MaintMirror

MaintMirror is a web app (with optional mobile companion) that converts messy maintenance work orders, technician notes, and sensor snippets into a lightweight “digital twin of history” for each asset. Instead of promising perfect physics-based twins, it focuses on what most plants actually have: CMMS data, PDFs, and inconsistent notes. The app ingests work orders, parts replaced, downtime reasons, and basic telemetry, then uses AI to normalize terminology, detect recurring failure patterns, and recommend inspection/replacement windows with confidence levels. It highlights the top drivers of unplanned downtime, flags assets with suspiciously frequent repeat repairs, and suggests standardized failure codes to improve data quality over time. Integrations target common CMMS/EAM systems and simple CSV exports first, because full OT integration is expensive and slow. The goal is practical predictive maintenance that works with imperfect data.