EdgeAlyzer™ The Only True AI Edge Predictive Maintenance

 Everything runs locally on the EdgeAlyzer: data acquisition, AI inference, and full web visualization. Install sensors, power it on, and start predicting failures in hours — no VMs, no firewalls, no cloud bills ever.

Four decades of PLC, motion, and safety system experience went into every sensor package, workflow, and commissioning guide. This isn’t “big data” theory — it’s predictive maintenance that actually works on your floor.

 Per-sensor autoencoder models trained and executed entirely on-device deliver anomaly detection in 2–3 milliseconds. No data ever leaves the edge, no external ML services required.  

Capture 8–48 hours of normal operation and the system automatically learns your machine’s unique fingerprint — including RPM/vibration correlations that generic cloud AI misses. Operator feedback loops continuously improve accuracy without retraining from scratch. AI  

accelerated inference flags bearing wear, imbalance, misalignment, and looseness faster than the machine can damage itself.

 Beautiful, auto-generated dashboards for trends, fault history, runtime accumulation, and AI anomaly scores. Access from any phone, tablet, or PC via the built-in Wi-Fi hotspot or Ethernet — no software to install.

 Multi-level warning/alarm limits on every signal with persistent runtime tracking. Drive stack lights, sirens, email, SMS, or MQTT alerts directly from the same definitions.

 REST APIs and MQTT publisher let you feed CMMS, MES, SCADA, or historians. You own your data; push it wherever you want — or keep it 100% offline.

 One Supervisory Edge unit aggregates dozens of EdgeAlyzers into a single facility-wide view, broadcasts its own secure Wi-Fi network, and works even when plant IT is down.