Industrial diagnostics

From a strange reading to a fix you can stand behind.

Qriton combines sensor data, inspection imagery, maintenance history and operator knowledge into one diagnosis: what is failing, why, how severe it is and how long your team has to act.

An anomaly alert is not a maintenance decision.

The hard work starts after a threshold is crossed. Vibration, acoustics, images, work orders and operator notes rarely arrive in one view, and a risk score does not say which failure modes contribute or what to fix first.

After an incident, teams rebuild the reasoning from systems that captured only part of the story.

What changes.

Root cause

The contributing failure patterns and their weight, not just an anomaly flag.

Time window

Remaining useful life, expressed as an intervention window your team can schedule.

Decision record

Why the part was repaired, monitored or replaced, on file for the auditor and the insurer.

How it works.

01

Collect

Time series, logs, notes, images, 3D data and safety context, from the systems you already run.

02

Diagnose

Condition, failure modes, severity and remaining life, with stated uncertainty.

03

Review

Specialists see the evidence and approve or challenge the diagnosis.

04

Act

A clear recommendation and intervention window, with a replayable record.

Questions.

Which data can the diagnosis use?
Time-series sensors, logs, work orders, operator notes, inspection images and 3D point clouds, according to the pilot scope.
Does it replace our monitoring systems?
No. It starts from the evidence those systems already produce and adds a diagnostic and decision layer.
Can it run inside the plant?
Yes. Qriton runs on customer-controlled and edge infrastructure when data cannot leave the site.

Bring us the decision that has to be right.

BriefingPilot on your dataProduction