Pragma

For asset-intensive organisations that have already digitised basic maintenance transactions and now seek to graduate from reactive firefighting to predictive, risk-based optimisation, Pragma On Key offers a rare blend of deep engineering heritage, explainable AI, and outcome-centric commercial arrangements. Its strongest fit lies in brown-field environments—rail, utilities, mining, and heavy manufacturing—where historical CMMS data exists but has yet to be monetised.

Asset Strategy Optimisation

Users can build Failure Mode and Effects Analysis (FMEA) libraries directly in the system. The AI engine ingests these libraries and automatically generates dynamic maintenance tactics, suggesting interval changes or condition-monitoring replacements based on actual asset performance rather than OEM manuals. A Monte-Carlo simulation engine visualises the impact on availability, cost, and risk over a 10-year horizon.

Mobile Workforce Enablement

Inspectors capture vibration, thermography, or lubricant samples via native iOS/Android apps that work offline. Photos are auto-tagged with Azure Cognitive Services; defects are classified using a fine-tuned Vision Transformer. Once synchronised, the app displays AI-generated next-best actions such as “Schedule balancing within 72 hours – probability of bearing failure 74 %”. Technicians can accept, reject, or escalate each recommendation, feeding the human-in-the-loop dataset.

Supply-Chain Integration

On Key integrates with SAP or Oracle ERP to check real-time parts availability. The optimisation engine can delay non-critical work orders until parts arrive, reducing expedited freight costs. A digital-twin of the warehouse allows planners to run what-if scenarios: for example, the impact of consolidating two regional stores on overall stock-out risk.