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Predict Guard

by Scops

Non-invasive LoRaWAN sensors deployable in about 20 minutes feed vibration, temperature and current data to an AI engine that raises predictive alerts and opens CMMS maintenance tickets.

Scops
Industry
Buildings & FacilitiesIndustrial & ManufacturingCommercialManufacturing
Use cases
Predictive MaintenanceResource MeteringWorker SafetyAsset Tracking
Connectivity
LTE-M
Deployment
Public SaaSEdge/Local
Services
System Integration
Available in
Finland
Add to RFP
The solution

How Predict Guard addresses it

Predict Guard collects location, movement, and asset-status signals across commercial buildings and workplaces and sends the readings to a secure cloud application. Dashboards and configurable rules show condition trends and early fault indicators, retaining history by site, zone, or asset. This gives facility, property, and energy teams the context to plan maintenance before failure, helping them reduce unplanned downtime and unnecessary service and document the response.

What it is

Predict Guard is a predictive maintenance, resource metering, worker safety solution by Scops, delivered as Public SaaS / Edge/Local, serving Buildings & Facilities, Industrial & Manufacturing.

How it works

Sensors, meters, tags, or controllers are installed at the relevant points across commercial buildings and workplaces to capture location, movement, and asset-status signals. Readings move over LTE-M to a secure cloud application, with a gateway or edge service added where required. The application organizes condition trends and early fault indicators by site, zone, or asset and keeps a history for comparison. When a rule identifies an exception, an alert gives the responsible team the context to plan maintenance before failure. Deployment can start with one area or asset group and extend to additional sites using the same monitoring and response workflow.

ConnectLTE-M
AnalyzePublic SaaS / Edge/Local platform
ActSystem Integration

Vendor documentation: vendor website

Evidence level: L1 · Vendor-stated: how evidence levels work

Why teams choose it

Less downtime: Cut unplanned stoppages by about 40%

Energy savings: Optimize consumption by around 15% through analytics

Fast ROI: Pilot running in about 20 minutes with no cabling or heavy integration

Comprehensive CMMS: Manage maintenance with tickets, manuals, and digital twins, with faulty sensors auto-detected at scale

AI-Driven Anomaly Detection

Detects anomalies in energy, vibration, temperature, and current, with automated email and SMS alerts

Plug-and-Play LoRaWAN Starter Kit

Non-invasive sensors and gateway deployable in 20 minutes

Predictive Maintenance Workflows

Predictive and preventive maintenance with CMMS integration

Digital Twin Dashboards

Historic trends and KPIs in digital twin views

Sensor Health Checks

Automates data integrity across hundreds of endpoints

ETL Integration

Ingests data from IoT, SCADA, ERP, and manual logs

Not sure this fits your deployment?✓ Enterprise active

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Have a question for Scops?

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