Best Predictive Maintenance software (2026)
Updated 12 June 2026 · independent catalogue, no sponsored ranking
12 predictive maintenance platforms for industrial teams, compared on price and features.
How predictive maintenance software works
- Collect: sensors (vibration, thermal, ultrasonic, electrical) and historian/SCADA tags stream condition data per asset.
- Detect: models learn each asset's normal signature and flag anomalies — bearing wear, imbalance, cavitation, insulation degradation.
- Predict: the platform estimates remaining useful life (RUL) and failure mode, ranked by criticality.
- Act: alerts become CMMS work orders with recommended actions, parts and deadlines.
How to choose (selection criteria)
- Asset coverage: rotating machinery only, or also static/thermal equipment (heat exchangers, steam systems, insulated lines)?
- Data sources: own wireless sensors vs existing historian (OSIsoft PI, OPC-UA) vs both.
- Deployment: cloud vs on-prem/edge — many plants require on-prem for OT security.
- CMMS integration: alerts must become work orders (SAP PM, Maximo, Fiix) or they get ignored.
- Time-to-value: template models per asset class beat months of custom data science.
Augury
Machine health monitoring for rotating equipment using vibration and AI.
Siemens Senseye Predictive Maintenance
Scalable predictive maintenance that learns from existing condition data.
AVEVA Predictive Analytics
Early-warning analytics for critical process and power assets.
Uptake
Industrial AI for asset performance and predictive maintenance.
SparkCognition
AI/ML platform for predictive maintenance and industrial reliability.
Tractian
Sensor-based machine health monitoring with a fast retrofit setup.
Nanoprecise
AI-driven predictive maintenance with multi-parameter sensors.
Emerson AMS
Asset management and condition monitoring for process plants.
Waites
Wireless condition monitoring and predictive maintenance.
Petasense
Wireless sensors and AI analytics for asset reliability.
Samotics
Electrical-signature analysis for machine health and efficiency.
Falkonry
Time-series AI for anomaly detection and operational insight.
FAQ
What is predictive maintenance software?
Software that monitors equipment condition data (vibration, temperature, electrical signals, process tags) and uses models or machine learning to predict failures before they occur, so maintenance is scheduled exactly when needed — not on a fixed calendar and not after breakdown.
What is the difference between preventive and predictive maintenance?
Preventive maintenance services equipment on a fixed schedule whether it needs it or not. Predictive maintenance uses each asset's actual condition data to forecast failure and trigger work only when degradation is detected — fewer unnecessary interventions and fewer surprises.
What data does predictive maintenance need?
The most common signals are vibration spectra, temperatures, motor current, ultrasound and oil analysis, plus process data from the historian/SCADA. Modern platforms combine purpose-built wireless sensors with the tags a plant already records.
How much does predictive maintenance software cost?
Typically priced per monitored asset or per site, ranging from tens of dollars per asset per month for sensor-plus-app bundles to enterprise platform licences. Pilots on the most critical assets are the normal entry path; pricing for the platforms below is listed where vendors publish it.