How do integrations work with Canopy to turn raw data into actionable intelligence?

Overview

Canopy's platform enables flexible integration with any device and ancillary management systems in your environment. This capability transforms raw device telemetry into meaningful, actionable data for remote monitoring, management, and service operations.

The Data Flow: How Canopy Processes Device Information

1. Data Collection via Leaf Agent

The Canopy Leaf Agent runs on remote devices—whether self-service kiosks, IP cameras, POS systems, digital signage, or other connected equipment. The agent continuously collects operational data and transmits it to the Canopy platform.

2. Raw Device Data

Devices generate streams of unstructured or semi-structured data. For example, a typical data payload might include:

{
  "messageType": "statistic",
  "statisticType": "systemUtilization",
  "data": {
    "cpuPct": "0.9241323087034556",
    "uptime": "7898742",
    "memFree": "0.1572727450100482",
    "diskUsage": {...},
    "freePct": 0.71,
    "freeBytes": 43502280
  }
}

This raw data contains valuable information about device health and performance, but it needs to be structured and interpreted to become useful for operations teams.

3. Flexible Data Transformation

Canopy provides four powerful mechanisms to transform raw device data into organized, meaningful intelligence:

Default Fields

Pre-configured fields built into the Canopy system that cover common device metrics and operational data. These provide immediate, out-of-the-box functionality and can be customized as needed.

Custom Fields

Create and manage new fields tailored to your specific devices and use cases. Custom fields can be mapped to specific data points coming from the Leaf agent, allowing you to capture unique metrics relevant to your operational environment—whether that's transaction counts from a kiosk, temperature readings from kitchen equipment, or network latency from payment terminals.

Field Collections

Organize related fields into logical groups associated with Canopy entities. Collections help structure complex data sets, making it easier to view and analyze related metrics together—for instance, grouping all performance metrics for a specific device type or location.

KPIs - Calculated Fields

Define metrics derived from event-driven calculations. Once configured, KPI values are automatically computed from incoming data and compared against preset thresholds. This provides proactive health status indicators—triggering alerts when a device's CPU usage exceeds acceptable limits, disk space runs low, or uptime falls below service level requirements.

4. Configuration Management

All of these data transformation options are managed through Canopy's settings interface. Users can configure how raw device telemetry maps to fields, define calculation logic for KPIs, set threshold values for alerts, and organize data into meaningful collections—all without requiring changes to the devices themselves.

The Value: Universal Device Support

This flexible architecture means Canopy isn't limited to specific device types or pre-defined data structures. Whether you're managing Android tablets running kiosk software, Linux-based digital signage, Windows POS terminals, or IoT sensors, the Leaf agent can collect their data and Canopy can interpret it according to your operational needs.

For restaurant operators managing diverse technology stacks, this eliminates the need for multiple monitoring tools. A single platform can ingest data from drive-thru timers, kitchen display systems, payment terminals, and surveillance cameras—then surface the insights that matter most to your operations.