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What is Sandhed?

Sandhed functions as a digital twin platform designed specifically for manufacturers, enabling users to upload their facility's layouts to construct an interactive 3D space that showcases real-time sensor information, equipment conditions, and asset placements. The platform integrates effortlessly with more than 150 industrial protocols, including OPC UA, MQTT, and Modbus, guaranteeing it works well with the existing PLCs and sensors at the site. Users can ask operational questions in plain language and obtain instant answers derived from live data. Furthermore, by capturing images of any machinery, the AI can create a matching 3D model, enhancing visualization. The system also features maintenance management tools, which include 19 compliance templates that facilitate adherence to regulations. Founded in Copenhagen and now operating from Malta, Sandhed is broadening its presence in the field of digital manufacturing solutions. This cutting-edge strategy empowers manufacturers to significantly improve their operational efficiency and enhance their decision-making capabilities. Ultimately, Sandhed stands out as a transformative tool in the manufacturing sector, promoting smarter operations and innovative practices.

What is GE Digital Twin?

Employing advanced analytics and machine learning methodologies is vital for reducing operational costs and alleviating risks. Digital twins, a key element of the digital transformation journey, offer exact virtual models of physical assets, systems, and objects that aim to improve productivity, streamline processes, and boost profitability. Generally, a digital twin is seen as a software representation of a tangible asset or system designed to identify, prevent, forecast, and enhance operations through real-time data analysis, ultimately providing considerable advantages for businesses. At GE Digital, we focus on utilizing digital twin software to support our clients across three essential areas: Asset, Network, and Process. By adeptly overseeing, simulating, and controlling an asset or process, organizations can greatly improve system performance. Moreover, it is imperative to prioritize the health and safety of employees and the environment while pursuing business objectives, which entails reducing incidents associated with assets and processes and avoiding unexpected downtimes, thus nurturing a more robust operational structure. The adoption of digital twin technology not only boosts efficiency but also opens doors for innovation across numerous industries. As organizations embrace this technology, they position themselves for sustained growth and competitive advantage in an ever-evolving marketplace.

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Integrations Supported

APERIO DataWise

Integrations Supported

APERIO DataWise

API Availability

Has API

API Availability

Has API

Pricing Information

€499
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

Sandhed

Date Founded

2026

Company Location

Malta

Company Website

sandhed.com

Company Facts

Organization Name

GE Digital

Date Founded

2015

Company Location

United States

Company Website

www.ge.com/digital/applications/digital-twin

Categories and Features

Categories and Features

Simulation

1D Simulation
3D Modeling
3D Simulation
Agent-Based Modeling
Continuous Modeling
Design Analysis
Direct Manipulation
Discrete Event Modeling
Dynamic Modeling
Graphical Modeling
Industry Specific Database
Monte Carlo Simulation
Motion Modeling
Presentation Tools
Stochastic Modeling
Turbulence Modeling

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