MaintenanceAI analyzes the maintenance evidence your team already owns and turns it into prioritized bad actors, repeat-failure findings, PM improvements, backlog actions, planning gaps, and executable next steps.
Start with the free Health Check See sample output
No new CMMS required. Start with approved maintenance history from the system you already use.

Concept visualization of the MaintenanceAI intelligence layer.
Failure patterns, reactive burden, repeat work, labor, corrective history, and closeout quality.
Task clarity, failure-mode relevance, completion history, frequency basis, and improvement opportunities.
Bad actors, hierarchy quality, aging work, job readiness, priority signals, and maintenance-system constraints.
Identify the maintenance-system areas most likely to need attention before sharing any CMMS files.
Run the free Health CheckApproved customer data is normalized and analyzed for bad actors, repeat failures, PM effectiveness, planning gaps, backlog health, and data quality.
See how CMMS data analysis worksReceive prioritized findings, supporting evidence, structured recommendations, and clear next actions with human technical review.
Open Customer PortalThe Reliability Reset explains how to control backlog, priorities, planning, scheduling, PM quality, and repeat failures. MaintenanceAI looks at the evidence in your own maintenance history and helps determine where limited time and money should go next.
Run the free Health Check first. When you are ready for facility-specific answers, MaintenanceAI applies the method to approved maintenance data.
Start the free Health Check Customer Portal