Troubleshooting

Faster diagnosis. Minimum mean time to repair.

Get the right fix to the right person in minutes. AR-guided troubleshooting and on-device AI, directly at the asset.

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Maintenance technician at an opened control cabinet using the Dropslab troubleshooting view on a phone: two detected issues with live video and AR annotations

From first symptom to verified fix.

From the moment a line stops to a captured, reusable solution.

AR diagnosis at the failing component
Step 01

Identify the fault. Guide the fix.

The technician points the device at the failing component. Dropslab identifies the asset, surfaces the most likely fault based on symptoms and prior cases, and overlays the right repair steps on the exact part, visible on tablet or smart glass.
- On-device AI identifies the component and ranks fault likelihood
- AR step markers on the actual part: no manual lookup, no wrong-asset mistakes
- On-device AI verifies critical steps before the next one starts
Remote expert annotating the technician’s view
Step 02

Escalate in one tap. Expert in the same view.

When the guided flow doesn’t resolve it, one tap pulls a remote expert into the same view with live AR annotation. The expert sees what the technician sees, draws on the part and walks them through the fix. No travel required.
- Live AR annotation on the asset, shared in real time
- Voice, photo and sensor context attached automatically
- Travel and on-site escalation deflected when AR is enough
Knowledge capture and CMMS write-back
Step 03

Capture the fix. Close the loop.

Every resolved fault becomes a reusable troubleshooting node, anchored on the actual part. The next technician sees the previous fix in context. Fault history, audit trail and CMMS write-back happen automatically.
- Resolved fault becomes a reusable AR-anchored troubleshooting node
- Native sync with MaintainX, Maximo, Limble, Fiix, SAP PM
- Per-step audit log: timestamp, AI decision, operator, SOP revision

Diagnosed at the asset. Resolved with proof. Captured for the next time.

End-to-end walkthrough

Six capabilities, one layer.

Diagnosis, repair, escalation and capture on the same asset record.

Fault recognition: On-device AI identifies the component and ranks the most likely fault, before the technician opens a single manual.
AR-guided repair: The exact repair step, on the exact component, visible on tablet or smart glass, right where the work happens.
One-tap remote expert: Pull a remote expert into the same view with live AR annotation. No travel, no “send me a photo” loop.
Reusable fix library: Every resolved fault becomes an AR-anchored node on the part: the right fix available to every technician, every shift.
IoT-triggered diagnostics: Sensor anomalies open the right diagnostic procedure automatically, before the breakdown happens.
Maintenance system write-back: Every diagnostic step, photo and resolution flows back into your existing maintenance system in real time.

−30%

Measured, not marketed

Troubleshooting time, measured across Dropslab deployments.

One number. From real assets, real faults, real technicians. AR-guided diagnosis on the actual component plus an AI second opinion compresses the loop: fewer minutes finding the fault, fewer minutes offline, fewer escalations. Not an industry benchmark. Measured by us.

Source · Dropslab deployments · Dropslab-measured