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Plant and assets
Signals, equipment state, and operating context
Clairon is a diagnosis layer for industrial monitoring. It turns an alarm or unexplained drift into an evidence-backed operator brief, while the monitoring stack already in place remains in control.
A person always decides. Clairon never acts on your plant by itself.
In an alarm flood, the signal that matters is buried among symptoms, nuisance alarms, and stale warnings. With a slow drift, nothing fires at all. In both cases, the person on duty has to rebuild the operating context before deciding what to check.
A threshold can say that a value crossed a line; it cannot distinguish cause from symptom. Nuisance, chattering, and stale alarms arrive beside the event that matters, while the evidence and decisions that explain it are often scattered across shifts and systems.
A threshold cannot recognize a drift that never crosses one. A pump degrades, a schedule sticks, or energy use creeps upward until the change surfaces later. Teams bridge the gap with experience, but the next review often starts by rebuilding the same context.
Where Clairon sits
Clairon sits between the monitoring evidence and the person who decides. It reads from the system already in place, returns an evidence-backed operator brief, and keeps the evidence, diagnosis, and human decision linked for the next relevant review.
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Signals, equipment state, and operating context
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Alarms, history, rules, and dashboards
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What changed, likely causes ranked, and the next check
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Confirms, corrects, or escalates
The evidence, diagnosis, and human decision stay linked, so the next relevant review can start from prior context instead of rebuilding it.
See it work
Follow the work from the first signal to a clear diagnosis, a human decision, and a record the team can use next time.
Illustrative Compressor A maintenance workflow using representative inspection evidence and a procedure-grounded review.
Frame 1 / 4
A technician’s inspection supplies the evidence: the asset, the location, and the meter reading. The review starts with what was observed, not an assumption about the cause.
Clairon reads through the monitoring interfaces already in place, shows the evidence behind every brief, and links the human decision to the incident record.
The agent engine is open source, and each brief stays linked to the evidence it used, the workflow that produced it, and the human decision that followed.
Existing monitoring remains in place. Inference can run locally or on infrastructure you control, with EU hosting in Frankfurt for the services Clairon operates.
Deterministic rules detect the event. Diagnosis runs for a defined incident or review, returns a specific next check, and leaves the decision with a person.
Operational experience
Keep the record useful after the immediate response.
Clairon keeps the monitoring evidence, diagnosis, and human decision together. When a similar situation returns — or a scheduled review checks the result — the prior record comes back as context. Corrective actions and effectiveness checks remain with the maintenance, quality, change, or training systems that already own the work.
Choose one alarm, slow drift, or recurring review where people still have to gather the evidence, recall prior cases, and work out the next check from scratch.
A bounded first step
Clairon proves one read-only diagnosis beside your existing monitoring before anything broader is considered.