Predict equipment risk before downtime becomes expensive.
MaintenX combines machine failure prediction, explainability, and AI-assisted recommendations in one operator-ready interface.
Realtime Risk Signal
Submit telemetry and receive probability-driven failure classification instantly.
AI Maintenance Assistant
Gemini-powered explanations transform model output into actionable operator guidance.
Operational Confidence
Expose prediction, recommendation, and readiness in one clean workflow.
Core Metrics and Reliability Signals
A compact benchmark and product-readiness layer to help teams quickly understand performance, delivery flow, and AI support status.
99.90%
Primary production model benchmark
3 Layers
Prediction, explanation, recommendation
Gemini
Natural-language maintenance guidance
Realtime
FastAPI-connected dashboard experience
Prediction Form
Machine Type
Encoded product family identifier.Air Temperature
Ambient operating temperature in Kelvin.Process Temperature
Process temperature in Kelvin.Rotational Speed
Machine spindle speed in RPM.Torque
Mechanical load in Newton meters.Tool Wear
Accumulated wear exposure in minutes.TWF Flag
Tool wear failure indicator.HDF Flag
Heat dissipation failure indicator.PWF Flag
Power failure indicator.OSF Flag
Overstrain failure indicator.RNF Flag
Random failure indicator.Prediction Result
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Idle
Submit machine telemetry to generate risk probability, classification, and maintenance guidance.
Maintenance Guidance
Explanation
The assistant explanation will appear here once a prediction response is received.
Recommendation
Recommended maintenance action will appear here after inference.
Make predictions understandable, not just accurate.
MaintenX combines model inference with explanation and recommendation layers so engineering teams can review why a machine is risky and what action should happen next.
Included in this flow
Prediction API, benchmark metrics, assistant guidance, and SHAP report generation are all represented in the product workflow.
Explainability Layer
SHAP reports expose the strongest contributors behind failure classification so operators can review decisions with more confidence.
Metrics Visibility
The product communicates probability, risk percentage, and operational state in a compact executive-style decision panel.
Actionability First
Assistant recommendations turn raw model outputs into maintenance next-steps instead of leaving teams with only scores.