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What is Kazuhm?

By the year 2025, it is anticipated that the Internet of Things (IoT) will comprise 41 billion devices capable of producing over 76 zettabytes of data. In response, organizations are increasingly adopting IoT strategies aimed at boosting manufacturing productivity and prioritizing employee safety. A variety of industries, such as utilities, agriculture, energy, and healthcare, are harnessing interconnected sensor networks to collect a wide range of observable and actionable insights. Nevertheless, to fully realize the benefits of IoT projects, it is essential for data to be processed rapidly enough to impact decision-making in microseconds. Furthermore, managing the costs tied to data processing and storage is vital for organizations seeking a solid return on investment. To address these challenges, a groundbreaking distributed computing technology known as Kazuhm has emerged, designed to process IoT data directly within networks on the originating devices, which facilitates ultra-low latency and lowers costs compared to conventional cloud or edge solutions. This cutting-edge method not only streamlines data management but also equips companies to react to real-time information with greater efficiency and agility. Ultimately, the integration of such technologies could redefine how businesses operate and respond to the dynamic demands of their industries.

What is Azure Digital Twins?

Azure Digital Twins serves as an IoT platform enabling the creation of digital replicas of physical entities, spaces, processes, and people. This innovative platform yields critical insights that can significantly improve product development, optimize operational efficiency, lower costs, and enhance customer satisfaction. It provides an intuitive framework for crafting digital representations of interconnected settings using a flexible modeling language. Users can model a wide variety of entities, including buildings, manufacturing plants, agricultural fields, energy systems, transportation networks, sports facilities, and even entire cities. These digital twins come alive in a dynamic execution environment that monitors changes over time. By utilizing powerful query APIs, users can glean actionable insights into the behaviors of their modeled environments and easily integrate with Azure's data analytics services. The open modeling language allows for the creation of customized domain models tailored to any connected setting through the Digital Twins Definition Language, ensuring adaptability across various applications. Thus, Azure Digital Twins not only supports business innovation but also enables organizations to adjust effectively in an ever-evolving digital landscape, making it an invaluable tool for modern enterprises.

Media

Media

Integrations Supported

Azure Marketplace
ICONICS' Intelligent Building Software (IBSS)
Microsoft Azure

Integrations Supported

Azure Marketplace
ICONICS' Intelligent Building Software (IBSS)
Microsoft Azure

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Kazuhm

Date Founded

2017

Company Location

United States

Company Website

www.kazuhm.com

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/services/digital-twins

Categories and Features

IoT

Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization

Categories and Features

IoT

Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization

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