Problem
Industrial equipment inspections and maintenance activities can involve fragmented workflows, manual reporting, and disconnected operational data. When inspection results, equipment conditions, reported defects, and maintenance records are managed separately, organizations may experience delayed issue escalation, limited visibility into asset health, and difficulties tracking recurring equipment problems. These challenges also limit the availability of structured historical data required for advanced analytics and predictive maintenance.
Solution
Techniq Asset Intelligence connects field inspections, equipment health monitoring, and maintenance management within a single digital platform. Field workers scan an equipment QR code to access asset-specific inspection checklists and submit measurements such as temperature, pressure, and vibration. A configurable rule engine evaluates these readings, identifies abnormal conditions, and generates explainable asset health scores. Critical findings automatically create operational issues that can be converted into maintenance work orders. The platform tracks technician assignments, corrective actions, root causes, and maintenance completion while providing historical measurement trends and fleet-level dashboards. The current solution uses deterministic condition-based analytics. Predictive maintenance AI is planned for a future phase using real industrial operating and failure data.
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