Proof of concept · Manufacturing
Learns a baseline for each machine, flags anomalies in telemetry and explains them through a diagnostics assistant.
Overview
Equipment generates large volumes of telemetry, but early signs of degradation get lost in the noise, and most plants lack the labelled failure data that classic models need.
An Isolation Forest model learns normal behaviour for each machine and flags drift. Anomalies are surfaced through APIs, dashboards and a conversational diagnostics agent that drafts work orders for a planner to approve.
Outcomes
Where this applies
Request an Agent Pilot
Tell us about your systems and timeline. We will scope a pilot with agreed measures and human decision points.
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