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Aviation / Aerospace

# Major Aerospace OEM

On-Device ML for Aerospace Manufacturing

On-device MLComputer VisionEdge ComputingAviation

## The Challenge

A major aerospace OEM needed machine learning systems that could run on-device in environments where cloud connectivity isn’t guaranteed and reliability is non-negotiable. This required a fundamentally different approach than typical ML engineering — models that are small, fast, and bulletproof.

## What We Built

Our team designed and built several production ML systems:

-   **On-device machine learning** models optimized for edge deployment
-   **Computer vision** systems for manufacturing and inspection workflows
-   **Recommendation engines** for maintenance and operational decision-making
-   Edge infrastructure that meets aerospace-grade reliability requirements

## The Result

-   **3 production ML systems** deployed to edge devices in manufacturing environments
-   **Models running on-device** with no cloud dependency — zero-downtime inference
-   **Sub-second inference latency** on constrained hardware
-   Production systems operating where failure isn’t an option and cloud connectivity can’t be assumed — the kind of work that separates real ML engineering from demo-day prototypes.