Edge AI fleet maintenance processes vehicle data locally — on your depot server, not a remote cloud — delivering predictive fault alerts in under 200 milliseconds. For fleets in remote corridors, restricted-network environments, or air-gapped government operations across the USA, UK, Canada, Germany, Australia, and UAE, Oxmaint's on-premise edge platform delivers full AI predictive maintenance without cloud dependency, data sovereignty risk, or per-vehicle subscription costs.
EDGE AI · ON-PREMISE DEPLOYMENT · OXMAINT
Real-Time Fleet Intelligence — Without Cloud Dependency
Oxmaint edge AI runs on your depot servers. No cloud latency. No data risk. Full predictive maintenance in air-gapped or remote environments.
Why Edge AI — Four Reasons Fleets Are Switching
Under 200ms Alerts
Faults flagged locally before the next engine cycle — not after a cloud round-trip.
Zero Cloud Dependency
Works fully offline — mines, offshore terminals, tunnels, restricted government fleets.
Data Sovereignty
Vehicle telemetry and fault history never leave your premises or jurisdiction.
Scales On Your Terms
Add vehicles and depots without increasing cloud costs or renegotiating SaaS contracts.
Edge AI vs Cloud AI — Decision Matrix
Fleet Maintenance: Edge AI vs Cloud AI
Based on deployments — USA, UK, Germany, UAE, Australia, Canada
Edge AI (On-Premise)
Cloud AI
Alert Latency
Under 200ms
2–8 seconds
Works Offline
Full capability
No
Data Sovereignty
On-premises
Third-party servers
Remote / Rural Fleets
Fully supported
Connectivity required
Upfront Hardware Cost
One-time investment
Low / none
Recurring Subscription
Optional / minimal
Scales with fleet
Air-Gapped Deployment
Supported
Not possible
SAP / PLC Integration
Direct local API
Via cloud connector
Technologies That Make Edge AI Work
Six components work together in Oxmaint's edge stack — all running on your local infrastructure.
AI Camera Vision
Detects tyre wear, brake degradation, and fluid leaks locally — no image data leaves the depot.
OBD-II Gateway
Fault codes, DPF status, and engine load stream into the edge AI model — no cellular plan needed.
AI Digital Twin
Virtual vehicle replica runs on local servers — simulating failures without sending data externally.
PLC / SCADA Connector
Depot controllers feed pressure, temperature, and cycle data into the edge AI via local network.
SAP PM Integration
AI-generated work orders push directly into SAP PM via local API — no cloud middleware.
Predictive ML Engine
Fleet-specific ML models run on local GPU — improving accuracy from your own operational history.
Oxmaint Edge Platform — What You Get
Asset Energy Baseline
FOUNDATION
Consumption baselines stored locally. 5–10% deviation auto-triggers an on-site efficiency investigation.
Run Hours & Logging
DATA
Energy estimates accurate to 5–8% stored entirely on your local server — no cloud billing per asset.
Efficiency Alerts
TRIGGER
Consumption above baseline raises a work order instantly — inspect coils, valves, or traps without cloud latency.
Carbon Intensity Reporting
ESG
Asset-level ESG reports generated on-premise — no operational data sent to external services.
Failure Forecasting
FORECAST
12–36 month forecasts from local historical data — no external AI API calls or per-query charges.
Audit-Ready Records
COMPLIANCE
Every alert and intervention stored locally with timestamp and technician ID — FMCSA and ISO 55001 ready.
"After switching to Oxmaint edge, our remote fleet in Northern Alberta no longer loses AI monitoring when satellite drops. Uptime improved by 38% in six months."
— VP Fleet Operations, Energy Sector Logistics, Alberta Canada · 2025
OEE Framework — Measuring Edge AI Maintenance Performance
Edge-AI-maintained fleets measure effectiveness against Availability × Performance × Quality. Oxmaint tracks all three on-premise — no internet required.
OEE Benchmark — Edge AI vs Industry Average
Industry average vs world-class targets for edge-AI-maintained fleets
A
AVAILABILITY
Actual run hours ÷ scheduled. Edge AI eliminates unplanned outages.
×
P
PERFORMANCE
Actual output ÷ maximum possible. Edge AI removes derating from preventable degradation.
×
Q
QUALITY
Usable output ÷ total. Edge AI catches calibration drift before quality events occur.
=
OEE
OEE SCORE
Every percentage point = real uptime and real revenue recovered.
Industry Avg~60–68%
World Class85%+
Frequently Asked Questions
What hardware does Oxmaint edge AI require?
Standard x86 Linux server (16GB RAM, 4-core CPU) or Nvidia Jetson module. Deploy on existing depot IT — no proprietary hardware.
Can edge AI work completely offline?
Yes — fully air-gapped. Model updates delivered via encrypted USB or local network. No internet needed day-to-day.
How does edge AI integrate with SAP PM?
Via local REST API or RFC connector — AI work orders push into SAP directly, no cloud middleware required.
Is on-premise more expensive than cloud software?
Upfront hardware is higher, but 3-year total cost is 30–45% lower for 50+ vehicle fleets — no per-vehicle fees compounding with fleet size.
Does it work with OBD-II devices already on our fleet?
Yes — all major OBD-II gateways supported via WiFi, CAN bus, or Bluetooth. Data processed on-site, never transmitted externally.
How long does deployment take for a 50-truck fleet?
2–4 weeks — hardware setup, OBD-II pairing, SAP integration, and first AI baselines running within 30 days of go-live.
Deploy Edge AI on Your Terms
Full AI predictive maintenance on your hardware — no cloud, no data risk.
