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Amazon Web Services (AWS)

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18,243 reviews
  • 445 profiles
  • 221 categories
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4.4
#1 in 34 categories
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Serving customers since
2006
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AWS SimSpace Weaver

1 review

AWS SimSpace Weaver is a fully managed compute service designed to help users build and operate large-scale spatial simulations in the cloud. It enables the creation of complex, dynamic 3D environments with millions of interacting entities, such as vehicles, people, and devices, all in real time. By distributing simulation workloads across multiple Amazon EC2 instances, SimSpace Weaver allows for the modeling of expansive scenarios like city-scale traffic patterns, crowd movements, and immersive training environments. This service abstracts the complexities of infrastructure management, including provisioning, networking, and data synchronization, allowing developers to focus on simulation logic and content creation. Additionally, SimSpace Weaver integrates seamlessly with popular development tools like Unreal Engine and Unity, facilitating a streamlined development process. However, it's important to note that AWS has announced the discontinuation of support for SimSpace Weaver, effective May 20, 2026. After this date, the service will no longer be accessible. Key Features: - Managed Infrastructure: Automatically handles the deployment and management of simulation infrastructure, scaling across multiple Amazon EC2 instances without user intervention. - Spatial Partitioning: Divides the simulation world into discrete areas, each managed by a dedicated application, enabling efficient handling of large-scale environments. - Cross-Instance Data Replication: Maintains global state awareness of all simulated entities, ensuring seamless interaction and movement across different simulation areas. - Integration with Development Tools: Offers built-in support for Unreal Engine 5 and Unity, allowing developers to leverage existing tools and assets in their simulations. - Local Development Environment: Provides a local environment for testing and iterating simulations on personal hardware before scaling in the cloud, using consistent APIs for easy transition. Primary Value and Solutions: AWS SimSpace Weaver addresses the challenges of creating and managing large-scale spatial simulations by providing a scalable, managed infrastructure that simplifies the development process. It enables organizations to model complex, real-world scenarios—such as urban planning, emergency response, and large event management—without the need for extensive hardware investments or infrastructure management. By facilitating real-time interactions among millions of entities, SimSpace Weaver allows users to gain valuable insights, perform immersive training, and make informed decisions based on simulated outcomes. The service's integration with popular development tools and its local development environment further streamline the simulation creation process, making it accessible and efficient for developers.

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ELECTRA-Base++ TensorFlow Hub Sentence Pair Classification

1 review

This is a Sentence Pair Classification model built upon a Text Embedding model from TensorFlow Hub

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EfficientNet B0 Lite

1 review

It takes an image as input and classifies the image to one of the multiple classes. The model available for deployment is pre-trained on ImageNet which comprises images of different classes. The model predicts classes including the additional class for background. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

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SSD EfficientDet D1

1 review

It takes an image as input and returns bounding boxes for the objects in the image. The model is pre-trained on COCO 2017 which comprises images with multiple objects and the task is to identify the objects and their positions in the image. A list of the objects that the model can identify is given at the end of the page. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

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ResNet 50

1 review

This is a Image Classification model from TensorFlow Hub

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DistilBERT Base Uncased

1 review

This is a Sentence Pair Classification model built upon a Text Embedding model from PyTorch Hub

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VGG-13

1 review

It takes an image as input and classifies the image to one of the multiple classes. The model available for deployment is pre-trained on ImageNet which comprises images of different classes. PyTorch, the PyTorch logo and any related marks are trademarks of Facebook, Inc.

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VGG 16

1 review

This is a Image Classification model from PyTorch Hub

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AWS Elemental Conductor

1 review

AWS Elemental Conductor is a video network management system for file-based and live video delivery applications. The software-based solution offers high availability, secure administration and comprehensive monitoring of video encoding and delivery tasks through an easy-to-use web-based user interface.

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Amazon Web Services (AWS) Reviews

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Profile Name
Star Rating
11948
5313
731
146
96
rupali j.
RJ
rupali j.
--CA Finalist ll Audit Associate @crowe II Ex- BDO Rise Pvt Ltd
09/16/2026
Validated Reviewer
Review source: G2 invite
Incentivized Review
Translated Using AI

Easy, Scalable Text Insights with Amazon Comprehend

What I like most about Amazon Comprehend is how easy it is to extract insights from large amounts of text without needing complex machine learning expertise. It saves time, scales efficiently, and helps automate tasks such as sentiment analysis, entity recognition, and document classification with reliable results.
KESHAV B.
KB
KESHAV B.
Chartered Accountant (Jan’26) | Senior Associate @ EXO Edge | R2R | MIS | Assurance | Tax | Financial Analysis | SAP | Workday | Tally | MS Excel | CaseWare - Driving Accurate Closures & Insightful Financial Decisions
09/16/2026
Validated Reviewer
Review source: G2 invite
Incentivized Review
Translated Using AI

Accurate Sentiment Insights with Seamless AWS Integration

Amazon Comprehend makes it easy to understand and analyze large amounts of text without building complex AI models from scratch. I particularly appreciate its accurate sentiment analysis, entity recognition, and seamless integration with the AWS ecosystem, which helps save time and improve efficiency in data-driven projects.
MD
Marco D.
09/16/2026
Validated Reviewer
Verified Current User
Review source: G2 invite
Incentivized Review

Flexible, Well-Documented Scaling - But Pricing Can Get Steep

First: Amazon EC2's wide availability allows for a large number of first and third party tools for integrating the service with other services. Everything is well documented by Amazon themselves or by third parties.<br><br>Second: For our use case we needed to scale to a large number of compute instances rapidly which EC2 made possible. I also appreciate the flexibility of scaling down as quickly as we scaled up if needed.<br><br>Third: We initially focussed on a single European market, but Amazon's global reach allows our tech stack to easily enter different markets to, for example, be compliant with that markets compliance requirements.

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What is Amazon Web Services (AWS)?

Amazon Web Services (AWS), a subsidiary of Amazon, is a leading cloud computing platform that provides a wide range of on-demand services such as computing power, data storage, databases, networking, and artificial intelligence tools. It enables businesses to build, deploy, and scale applications without investing in physical infrastructure, using a flexible pay-as-you-go pricing model. With a global network of data centers, AWS supports organizations of all sizes—from startups to large enterprises—by offering reliable, secure, and highly scalable solutions for modern digital operations.

Details

Year Founded
2006
Ownership
NASDAQ: AMZN
Website
aws.amazon.com