Predictive Maintenance Before Failure Happens
Move from reactive repairs to AI-driven foresight. Our predictive maintenance platform ingests real-time sensor data, detects anomalies, and forecasts equipment failures — giving your operations teams time to act before costly breakdowns occur.
45%
Reduction in unplanned downtime
3–6x
ROI within 18 months
30%
Maintenance cost savings
99.2%
Failure prediction accuracy
How It Works
From raw data to decisions — step by step
A transparent look at our technical methodology, so your engineering and architecture teams know exactly what they're getting.
Sensor Data Ingestion
We connect to your existing IoT sensors, SCADA systems, and PLCs via MQTT, OPC-UA, or REST APIs. Our edge connectors normalize heterogeneous data streams into a unified time-series format in real time.
Feature Engineering & Anomaly Detection
Raw signals are transformed into meaningful features — vibration FFT, thermal gradients, pressure differentials. An ensemble of unsupervised models (Isolation Forest, Autoencoders) flag anomalous behavior before failure occurs.
Remaining Useful Life (RUL) Prediction
Supervised LSTM and XGBoost models, trained on historical failure data, estimate the remaining useful life of each asset class. Models are retrained continuously as new failure data arrives.
Work Order Generation & Integration
Maintenance alerts are automatically routed to your CMMS (SAP PM, Maximo, ServiceNow) via API, creating prioritized work orders with failure context and recommended spare parts — before technicians are dispatched.
Operations Dashboard & Reporting
A real-time command center surfaces asset health scores, upcoming maintenance windows, and cost-avoidance metrics. Role-based views for plant managers, technicians, and executives.
Architecture
Reference Architecture
A layered view of the platform stack — from source systems to actionable outputs.
Data Sources
Ingestion & Streaming
AI / ML Platform
Action & Integration
Industries
Built for asset-intensive industries
Heavy Manufacturing
Predict bearing failures, motor overheating, and gear wear in CNC machinery and industrial robots — eliminating costly production halts.
Energy & Utilities
Monitor turbines, transformers, and grid assets in real time. Prevent catastrophic failures and optimize maintenance schedules for field crews.
Aviation & MRO
Integrate with onboard health monitoring systems to predict component fatigue and schedule maintenance at optimal intervals, ensuring airworthiness.