Suppliers > China > DataMesh


DataMesh Logo
HQ Location
Year Founded
Company Type
51 - 200
Twitter Handle
Company Description

DataMesh enterprise-level cognitive platform and application uses advanced Machine Learning and natural language analysis, mixed reality and other technical means to dig deep into the Unstructured Data of enterprises and provide high-quality collaborative information to front-line workers. Cognitive level, improving the delivery ability of enterprises in many aspects such as maintenance inspection, teaching and training, remote guidance, design and survey, brand marketing, etc., is an indispensable component of enterprise Digital Transformation.

IoT Solutions

Industry 4.0 & Digital Twin Based on product lifecycle data, DataMesh simulates, evaluates and optimizes the production process and further extends the entire product lifecycle management to help manufacturing companies build new ways of organizing production. The DataMesh Industrial PaaS platform combines enterprise CAD applications with an efficient 3D training editor to quickly build training and simulation scenarios through mixed reality, helping multi-users to build Digital Twin solutions based on real-world simulation of operational steps and interactions. Smart City & BIM DataMesh Mixed Reality platform enables Smart City solutions to quickly create compelling storyboard for their presentations. Connected with DataMesh DataMix, IoT data can be further leveraged to create Digital Twin of the city. Interactive Mixed Reality DataMesh MR brand marketing solution uses DataMesh Live!, DataMesh Director and other products, and based on the user’s real scene, through 3D modeling to reproduce the real work scene. Different from the AR/VR scene, the mixed reality scene combines technologies such as large spatial positioning to make the display effect more realistic.

Key Customers

Porsche,Daimler, Mercedes-Benz Beijing, Deloitte, Glodon, Microsoft

Technology Stack
DataMesh’s Technology Stack maps DataMesh’s participation in the application infrastructure and middleware, and analytics and modeling IoT Technology stack.
  • Devices Layer
  • Robots
  • Edge Layer
  • Automation & Control
    Processors & Edge Intelligence
  • Cloud Layer
  • Platform as a Service (PaaS)
    Infrastructure as a Service (IaaS)
  • Application Layer
  • Functional Applications
  • Supporting Technologies
  • Analytics & Modeling
  • Application Infrastructure & Middleware
  • Cybersecurity & Privacy
  • Networks & Connectivity
Technological Capability:

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