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What is Digital Twin Streaming Service?

The ScaleOut Digital Twin Streaming Serviceâ„¢ enables the effortless development and implementation of real-time digital twins tailored for sophisticated streaming analytics. By connecting to a wide range of data sources, including Azure and AWS IoT hubs and Kafka, it significantly improves situational awareness through live, aggregated analytics. This cutting-edge cloud service can simultaneously monitor telemetry from millions of data sources, delivering immediate and comprehensive insights with state-tracking and targeted real-time feedback for various devices. Its intuitive interface simplifies deployment and presents aggregated analytics in real time, which is crucial for optimizing situational awareness. The service is adaptable for a broad spectrum of applications, such as the Internet of Things (IoT), real-time monitoring, logistics, and financial sectors. An easy-to-understand pricing model ensures a swift and hassle-free initiation. Additionally, when used in conjunction with the ScaleOut Digital Twin Builder software toolkit, the service sets the stage for an advanced era of stream processing, enabling users to harness data more effectively than ever before. This powerful combination not only boosts operational efficiency but also cultivates new opportunities for innovation across different industries, driving progress and transformation in the way businesses operate.

What is Digital Twin Studio?

The Data-Driven Digital Twin toolkit enables real-time visualization, monitoring, and optimization of operations through the use of machine learning and artificial intelligence, effectively managing costs associated with SKUs, resources, automation, equipment, and more. Featuring Digital Twin Shadow Technology, this system provides real-time visibility and traceability via its Open Architecture, allowing seamless interaction with various RTLS and data systems, including RFID, barcode, GPS, and various management software like WMS, EMR, ERP, and MRP. With the integration of AI and machine learning, users benefit from predictive analytics and dynamic scheduling, as the technology offers timely insights and alerts about potential issues before they escalate. Additionally, the Digital Twin Replay feature allows users to revisit past events and configure active alerts, while the Digital Twin Studio supports the playback and animation of these events in virtual reality, 3D, and 2D formats. Furthermore, the tool provides dynamic dashboards with a user-friendly drag-and-drop builder, offering limitless customization options for data presentation and analysis. This comprehensive digital twin solution empowers organizations to enhance efficiency and gain deeper insights into their operational processes.

Media

Media

No images available

Integrations Supported

AWS IoT
Amazon Web Services (AWS)
Apache Kafka
Microsoft Azure

Integrations Supported

SQL

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS
Windows
On-Prem

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

ScaleOut Software

Date Founded

2003

Company Location

United States

Company Website

www.scaleoutsoftware.com/products/digital-twin-streaming-service/

Company Facts

Organization Name

CreateASoft

Date Founded

1992

Company Location

United States

Company Website

www.createasoft.com

Categories and Features

Digital Twin

Not specified

Streaming Analytics

Not specified

Categories and Features

AI Manufacturing

Not specified

Digital Twin

Not specified

Machine Learning

Deep Learning
Model Training
Predictive Modeling
Statistical / Mathematical Tools
Visualization

Manufacturing Intelligence

Aggregation
Analysis
KPIs
Propagation
Visualization

RFID

Not specified

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