Predictive maintenance
From breakdown to forecast, on the assets that matter most.
Solazur helps mid-market manufacturers, industrial-services firms, and energy operators turn their data into uptime, throughput, and quality, without scaling the engineering team.
From breakdown to forecast, on the assets that matter most.
Stable lines, fewer scrap parts, lower changeover time.
Inline checks, automatic audit trails.
Demand sensing, working capital recovery.
Customer specs to quote, in hours not days.
Consumption signals tied to production reality.
Yes, and it is the most undervalued one. The spreadsheets are usually where the actual operational logic lives: production scheduling, capacity planning, material reconciliation, cost roll-ups. We do not replace them with a new system. We automate the data that feeds them and the steps that come after them.
It sits on top, not inside. We do not touch the deterministic control layer. We work at the level above: production order management, quality data consolidation, planning adjustments, supplier coordination. The MES keeps running the line, the automation handles the office work that surrounds it.
Yes. Quality data extraction and compliance reporting are among the most consistent ROI cases in manufacturing. We build the workflow that pulls quality measurements from the production systems, formats the reports for the regulator or the customer, and routes them for review. Reporting cycle time drops from days to hours.
It can, with care. Multi-plant integration is harder than single-plant, but it is exactly where the value lives because reporting, planning, and procurement need consolidated data. We design the architecture so each plant keeps its own system and the automation layer reconciles across them.
This is where we say no more often than yes. Predictive maintenance only pays off when you have years of historical sensor data and a reliable failure record to train against. If you do, we can help build it. If you do not, we recommend starting with the simpler automation cases first and revisiting predictive once your data foundation is there.
Bring your three biggest operational headaches. Leave with a one-page roadmap.