Real-time streaming analytics and edge computing close to where data is generated
Using our Crosser Flow Studio tool, build data processing flows, using a graphical editor and then deploy these flows onto a number of Edge nodes. At the core of each Edge node is Crosser's in-house developed real-time streaming analytics engine. The Edge node software is deployed as a Docker container and runs on any host that supports Docker.
Crosser introduced a strategy for "Bring your own AI" to enhance the Edge Intelligence in Industrial IoT, giving customers full freedom to deploy their favourite machine learning framework on our platform.
Typical use cases include remote condition monitoring, predictive maintenance, machine/asset data to cloud, vision based quality inspection, secure sensor tag separation, deployment of AI and machine learning models, as well as many more.