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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 Actcast?
Actcast is an innovative AI-driven IoT platform that effectively bridges the gap between real-world events and the Internet by performing deep learning inference on edge devices, enabling instant detection, analysis, and integration of physical data with online systems while reducing data transfer costs and addressing privacy issues. Utilizing edge computing, it empowers the execution of sophisticated deep learning models on cost-effective hardware such as Raspberry Pi, transforming raw data collected from sensors and cameras into valuable, semantic information that can be communicated to web services or applications. The platform is built to facilitate the deployment, remote oversight, and monitoring of various IoT applications, known as "Acts," across multiple devices, providing developers with vital resources including an SDK and command-line interface for the creation, packaging, and deployment of applications within Docker containers that interpret input and produce concise outputs. Additionally, Actcast offers features for organizing device clusters, establishing triggers and webhooks for event notifications, and managing updates and device statuses via a centralized dashboard, thus promoting a more efficient and streamlined IoT experience. This holistic strategy not only boosts operational efficiency but also significantly enhances the scalability of IoT solutions, making it a valuable asset for developers looking to innovate in the field. Ultimately, Actcast serves as a transformative tool for harnessing the power of IoT in contemporary applications.
Integrations Supported
Raspberry Pi OS
Slack
X (Twitter)
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
Actcast
Date Founded
2018
Company Location
United States
Company Website
actcast.io
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