Our Edge gateways are specifically designed for edge use cases to automate and connect devices at the edge. They support M2M and IoT applications, from sensors to connected vehicles, from remote monitoring to smart farms and cities. Our Gateways deployed at the Edge benefit from "low-code" prgramming environment (i.e. NodeRed), open interfaces for 3 rd party modules and standards based interfaces. We’re building a portfolio of high-performance, low-power purpose-built systems that enable edge computing at scale.
Our software platform and soultions are constantly built around the trend that hardware is becoming more and more widley available and interchangeable and that real value is delivered by advanced software techiques/approaches and architectures. In particular we combine cloud and edge computing paradigms and cloud-native technologies to support highly adaptable "Data-driven" applications.
Any "data-driven" approach starts by connecting your physical asset to the enterprise network for embedding data in every decision, interaction and process. Due to the typical heterogenity of hardware, software and protocols, this step requires the design and development of generic and standardized applicationprogramming interfaces (APIs) and communication protocols. We call this step "digitalizing the physical" and is the first step towards the development of "digital twins".
The Asset Administration Shell (AAS) is a standardized digital representation of an asset. Cornerstone of Interoperability between applications (acting like an USB connnector) and the digital basis for autonomous systems and AI applications. An asset is everything that requires and/or could require a connection to an Industrie 4.0 based solution. The AAS is the implementation of the “Digital Twin” concept for Industrie 4.0. It holds digital models describing various aspects of the asset (data image of the asset). We are embracing the fourth industrial revolution since our solutions deeply rely on the AAS concept as the necessary mechanism to enable the data extraction and provisioning in real-time from physical asset.
We are experienced in helping and guiding our clients in identifying the capabilities they need. This is the foundation of our ML models developement strategy where we deliver mainly three options that can differ from client to client: to build fully tailored ML models open-source third-party libraries, to integrate state-of-the-art existing platform-based solutions, and/or to design and develop highly specific solutions for selected use cases.
Easy Integration within existing processes
Highly costumizable platform
Continous Integrations/ Continous Delivery
Data in real-time