Compare AssetWatch vs. Crosser

We cater to numerous clients, ensuring daily prevention of downtime while significantly enhancing their financial outcomes. Explore approaches to eradicate downtime specific to your sector, leading to decreased financial setbacks and improved operational efficiency. Our continuous monitoring focuses on critical assets that could result in lost production and expensive repairs if they fail. Each year, organizations face production losses stemming from unexpected downtime and its repercussions. We can proactively monitor and address over 100 potential machine issues while they are still developing. These problems can often be detected weeks or even months before a failure occurs. Our platform offers comprehensive monitoring across various conditions and components, providing a complete overview of an asset’s health. By identifying issues early, we enable proactive measures that allow for the most cost-effective resolutions, minimizing unplanned downtime and lowering yearly machine repair expenses. We combine the strengths of human insight and advanced technology to guide our clients in determining the necessary actions to take. Ultimately, our commitment is to enhance operational reliability and safeguard against unexpected disruptions.

Analyze and utilize your data at the Edge to transform Big Data into manageable, pertinent insights. Gather sensor information from all your equipment and establish connections with various devices like sensors, PLCs, DCS, MES, or historians. Implement condition monitoring for assets located remotely, aligning with Industry 4.0 standards for effective data collection and integration. Merge real-time streaming data with enterprise data for seamless data flows, and utilize your preferred Cloud Provider or your own data center for data storage solutions. Leverage Crosser Edge's MLOps capabilities to bring, manage, and deploy your custom machine learning models, with the Crosser Edge Node supporting any machine learning framework. Access a centralized library for your trained models hosted in Crosser Cloud, and streamline your data pipeline using a user-friendly drag-and-drop interface. Easily deploy machine learning models to multiple Edge Nodes with a single operation, fostering self-service innovation through Crosser Flow Studio. Take advantage of an extensive library of pre-built modules to facilitate collaboration among teams across different locations, effectively reducing reliance on individual team members and enhancing organizational efficiency. With these capabilities, your workflow will promote collaboration and innovation like never before.