A GPS ping proves a vehicle was on a road. It does not prove who was driving it, whether they were authorized to, or what happened in the four seconds before a harsh-brake event. This is the platform built to answer all three, in real time, at fleet scale.
Edge device to cloud identity provider, decoupled end to end. No tier blocks another.
Event partition, rolling buffer, local SQLite queue, so an incident never loses its video.
Every edge device authenticates on a client certificate before a byte of telemetry moves.
New cabin-safety behaviors ship to the fleet without touching a single piece of hardware.
A commercial fleet technology group serving operators who run mixed HazMat, last-mile delivery and ride-hailing fleets: the segment of the market where "where is the vehicle" has always been solved, and "who is driving it, and how" is the question that actually decides a liability case.
One in-vehicle edge agent, one event backbone, one video pipeline, serving every fleet type the group's customers operate.
Driver-monitoring safety alerts, biometric access control, and on-demand live video to dispatch.
Every fleet type the group's customers run, served without a different architecture behind each one.
A GPS ping proves a vehicle was on a road. What the group's customers were absorbing as risk was everything that ping could not show.
Three things a location signal could not show, and that the group's customers were absorbing as risk instead.
A vehicle ID and a GPS trace say a truck moved from A to B. They say nothing about whether the person behind the wheel was the authorized driver, a sub-contracted operator, or someone who should not have had the keys.
When a harsh-brake or collision event happened, the only record was whatever the driver reported: unverifiable, and useless against a liability claim or an insurance dispute.
Fatigue, distraction and lane departure were things a fleet manager learned about after an incident, from a report, not something the vehicle itself could catch and act on in the moment.
A location ping proves a truck was on a road. It does not prove who was driving it, whether they were fit to, or what happened in the four seconds before the harsh-brake event. Operators were making six-figure liability decisions on the one signal that answers none of that.
At ignition, without bolting on new hardware.
Even under storage or link failure.
And let dispatch see the cabin live, on demand.
Any fleet size can sit behind them.
Zero silent failures. A critical event has to produce evidence even when the storage layer is under contention or the network drops entirely. The moment a fleet needs proof most is exactly the moment conditions are worst.
Runs on commodity in-vehicle IoT hardware and standard cloud primitives the operator can audit. No proprietary black box between the edge and the evidence.
Identity, evidence, live visibility, access and driver communication are not five products bolted together. They are five consumers of the same telemetry stream, each reacting to the events it cares about.
A layered, event-driven microservices architecture built to decouple device ingress, asynchronous event processing and synchronous command routing from each other.
The edge unit is the only device on the network. Everything past the gateway is a Kafka consumer, so adding a service never means touching the vehicle.
Governance lives in one place, the gateway and the identity provider, instead of five services each deciding for itself what a trusted device looks like.
Not just a bandwidth choice. A strict, versioned schema means the contract between edge firmware and cloud services cannot silently drift as either side evolves: a serialization decision doubling as an API contract.
Every microservice is a consumer, never a direct recipient of device traffic. A storm of road-event traffic during rush hour or bad weather backs up the broker, not the geofence check or the dispatcher's UI.
Event partition, then a non-blocking read of the rolling buffer, then a local SQLite queue with exponential backoff. This is the unglamorous logic that decides whether video evidence exists at all when the flash controller locks or the link drops, precisely when a fleet needs it most.
Cellular video is the most expensive resource on the vehicle. The platform keeps it dormant until a dispatcher asks for it, then tears the tunnel down the instant they hang up. Bandwidth spent only when someone is actually watching.
An offline device does not drop a send request, it gets marked Queued and delivered the moment the device reconnects: the same dormant-until-needed instinct behind the video tunnel, applied to voice. A duplicate send is blocked while one is still queued, and only reopens once that request resolves to sent, played, aborted, failed or timed out, so dispatch never wonders whether an announcement actually went anywhere.
Storage fallback logic is the unglamorous five percent of an IoT platform that decides whether the other ninety-five percent is trustworthy in court.
A platform whose output is liability evidence has to treat failure modes as first-class design targets, not edge cases handled by a retry decorator.
On the security side, every device authenticates over a persistent TCP/TLS connection with client-side certificate verification; live video channels are brokered through AWS STS short-lived credentials rather than a standing key. That combination sets a materially higher bar than the password-based auth most IoT fleets still run on.
A password can be shared across a hundred devices. A client certificate and a short-lived STS token cannot. The security model was built to make that distinction, not just document it.
Instant geofence alerts on lane deviation; live DMS streaming lets dispatch confirm alertness on long-haul night transits.
Automated tracking of infractions, phone use and distraction, feeds localized scorecards managers use to curb risky behavior.
Biometric validation blocks unverified operators; automated video upload gives rapid proof to settle disputes and protect liability.
All three run on the same event contract. A new fleet type is a new set of geofence rules and alert thresholds, not a new integration. The same is true for a new way to reach the driver: audio announcements ride the identical send-to-device, queue-if-offline, track-to-resolution pattern already built for video.
The committee did not need to trust a vendor's claim. They could trace every alert back to the exact frame of video that produced it.
New DMS model, shipped OTA to existing camera hardware.
Same containerized update path, no new sensor.
Route-specific alertness thresholds per corridor.
Onboarded against the same event contract, not a new stack.
Six rules, in order, and the platform is an instance of them rather than an exception to them.
Capture at the edge, in a strict schema, from day one.
Authenticate the device before a byte of telemetry moves.
Decouple every consumer through one event broker. Never a direct write.
Fan out to independent services that share a contract, not a database.
Degrade storage in tiers. Never in silence.
Expose identity and video through short-lived cloud credentials, not standing keys.
If where the vehicle is happens to be a solved problem for you, and who is driving it, and how, is not yet, that is the gap this platform was built to close.