POAM-edge
On-device adaptive monitoring
Ultra-light predictive engine for embedded controllers and gateways that adapts to shifting conditions without shipping data offsite.
Parameters
120M
Deployment
Edge GPU, x86 gateways
Latency target
<25ms target latency
Overview
POAM-edge is built for predictive maintenance teams that need adaptive learning without sacrificing reliability. The model stays calibrated with hourly micro-updates so alerts stay relevant as operating conditions shift.
Best for
Remote or disconnected assets
Low-power vibration + temperature sensors
Immediate local alerts
Capability 1
Streaming anomaly scoring
Built for high-frequency telemetry, stable drift detection, and clear operator action.
Capability 2
Local drift correction
Built for high-frequency telemetry, stable drift detection, and clear operator action.
Capability 3
Edge-first alert routing
Built for high-frequency telemetry, stable drift detection, and clear operator action.
Implementation notes
We size POAM-edge to your asset mix and telemetry density, then validate the model in simulation before deploying to production. Deployment bundles include monitoring dashboards, alert routing, and retraining workflows tuned to your maintenance cadence.