Know before
the failure
Fieldiq streams vibration, temperature, and load telemetry from distribution transformers and line reclosers into anomaly models calibrated per asset class — flagging incipient failures before outage events occur.
Why distributed assets need their own models
Per-asset-class baselines
Anomaly thresholds are trained on the electrical and thermal signatures of each asset class — not generic vibration norms. A 37.5 kVA pad-mount transformer behaves differently from a 500 kVA pole-top unit.
Built for distributed topology
Hundreds of field assets scattered across a service territory, not a centralized plant floor. Fieldiq handles sparse connectivity, intermittent telemetry, and geo-tagged asset inventories natively.
Incipient fault detection
Flag failures 2–6 weeks before they cause outages. Reduce unplanned restoration events and SAIDI impact across your service territory.
Sensor-agnostic ingest
Works with existing IED/RTU telemetry, retrofit vibration sensors, and temperature loggers. No proprietary hardware required.
Supported asset classes
Operational impact metrics
Metrics reflect internal validation data. Results vary by asset age, sensor placement, and data quality.
Connects to your existing stack
Fieldiq reads from SCADA systems, PI/AF historians, and DERMS feeds via standard protocols. No rip-and-replace.
View IntegrationsStart with one feeder, one asset class
Deploy a proof-of-concept on a representative slice of your distribution network. Fieldiq's team handles onboarding, model calibration, and SCADA integration.