How does driver monitoring reduce accidents?

Edge models track eye closure (PERCLOS) and head pose. If a driver nods off or looks at a phone, an audible alarm fires within milliseconds, helping lower accident rates.

How is fuel waste reduced?

We correlate driving behavior such as idling and harsh acceleration with engine data, then coach drivers in real time to lower cost per mile.

Can AI predict vehicle breakdowns?

Yes. Models analyze engine vibration and thermal patterns to flag part wear weeks before a roadside failure, so repairs can be scheduled.

What is predictive route optimization?

Beyond distance, we factor in traffic, weather, delivery constraints, and time to park. Vision models find available loading zones to save minutes per stop.

Can drivers do vehicle inspections with a phone?

Yes. A walk-around with a smartphone lets AI identify flat tires, broken lights, or body damage before the truck leaves the yard, replacing paper DVIRs.

Does video go to the cloud?

Not by default. Models run on edge gateways in the vehicle, so video is processed locally within milliseconds, and only safety events are uploaded.

Which hardware do you work with?

We deploy on edge gateways and dashcams such as Lytx or Geotab hardware, and can integrate with your existing telematics platform.

How do you reduce false alarms?

We run driver and road models together, so context matters. Checking a mirror is treated differently from falling asleep.

Can it plug into our existing dashboards?

Yes. Alerts and scores connect to your fleet software through APIs and data pipelines, so teams work in the tools they already use.

How is driver privacy protected?

Privacy mode records only safety events. Routine footage is anonymized or discarded, while critical incidents are kept for coaching and review.

Who can access the video clips?

Access is role-based, so only authorized safety and operations staff can review event clips.

How accurate are the models?

Accuracy depends on your cameras, lighting, and fleet. We validate on your own data in a pilot and tune thresholds before rollout.

How do models stay current?

We monitor performance and use approved feedback and retraining workflows as conditions and vehicles change.

Data is encrypted in transit and at rest, with access controls and audit logs suited to your compliance needs.

What results can we expect?

Reference outcomes include up to 40% lower accident rates, around 20% fuel waste addressed, and 10-15 minutes saved per delivery stop. Actual results vary by fleet.

Do you offer a pilot first?

Yes. A scoped pilot on a small group of vehicles proves value before fleet-wide rollout.

How do you measure ROI?

We agree on metrics up front, such as incidents per million miles, fuel cost per mile, unplanned downtime, and minutes per stop.

Can you run it for us?

Yes. Managed support covers monitoring, retraining, and new use cases after launch.

Where do I start a conversation?

Use any Contact Us or Book a Free Consultation button and we will reply with a scoped proposal.

AI Fleet Management

Real-Time Vision AI For Driver Monitoring And Fleet Optimization

For commercial fleets, last-mile delivery, and telematics providers, we build custom Vision models that detect distracted driving, optimize fuel efficiency, and predict vehicle breakdowns in real-time.

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Aarvexa fleet vision analysis

0%Lower accident rates

0%Fuel waste addressed

0minSaved per delivery stop

IN-CAB VISIONDROWSINESS

RECPERCLOS 8%

DRIVER · FACE 99%

Driver attentive

ROAD AI

CARTRUCK

ENGINE HEALTH

Bearing wear · fails in ~3 weeks

FUEL WASTE

−0%

DRIVER SAFETY SCORE

Fleet average · today

FLEET STATUSmonitoring…

Risk events3 prevented

Fuel waste−20%

Downtimepredicted

Edge AI · results in milliseconds

The problem

Why GPS Tracking Isn't Enough?

Standard telematics tells you where the truck is. It doesn't tell you how it's being driven. Relying solely on GPS and basic sensor data creates four critical blind spots:

The "Distraction" Epidemic

GPS can't see the driver texting. Accidents happen in split seconds. Our in-cab vision AI detects phone usage, fatigue, and seatbelt violations instantly to prevent crashes.

Fuel Waste

Idling and aggressive acceleration burn 20% of your fuel budget. We correlate driving behavior with engine data to coach drivers in real-time, reducing cost per mile.

Reactive Maintenance

Waiting for a "Check Engine" light is too late. Our AI listens to engine vibrations and analyzes thermal patterns to predict part failures weeks before a roadside breakdown occurs.

Route Optimization

GPS only shows where trucks are, not how efficiently they move. Our AI analyzes traffic, weather, and delivery constraints in real time to suggest faster, safer, and more fuel-efficient routes, reducing delays and costs.

Optimize Your Fleet with Vision AI

What we do

AI Fleet Solutions: Driver Monitoring & Smart Routing

Driver Monitoring Systems

Reduce accident rates by 40%. Our edge-native AI tracks eye closure (PERCLOS) and head pose. If a driver nods off or looks at their phone, an audible alarm triggers immediately.

Predictive Route Optimization

For last-mile delivery. We don't just use distance; we use "time to park." Our vision models analyze street-level data to find available loading zones, saving 10-15 minutes per delivery stop.

Automated Vehicle Inspections

Eliminate pencil-whipped DVIRs. Drivers walk around the truck with a smartphone; our AI automatically identifies flat tires, broken lights, or body damage, ensuring the truck is road-legal before it leaves the yard.

How we build

How We Build AI Co-Pilots For Safer, Smarter Driving

Step 1: Edge Inference

Sending live video to the cloud is too slow and expensive. We deploy models on edge gateways (like Lytx or Geotab hardware) to process video locally within milliseconds.

Step 2: Multi-Task Learning

We run simultaneous models: One tracks the driver (Face), one tracks the road (Lane/Object Detection). This contextual awareness prevents false alarms (e.g., checking a mirror vs. sleeping).

Step 3: Sensor Fusion

We fuse camera, accelerometer, and CAN bus data. Hard braking or sudden maneuvers trigger instant video clips, enabling automated coaching and faster incident response across fleets.

Step 4: Privacy-First Archiving

Our privacy mode records only safety events. Routine footage is anonymized or discarded, protecting driver privacy while ensuring critical incidents are captured for coaching and review.

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Tech stack

Our Tech Stack

Technical Stack & Expertise

Generative AI & Models

ChatGPTClaudeLLaMAGeminiDALL·EWhisperStable DiffusionCustom fine-tuned models

Frameworks

PyTorchTensorFlowHugging FaceLangChain

Platforms & Acceleration

OpenAINVIDIA TensorRTRay

Aarvexa AI leverages the world's most powerful AI frameworks, models, and acceleration platforms to build secure, scalable, and production-ready AI solutions. Our expertise spans generative AI, deep learning, MLOps, and high-performance inference.

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Stop reacting to accidents. Start preventing them.

FAQ

Frequently Asked Questions

Straight answers on AI fleet management: driver monitoring, routing, integration, privacy, and results.

It adds vision AI and sensor intelligence to your fleet so you can see how vehicles are driven, not just where they are. It detects risky driving, wasted fuel, and early signs of vehicle failure in real time.

Drowsiness (eye closure and head pose), phone use, distraction, and seatbelt violations, with an immediate in-cab alert and a short video clip for coaching.

GPS shows location and speed. It cannot see a driver texting, measure idling waste, or hear a failing bearing, so incidents and breakdowns are caught only after they happen.

Commercial fleets, last-mile delivery operators, trucking companies, and telematics providers who want to add vision AI to their platforms.

Use the Get a Custom Fleet Solution button. We review your fleet, hardware, and goals, then propose a focused first use case.