Turn Every Handheld Field Inspection Into AI-Verified Action

A mobile AI inspection app turns a smartphone or tablet into a guided, AI-assisted field inspection tool for an inspector who is physically present at the asset. It uses computer vision, OCR, guided checklists, and real-time analytics to capture asset conditions, identify potential defects, digitise readings, and generate structured inspection records - while the inspector remains in the loop and makes the final call. It's built for any asset a person can walk up to and safely inspect, not for autonomous drone, rover, or fixed-line capture.

No. Mobile AI Inspection is built for assets an inspector can physically and safely reach on foot. For assets that require aerial or ground-robotic access - elevated structures, confined spaces, or hazardous zones - see AI Infrastructure Inspection, which covers drone and rover capture on the same PETRAN/TRITVA platform.

AI Visual Inspection (Tritva) uses a fixed camera mounted on a production line for continuous, automated, line-speed inspection with no person in the loop. Mobile AI Inspection is for scheduled or one-off field visits where an inspector carries the device and makes the call, guided by AI. If you need the fixed-line version, see AI Visual Inspection.

The inspector captures photos, videos, voice notes, or equipment readings using a mobile device. AI analyses the collected data to identify defects, classify asset conditions, extract meter readings, and recommend the next inspection step. The findings can then be sent to dashboards or maintenance systems for review and action.

Depending on how the AI model is configured and trained, it can help detect corrosion, cracks, leaks, surface damage, missing components, abnormal wear, safety hazards, and other visible anomalies. Detection capability varies according to image quality, asset type, inspection conditions, and model training.

Yes. An offline inspection app can allow field teams to complete checklists, capture photos, record readings, and document defects in areas with limited connectivity. The inspection data can be securely synchronized with the central platform when an internet connection becomes available.

Yes. Gauge OCR inspection uses optical character recognition and computer vision to extract readings from analogue gauges, digital meters, nameplates, and equipment displays. Inspectors should still be able to verify readings before submitting them, particularly when images are unclear or gauges are damaged.

Accuracy depends on factors such as training-data quality, defect type, lighting, camera angle, image resolution, and operating conditions. Mobile AI should support inspector decisions rather than replace professional judgement. Organisations should validate models using representative images from their own assets and environments.

Yes. A field inspection app with CMMS work order integration can convert confirmed findings into maintenance notifications, corrective actions, or work orders. This helps eliminate duplicate data entry and connects inspection evidence directly to planning, assignment, and resolution workflows.

Yes. Mobile inspection data can be combined with IoT condition monitoring, SCADA data, and asset-management information to provide broader visibility into asset health. Field observations add visual and contextual evidence to sensor alerts and operational readings.

Mobile AI inspection apps are used across oil and gas, construction, utilities, manufacturing, infrastructure, transportation, mining, and energy. Common applications include asset-integrity inspections, safety audits, quality checks, meter-reading collection, preventive maintenance, and compliance documentation.