Optimyzer
Close the loop between sensors, parameters, and outcomes. Optimyzer learns your machine and recommends settings to lift throughput and cut scrap.
Adaptive optimization
Online learning adjusts parameters as drift and conditions change.
Multivariate control
Balance competing constraints across pressure, temperature, time, and feeds.
Quality prediction
Predict defects early from sensor signatures and act preemptively.
Parameter examples
Temperature profile • Pressure curve • Dwell time
Fill speed • Pack & hold pressure • Mold temperature
Feed rate • Laser power • Assist gas
How Optimyzer works
From inputs to recommendations: see how Optimyzer learns fast and adapts with feedback.
Deploy anywhere
Cloud, on‑prem, or edge. Integrate via OPC‑UA, MQTT, or REST. Hardened and secure by default.