Predictive Maintenance
At the Edge

FlightEdge delivers real-time AI-powered failure prediction for tactical aviation—where connectivity cannot follow.

THE CHALLENGE

Cloud-Dependent Systems
Can't Fly Combat

⚠️

Model Bias

Centralized models trained on fleet-wide data fail to capture platform-specific degradation patterns, leading to missed failures and false alarms.

⏱️

High Latency

Round-trip data transmission to cloud infrastructure introduces unacceptable delays for time-critical maintenance decisions in contested environments.

💸

Excessive Costs

Continuous telemetry streaming generates substantial recurring cloud costs that scale poorly across the tactical aviation fleet.

These constraints result in reactive maintenance, increased unscheduled downtime, and reduced fleet readiness—directly impacting sortie generation rates.

FLIGHTEDGE

Edge-Native AI That
Operates Anywhere

Purpose-built for disconnected, denied, and austere environments

Edge-Native Inference

ML models execute directly on embedded hardware, delivering sub-second Remaining Useful Life (RUL) predictions without network connectivity.

🔄

Real-Time Drift Detection

Alibi Detect monitors incoming sensor streams against training baselines, automatically triggering model fallback when PSI/KL thresholds are exceeded.

🔍

Explainable AI

SHAP-based feature importance explanations enable maintainers to understand why predictions are made, building trust and supporting informed decision-making.

🛡️

Air-Gapped Security

Three-zone architecture with hardware data diode ensures zero data exfiltration. Keycloak SSO with CAC/PIV authentication enforces role-based access control.

🎯

Platform-Specific Tuning

Katib hyperparameter optimization on platform-specific data eliminates fleet-wide model bias that plagues centralized systems.

📊

Actionable Intelligence

Transform raw sensor telemetry into maintenance decisions—not dashboards full of data nobody can act on.

DIFFERENTIATION

FlightEdge vs.
Cloud-Dependent Systems

Dimension
Current Approach
FlightEdge
Inference Location
AWS GovCloud
On-Aircraft / Flightline
Connectivity Required
Continuous
None (Air-Gapped)
Alert Latency
Hours to Days
Sub-Second
Model Bias Mitigation
Fleet-Wide Averaging
Platform-Specific Tuning
Data Movement
Full Telemetry Stream
Minimized Data Packages
OPERATIONAL IMPACT

Measurable Results
Mission Readiness

30-40%
Reduction in Unscheduled Maintenance Events
95%
Target Aircraft Availability Rate
25%
Reduction in Parts Stockpile Requirements
30%
Increase in Sortie Generation Capacity
OUR TEAM

Defense Tech Expertise
Colorado Springs

CMS

Christopher M. Stone

Principal Investigator

Defense Acquisition & AI/ML Systems

LJP

Lucas J. Pick

DevSecOps Engineer

Platform One BigBang & GitOps

FS

Fagana Samadova

Lead Data Scientist

Time-Series & Explainable AI

JS

Jeff Simpson

Lead Full Stack Engineer

Edge Computing & Visualization

GET IN TOUCH

Ready to Transform
Maintenance Operations?

Contact us to discuss FlightEdge deployment for your aviation sustainment mission.