Amazon Augmented AI vs TensorFlow comparison

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Amazon Augmented AI

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Executive Summary

We performed a comparison between Amazon Augmented AI and TensorFlow based on real PeerSpot user reviews.

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Amazon Augmented AI

Ranking in AI Development Platforms

16th

Average Rating

8.0

Reviews Sentiment

6.1

Number of Reviews

Ranking in other categories

No ranking in other categories

TensorFlow

Ranking in AI Development Platforms

6th

Average Rating

8.8

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2025, in the AI Development Platforms category, the mindshare of Amazon Augmented AI is 0.5%, down from 0.6% compared to the previous year. The mindshare of TensorFlow is 3.8%, down from 7.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

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Featured Reviews

reviewer2648256

Works

Automation reduces costs and boosts efficiency in financial tasks

I use Amazon Augmented AI for voice recognition and emotion recognition when I receive numerous emails, which are often not worth replying to. I rectify this with machine learning tools. I work in the financial industry, specializing in banks, insurance companies, government, and more The most…

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Ashish Upadhyay

Founder at BlockMosiac

A robust tools for model visualization and debugging with superior scalability and stability, and an intuitive user-friendly interface

The one feature we find most valuable at our company is its robust and flexible machine-learning capabilities. It empowers us to seamlessly create and deploy machine learning models, offering a versatile solution for implementing sophisticated environments and various types of AI solutions. The ability to develop and fine-tune models, such as risk assessment for detection and market protection, as well as the creation of recommendation systems, is paramount. This versatility extends to providing personalized identity-relevant applications for our enterprise clients, delivering valuable insights to the market. Its exceptional support for deep learning and its efficient resource utilization enable us to undertake complex financial and data analyses. The flexibility it provides is crucial for meeting industrial requirements and crafting solutions tailored to our client's specific needs.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The most valuable feature of Amazon Augmented AI is its automation capability."

"It provides us with 35 features like patch normalization layers, and it is easy to implement using the Kras library when the Kaspersky flow is running behind it."

"TensorFlow is an efficient product for building neural networks."

"TensorFlow is easy to implement and offers inbuilt functions for various tasks."

"Our clients were not aware they were using TensorFlow, so that aspect was transparent. I think we personally chose TensorFlow because it provided us with more of the end-to-end package that you can use for all the steps regarding billing and our models. So basically data processing, training the model, evaluating the model, updating the model, deploying the model and all of these steps without having to change to a new environment."

"TensorFlow improves my organization because our clients get a lot of investment from their investors and we are progressively improving the products. Every six months we release new features."

"Optimization is very good in TensorFlow. There are many opportunities to do hyper-parameter training."

"The available documentation is extensive and helpful."

"The most valuable features are the frameworks and the functionality to work with different data, even when we have a certain quantity of data flowing."

More TensorFlow pros

Cons

"The development support, costing twenty-nine dollars per month, is almost ineffective, with long email response times."

"There needs to be continuous monitoring and improvement, especially regarding security issues, to address threats from hackers."

"I know this is out of the scope of TensorFlow, however, every time I've sent a request, I had to renew the model into RAM and they didn't make that prediction or inference. This makes the point for the request that much longer. If they could provide anything to help in this part, it will be very great."

"In terms of improvement, we always look for ways they can optimize the model, accelerate the speed and the accuracy, and how can we optimize with our different techniques. There are various techniques available in TensorFlow. Maintaining accuracy is an area they should work on."

"It doesn't allow for fast the proto-typing. So usually when we do proto-typing we will start with PyTorch and then once we have a good model that we trust, we convert it into TensorFlow. So definitely, TensorFlow is not very flexible."

"It would be cool if TensorFlow could make it easier for companies like us to program for running it across different hyperscalers."

"We encountered version mismatch errors while using the product."

"I would love to have a user interface like a programming interface. You need to have a set of menus where you can put things together in a graphical interface. The complete automation of the integration of the modules would also be interesting. It’s more like plumbing as opposed to a fully automated environment."

"TensorFlow deep learning takes a lot of computation power. The more systems you can use, the easier it is. That's a good ability, if you can make a system run immediately at the same time on the same task, it's much faster rather than you having one system running which is slower. Running systems in parallel is a complex situation, but it can improve. There is a lot of work involved."

"For newcomers to the field, the learning curve can be steep, often requiring about a year of dedicated effort."

More TensorFlow cons

Pricing and Cost Advice

Information not available

"I did not require a license for this solution. It a free open-source solution."

"The solution is free."

"I rate TensorFlow's pricing a five out of ten."

"We are using the free version."

"I think for learners to deploy a project, you can actually use TensorFlow for free. It's just amazing to have an open-source platform like TensorFlow to deploy your own project. Here in Russia no one really cares about licenses, as it is totally open source and free. My clients in the United States were also pleased to learn when they enquired, that licensing is free."

"I am using the open-source version of TensorFlow and it is free."

"It is an open-source solution, so anyone can use it free of charge."

"TensorFlow is free."

More TensorFlow pricing and cost advice

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Top Industries

By visitors reading reviews

No data available

Manufacturing Company

14%

Computer Software Company

13%

University

Educational Organization

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What is your experience regarding pricing and costs for Amazon Augmented AI?

The support levels offered by Amazon vary in cost. While the development support is cheap, it is inadequate, and the better support levels depend on usage, such as the number of virtual machines an...

What needs improvement with Amazon Augmented AI?

There needs to be continuous monitoring and improvement, especially regarding security issues, to address threats from hackers. Libraries require more tweaking for ongoing development and improveme...

What is your primary use case for Amazon Augmented AI?

What do you like most about TensorFlow?

It empowers us to seamlessly create and deploy machine learning models, offering a versatile solution for implementing sophisticated environments and various types of AI solutions.

What is your experience regarding pricing and costs for TensorFlow?

I am not familiar with the pricing setup cost and licensing.

What needs improvement with TensorFlow?

Providing more control by allowing users to build custom functions would make TensorFlow a better option. It currently offers inbuilt functions, however, having the ability to implement custom libr...

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Google Vertex AI vs TensorFlow

Compared 17% of the time

PyTorch vs TensorFlow

Compared 12% of the time

Hugging Face vs TensorFlow

Compared 11% of the time

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Product Reports

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Also Known As

Amazon A2I

No data available

Overview

Amazon Augmented AI (Amazon A2I) makes it easy to build the workflows required for human review of ML predictions. Amazon A2I brings human review to all developers, removing the undifferentiated heavy lifting associated with building human review systems or managing large numbers of human reviewers.

Amazon Web Services (AWS)

TensorFlow is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google’s AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains.

Sample Customers

T Mobile, VidMob, Ripcord, NHS BSA

Airbnb, NVIDIA, Twitter, Google, Dropbox, Intel, SAP, eBay, Uber, Coca-Cola, Qualcomm

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