Nexus Overview

Connect  to virtually any data source, OT systems like PLC, SCADA, MES or Robotics.  

Connect to standalone IoT devices measuring temperature, humidity, flow or vibration.  

Connect to barcode scanners for traceability or Computer Vision cameras for streaming video or quality control operations.  

Connect to companywide UNS Broker for access to enterprise real-time data. 

Connect to FTP or file shares to either transfer or analyze files at edge or cloud.

Collect  data from data sources, validate, aggregate, and consolidate information, add metadata for further enrichment and contextualization of data, and assign data in the asset hierarchy for unified structure.  

Structure data according to ISA 95.2 and use the unified asset hierarchy to handle deployment to many edge devices and automatic connection to data sources.  

Use Nexus Management Portal for configuration or integrate through extensive Api support to 3rd party systems, for fully automated workflows.

Process  data before storing in cloud. Optionally aggregate and compress data before storing in cloud for increased performance and operational cost optimization.

Store  data in the cloud to one or more endpoints/historians, including Datalake, SQL databases, Azure Data Explorer and more.  

Ingest real-time data to companywide UNS Broker for access to all IIoT real-time data from other systems. 

Tricloud Nexus features a Module and Application store, that enables automated deployment of containers from cloud to edge, for execution in a near real-time environment.

You can build applications in the platform based on a selection of multiple modules, thereby packaging a set of modules for a specific use-case. 3rd party containers can be imported as modules to the platform as well.  

All modules and apps are handled with full traceability and versioning, making it easy to re-deploy to previous versions if necessary.  

By having a module and application store you get full control of your deployed solution and gain the possibility to deploy eg. AI algorithms to the edge on a continuous basis. This easily deployment of new improved models will help accelerate your continuous improvement efforts.