Crosser - Edge Analytics & Integration

More About Crosser - Edge Analytics & Integration

Crosser - Edge Analytics & Integration is positioned for organizations that need to process operational and sensor data close to its source while maintaining integration with enterprise IT and cloud platforms. It targets IIOT, manufacturing, utilities, and other sectors where real-time processing of machine and process data is required for automation, monitoring, and optimization. The platform focuses on enabling data pipelines that run on edge nodes, on-prem servers, or cloud infrastructure, with centralized control over deployment and lifecycle management.

The platform uses a flow-based, low-code development model where users visually design data pipelines from prebuilt processing modules. These pipelines typically include steps for data ingestion, parsing, filtering, aggregation, enrichment, analytics, and routing. Crosser connects to industrial devices and systems through support for common industrial and OT protocols (industrial connectivity and integration), and to IT systems via APIs, message brokers, databases, and cloud services. This allows enterprises to create unified data flows that span PLCs, sensors, Supervisory Control and Data Acquisition (SCADA) systems, MES/ERP applications, and data platforms.

From an architecture perspective, Crosser operates in distributed edge and hybrid environments. Edge nodes run the data flows close to machines or local processes, reducing data volume sent to the cloud and enabling near-real-time responses. A central cloud or on-prem component manages configuration, versioning, deployment, and monitoring of these distributed flows. This architecture aligns with edge computing patterns where compute and analytics are placed near data sources while orchestration and fleet management are handled centrally.

In marketplace categorization, Crosser can be mapped to several enterprise IT domains: edge analytics (analytics), streaming data integration (data integration), IIoT/OT data orchestration (industrial IoT), and hybrid integration between OT environments and cloud services (integration platform). It is used to build use cases such as condition monitoring, OEE analytics, predictive maintenance pipelines when combined with external Machine Learning (ML) services, and event-driven automation tied into enterprise applications.

Compared with traditional batch-oriented integration tools, Crosser focuses on streaming data, time-series signals, and event processing with deployment on resource-constrained or remote edge environments. Its low-code approach aims to make it accessible to engineers and domain experts who may not specialize in conventional software development, while still fitting into enterprise architectures that include message buses, data lakes, and analytics platforms. For enterprises standardizing on IIOT and edge computing, Crosser provides a configurable layer for ingesting, processing, and routing data between OT and IT systems.