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Making Big Data Small and Relevant

Edge Analytics software allows data produced by sensor-rich assets like machines, equipment, and devices to be pre-processed in real-time closer to where it is created.

There are several technical and business drivers and benefits with Crosser Edge Analytics architecture, including:

Cost Savings

Significant data reduction by removing dirty data and irrelevant data. Get significant cloud, analytics and network connectivity cost savings.

Innovate with more Data

Edge Analytics allows you to collect more data points without increasing your cost of data. More data - more innovation possibilities.

Transform Raw Data to Insights

Collect raw data, transform it, analyze it and act on the insights in real-time.

Local Intelligence and Automation

Run local triggers between machines or PLC’s with ultra-low latency. Runs autonomously without cloud connectivity.

Typical Deployment Scenarios

Crosser Edge Deployment Scenario


The Edge Analytics software is deployed on an IoT gateway on a remote unit, or embedded, and processes the sensor data from that single unit.

Crosser Field Edge Aggregation Scenario

Field Edge Aggregation

Also called Fog Computing. The Edge Analytics software is typically deployed on an IoT gateway and processes the sensor data from multiple field units.

Crosser On-premise Edge Scenario

On-Premise Edge

Typically on a factory shop floor or building with multiple machines. The Edge Analytics software is installed on a server/virtual machine and processes sensor data from multiple on-premise machines and data sources.

Business case objectives and use-cases

Edge Analytics is a key layer in the Industrial IoT or Industry 4.0 technology stack.

Smart and cost-efficient data collection and analytics is a fundamental part

Business Case Objectives

No data. No party

Getting access to relevant data in a central location, either cloud or data center,
is the fundamental starting point to enable these main use-cases and meet the business objectives.

Crosser Edge Analytics solution is purpose-built to address the key challenges for Industrial IoT, including:

Condition Monitoring - remote assets - challenges

Factory floor challenges

  • A high number of sensor tags - constant changes
  • Many data sources: PLC, DCS, MES, Historians, and databases
  • Many protocols: OPC, Modbus, MQTT, SCADA and more
  • Separated networks
  • OT and IT team collaboration

Factory Floor Challanges

Remote Condition Monitoring Challenges

  • Moving from basic telemetry to monitoring all subcomponent
  • How to collect more data but transfer less?
  • Limited and costly connectivity
  • Unreliable and intermittent connectivity
  • Managing a large volume of assets inside firewalls

Try Crosser For Free

Start innovating today. How it works:

1. Get an account
2. Log in and start designing your flows in the sandbox
3. Download the Crosser Container to your local test node
4. Test with real data