Edge Computing meets Logistics

Stop Reacting.
Start Predicting.

We build autonomous neural networks directly into commercial truck cabins. Powered by cutting-edge GPU architecture, FleetOpti AI eliminates latency, prevents mechanical failures, and dynamicly routes fleets globally.

The Legacy Problem

  • Cloud Latency

    Sending gigabytes of raw video and telemetry to the cloud for processing is too slow to prevent high-speed accidents.

  • Reactive Maintenance

    Current systems only alert dispatchers after a component has already failed, leading to costly roadside towing.

The FleetOpti Edge

  • Zero-Latency Inference

    By moving heavy compute to the edge, our models analyze driver state and hazards in milliseconds, completely offline.

  • Acoustic Prediction

    Machine learning identifies micro-anomalies in engine vibration, predicting failures weeks before they happen.

Autonomous Data Pipeline

How we process millions of data points continuously without overwhelming bandwidth.

1. The Edge (In-Cabin)

Cameras and acoustic sensors feed raw, high-throughput data directly into local GPU nodes. Irrelevant data is discarded instantly.

2. Local Inference

Optimized neural networks run hazard detection and fatigue analysis. Only critical alerts and compressed metadata are sent over 5G/LTE.

3. Global Cloud

Metadata from thousands of trucks converges in the cloud. Foundational AI models retrain and update global routing dynamically.

Powered by NVIDIA Ecosystem

Our entire infrastructure, from the truck cabin to the cloud training clusters, relies on purpose-built hardware and software frameworks to achieve industry-leading accuracy.

Jetson Platform

We deploy NVIDIA Jetson Orin modules inside commercial vehicles. This provides server-class AI performance at the edge, capable of running multiple concurrent neural networks for computer vision and telemetry parsing.

TensorRT

To maximize frame rates and minimize power consumption in the cabin, all our proprietary PyTorch models are optimized and compiled using NVIDIA TensorRT for ultra-low latency inference.

Metropolis

Leveraging the Metropolis application framework, we efficiently manage video streams from multiple dash and driver-facing cameras, applying complex analytics to understand spatial dynamics on the highway.

A100/H100 Cloud Compute

The edge is only as smart as the models we train. We utilize scalable GPU clusters to train massive multimodal architectures on petabytes of historical logistics and weather data.

10M+
Miles Analyzed
<10ms
Edge Latency
94%
Failure Prediction
San Francisco
& Kyiv Based

Frequently Asked Questions

Do you replace existing ELD/Telematics providers?

No. FleetOpti AI acts as a sophisticated intelligence layer that sits on top of standard ELD systems. We handle the heavy AI compute, while your existing hardware manages basic compliance reporting.

How do you handle areas with no cellular coverage?

That is exactly why we built an Edge-native platform. Our models run locally on the Jetson module. If a truck enters a dead zone, accident prevention and driver alerts continue to operate at 100% capacity.

Is the hardware included in the subscription?

We operate on an HaaS (Hardware as a Service) + SaaS model. Edge computing units are leased as part of the monthly enterprise contract, ensuring fleets always have the latest GPU capabilities without massive capital expenditure.

Join the Early Access Program

Request API access or schedule a technical demo for your fleet operations team.

We will normally respond within 24 hours.