NoamAI: maintenance optimization simplified

Leverage historical maintenance and fault data to reduce downtime and unnecessary part replacement. Get an optimized order of troubleshooting steps for any combination of faults, warnings, and pilot-reported issues.

Noam Platform screenshot showing recommendations and faults/warnings

“Traditional” troubleshooting

Diagram demonstrating how a typical "traditional" troubleshooting session is completed

Learning from history

The NoamAI platform generates an optimized order of steps for resolving maintenance issues by tapping into past maintenance records and aircraft health telemetry data.

Diagram demonstrating the data sources the NoamAI platform ideally requires to generate optimized troubleshooting order

The collated data combined with NoamAI's custom fault propagation performs a root cause analysis to determine which tasks resolves the most amount of issues.

Delivering value in multiple areas

Improved aircraft lifetime

Reduce aircraft downtime by spending less time on the ground troubleshooting mechanical issues and more time in the air serving customers

Better on-time departure performance

Minimize delays at the gate by helping line maintanence solve issues faster. Less delays at the gate means less missed takeoff slots, happier customers, and fewer fines

Knowledge Retention

Prevent the loss of deep organizational knowledge when senior staff leaves or retires. Let entry-level engineers tap into the deep knowledge-sets of senior staff

Picture of a Boeing 777-300ER at an airport gate
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