01 — SENSOR
One sensor per tire.
Internal TPMS sensor reads PSI, temperature, and wear behavior in real time. No external valve cap. No manual reads.
TIRE TELEMETRY FOR FLEETS
The tire that fails always gave signals first.
Tires represent 20–30% of fleet operating cost. Most fleets still manage them reactively—after heat, pressure loss, or uneven wear has already started. A single blowout at highway speed becomes a $40,000 incident once you count downtime, roadside service, cargo delays, and damage exposure.
Built for fleets running 10–500 tractors across Mexico and the US.
Proprietary AI Models
We don't just track tires. We predict exactly when they fail.
Most fleet software relies on historical averages or driver guesses. NERVE Labs AI ingests millions of live data points—micro-pressure drops, thermal spikes, and wear anomalies—straight from the hardware. Our models predict the precise failure window of a tire before the naked eye can detect wear.
Hardware-Enabled AI
We own the data source. Our sensors feed unfiltered, high-frequency telemetry directly into our neural networks.
Dynamic Forecasting
Adjusting expected wear curves instantly based on route geography, atmospheric heat, and load weight.
AI Inference Matrix
Failure Probability (Next 48h)
Confidence
98.4%
T1-R1 (Steer)
0.02%
T3-L2 (Drive)
14.5%
TR-R4 (Trailer)
89.2% →
CRITICAL INTERVENTION
T-MINUS 1.4 HOURS
Thermal runaway curve detected. Recommend immediate route diversion to nearest service yard to avoid
highway blowout.
From checking tires after the route to knowing which tire is becoming a problem before the route breaks.
Telemetry loop
Sensor to signal to action. The full loop.
18 internal sensors per full tractor-trailer configuration. 10 on the tractor. 8 on the trailer. Pressure, temperature, and wear behavior flow from the tire through the gateway to the cloud model that scores risk and fires alerts before the window closes.
02 — GATEWAY
One gateway per truck.
RF signals from all 18 sensors aggregate in the cab-mounted gateway. Data moves to the cloud over LTE with no driver interaction.
03 — AI RISK WINDOW
Predicted failure windows, not just alerts.
The cloud model scores each tire against behavior baselines, flags deviations, and forecasts the failure probability window so dispatch can act before the truck leaves the yard.
What you actually see
Live tire state across every unit in the fleet.
Your maintenance team does not need another dashboard. They need to know which tire will fail next. NERVE Fleet Console shows pressure, temperature, and wear by position, per truck, in real time. One alert panel. No noise.
NERVE Fleet Console
Fleet Health Score
87/100
Live monitored units
128
across active fleet
Next predicted failure
MX-184
36h risk window
Active alerts
1
1 warning, 0 critical
UNIT MX-184 — TRACTOR + TRAILER SENSOR ARRAY
Numbers that matter
12–18%
Reduction in tire cost from earlier intervention, better casing protection, and fewer emergency replacements.
2–4%
Fuel savings from maintaining pressure closer to optimal operating range across every axle.
30–45%
Fewer tire-related roadside incidents across fleets running active telemetry and predictive alerting.
Estimated ranges based on fleet maintenance benchmarks, TPMS adoption studies, and internal pilot assumptions. Final ROI depends on route profile, fleet behavior, tire program, and maintenance response time.
Who this is for
NERVE Labs is built for fleet operators with 10–500 trucks running national, regional, or cross-border routes across Mexico and the United States. The best fit is an operator that already knows tires are expensive, already has maintenance discipline, but still lacks live visibility into what is happening between inspections—on long-haul corridors, under cross-border pressure, with a maintenance team managing too many assets manually and no early signal before the next roadside event. Operators with smaller fleets starting from 10 units are equally well served—early adoption means full visibility from day one as the fleet grows.
Start here
Pilot it on 3 trucks.
Request a pilot — we’ll install on 3 trucks and prove ROI in 30 days.