Running entirely on consumer hardware, SpeedGuard is proof of how far edge AI can go.
Our computer vision systems bring contextual awareness to cameras
SpeedGuard is a small side project we built to test our real-time perception stack on everyday devices. It runs entirely on consumer-grade phones, with no cloud processing or vehicle integration. Just install, mount, and drive.
What started as a prototype turned into a quiet example of how adaptable our tech can be.
What it does today
SpeedGuard is live and working, with:
Real-time speed sign recognition using your phone’s camera
Manual dashcam recording with GPS tagging
Live map view with speed overlay
All processing happens locally on-device
Driving history and trip stats
It’s free to try, with no accounts, no subscriptions, and no extra hardware required.
What else we can do — on the same hardware
SpeedGuard only uses a fraction of our core platform. From the same model architecture, deployed on mobile devices, we’re able to support:
Automatic event detection (collisions, hard braking, near misses)
Speed camera warnings using fused map + vision inference
Distraction and fatigue detection from inward-facing cameras
“Blackbox” video capture triggered by events or fleet systems
Lane-level positioning from visual data
Drive scoring + coaching powered by vision patterns, not just motion
These capabilities are already live in other environments—commercial fleets, integrated vehicle platforms, and edge devices. SpeedGuard is simply the most accessible demonstration of what’s possible.
Why We Built It
We wanted to show what happens when real-world visual intelligence runs on everyday hardware. No dependencies. No overengineering.
Just a phone and the road.
SpeedGuard is not a product launch. It’s a public sandbox—purposefully simple, to let the core tech speak for itself.
Curious? Let's talk.
If this sparks ideas—for your platform, your stack, or your roadmap—we’d love to hear them.
We’re building the next generation of vehicle intelligence, and we’re building it to run anywhere.
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