Intelligence that understands the sounds around you.
Shravix is designed to run directly on wearable hardware — keeping detection local, responsive and independent of cloud connectivity. Here's how the system is designed to work, end to end.
From ambient sound to a timely response.
A high-level view of the processing pipeline. Proprietary implementation details, model weights and dataset specifics are not disclosed.
Audio capture
Always-on microphones continuously capture the surrounding acoustic environment alongside playback.
Audio segmentation
Incoming audio is windowed and preprocessed into segments suitable for real-time classification.
Embedded model
A compact MLP-based classifier runs directly on the wearable, without cloud or smartphone dependency.
Hazard classification
The model evaluates each segment for relevant acoustic events — currently tuned to vehicle horns.
Alert generation
When a relevant event is recognized, playback is briefly interrupted with a short spoken warning.
Playback control
After the alert, the listening experience resumes automatically where it left off.
- Ambient audio
- Microphone input
- Audio preprocessing
- MLP-based classification
- Hazard decision
- Interruptive voice alert
- Playback restoration
Prototype validation results.
| Metric | Prototype result |
|---|---|
| Detection accuracy | 94% under stated validation conditions |
| Inference latency | ~30 ms |
| False-positive rate | ~2 / 30 min |
| Inference | On-device |
| Connectivity | No cloud dependency |
| Smartphone dependency | None for classification |
| Technology readiness | TRL4 |
Results reflect prototype validation on development-board-class embedded hardware under the stated metropolitan-noise conditions. This is not a finished consumer wearable, and production performance may vary by hardware, environment and model configuration.
Designed to fit the hardware you already build.
Shravix is designed for programmable Bluetooth audio SoCs, reusing existing microphones where compatible and integrating at the firmware level — with no mandatory cloud service.
- Microphone reuse where compatible
- Runs on programmable Bluetooth audio SoCs
- Uses available DSP headroom
- Modest RAM / Flash footprint
- SDK / reference firmware pathway
Technical eligibility requirements
- Always-on microphones
- Programmable DSP
- Firmware upgradability
- Sufficient RAM / Flash
- Multi-microphone processing
These are technical eligibility requirements for evaluation, not universal guarantees of compatibility.
Protected technology, built for deployment.
The granted patent covers the stated combination of microphone input, MLP-based classification, interruptive voice alert and associated touch-panel control, with a 20-year term.
The patent is one component of a broader defensibility story — not every element below is legally protected, but together they form a practical moat around real-world deployment.
Evaluating Shravix for your platform?
Talk to us about SoC compatibility, integration effort and running a pilot.