integrates very well with the Google BigQuery and Google PubSub that makes it easy to have a ready to use pipeline from data ingestion to analysis.
  • Google Cloud AI has out of the box CV algorithms and video processing modules/APIs that makes is easy to use for image/video processing application and use cases.

Cons

  • Some of the build in/supported AI modules that can be deployed, for example Tensorflow, do not have up-to-date documentation so what is actually implemented in the latest rev is not what is mentioned in the documentation, resulting in a lot of debugging time.
  • Customization of existing modules and libraries is harder and it does need time and experience to learn.
  • Google Cloud AI can do a better job in providing better support for Python and other coding languages.

Return on Investment

  • Positive impact on ROI due to reduction in staff needed to build, deploy and manage a AI workload pipeline.
  • Positive impact on the business by moving to OpEx without need for upfront CapEx investment.
  • Improvement in time to analyze the data (structured and unstructured), increasing the business's ability to act based on AI results.

Alternatives Considered

Microsoft Azure and IBM Watson Analytics

Other Software Used

Google Analytics, Google BigQuery, Microsoft Azure