Applications: Intelligence in ActioN

We build focused ML solutions for critical tasks.

Below are examples of how we embed intelligence into existing hardware to create immense value.

Predictive Maintenance on CNC Tooling: A low-res camera captures an image of a tool tip. A Cortex-M4 runs a binary classifier to determine TOOL_OK or TOOL_DAMAGED in milliseconds, preventing scrap and downtime.
Consumable Spool Monitoring: A tiny, battery-powered camera monitors the diameter of a material spool. The model classifies its state as FULL, LOW, or EMPTY, sending a LoRaWAN alert to prevent production line halts.
Acoustic Anomaly in Fuel Injectors: A contact microphone on a fuel rail listens to an injector's "tick." An anomaly detection model on a Cortex-M MCU identifies the muffled acoustic signature of a leaky injector long before it triggers a standard engine fault code.

On-Shelf Availability: A low-power camera on a shelf edge is trained on the visual of a "fully stocked" state. When a gap appears, a Cortex-M33 detects the anomaly and sends a STOCK_LOW alert to staff, preventing lost sales.

Propeller Integrity on Commercial Drones: A dedicated accelerometer and Cortex-M4 on each drone motor arm run a high-frequency vibrational anomaly detection model. It senses the unique signature of a cracked propeller, allowing the flight controller to issue a "Land Immediately" warning and prevent catastrophic failure.

Standardized Alarm Detection: The always-on Cortex-M chip in a smart speaker, already listening for a wake-word, runs a second parallel model. It's trained to recognize the universal T3 (smoke) and T4 (CO) alarm patterns, turning the speaker into a critical safety device via a simple firmware update.
Washing Machine Bearing Failure: A washing machine's existing IMU, used for load balancing, is repurposed. A new model on the main MCU learns the machine's healthy vibrational signature and detects the subtle changes that predict a bearing failure months in advance, issuing a "Service Recommended" alert.