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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 AtomBeam?
There is no requirement to buy any hardware or alter your network setup, as installation is simply a matter of easily configuring a compact software library. By 2025, forecasts suggest that an astonishing 75% of the data created by enterprises, which amounts to 90 zettabytes, will be generated by IoT devices. For context, the total storage capacity of all data centers worldwide is currently less than two zettabytes combined. Alarmingly, 98% of IoT data is left unsecured, highlighting the urgent need for robust protection measures. Additionally, there are ongoing worries about the lifespan of sensor batteries, with few viable solutions expected to emerge soon. Many users also face challenges related to the restricted range of wireless data transmission. We envision that AtomBeam will transform the IoT landscape in a way similar to how electric light changed everyday experiences. Several obstacles hindering the broader acceptance of IoT can be overcome through the seamless implementation of our compaction software. By leveraging our technology, users can improve security, extend battery life, and broaden transmission capabilities. Furthermore, AtomBeam offers a significant opportunity for businesses to reduce costs associated with both connectivity and cloud storage, making it a highly attractive choice for those prioritizing efficiency. As IoT demand continues to climb, our innovative solutions provide a timely and effective response to the fast-evolving technological environment. In this way, we aim to not only address current challenges but also pave the way for a more interconnected future.
Integrations Supported
Additional information not provided
Integrations Supported
Additional information not provided
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
AtomBeam
Company Location
United States
Company Website
atombeamtech.com
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
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization