Market opportunity
Sound is the most ubiquitous untapped sensor input in IoT. Acoustic event detection enables always-on, cloud-free intelligence in any device with a microphone — a capability increasingly mandated in industrial safety, healthcare monitoring, and smart infrastructure.
What SensiML brings to market
SensiML's acoustic recognition engine combines proprietary signal processing, feature extraction, and classification techniques to deliver accurate sound recognition in extremely compact code. Unlike general-purpose ML frameworks that require cloud inference, SensiML models execute entirely at the sensor endpoint — enabling real-time response where latency and connectivity constraints rule out cloud-dependent approaches.
Capabilities & IP
98.8%
Demonstrated accuracy on industrial pump state monitoring
Validated across 5 distinct operating states including fault conditions — production-ready, not lab results.
≤256kB
Compact model footprint — runs on the smallest MCUs
Models as small as 40kB. No external memory or cloud dependency required.
6+
Vertical markets with active deployments
Industrial, healthcare, agriculture, consumer, commercial, and security.
Proven use cases
- Pump blockage and cavitation detection
- Livestock health and welfare monitoring
- Motor and drivetrain fault diagnosis
- Building and perimeter security alerting
- Cough and respiratory event detection
- Fan anomaly and bearing failure detection
IP & technical differentiators
- Proprietary pipeline: signal processing → feature extraction → classification
- Model compression to ≤40kB without accuracy loss
- Vendor-agnostic: deploys across 20+ silicon partner platforms
- Custom Professional Services for turnkey acoustic model delivery
- Licensable training datasets across multiple acoustic domains
SensiML has over a decade of production deployments across acoustic sensing use cases — creating a compounding dataset and validation moat that is extremely difficult for new entrants to replicate quickly.
See it in action
Acoustic Event Detection Pipeline
Proprietary signal processing, feature extraction, and classification — optimized for compact edge deployment.
Pipeline docs →
Pump State Monitoring Demo
98.8% accuracy across five pump states — production-validated on real industrial equipment.
Additional Acoustic Event Demos
