Deterministic edge intelligence.
Optimize deep learning models to run directly on legacy microcontrollers. Achieve zero-latency inference on the factory floor without cloud dependencies.
Industrial deployments
Our optimization compiler compresses complex neural networks to execute on rugged hardware. These technical briefs detail active production environments.
01 / Quality Control
02 / Anomaly Detection
03 / AGV Navigation
Deploy deep learning models on high-speed assembly lines. Real-time optical quality control runs locally with sub-millisecond inference speeds on existing microcontrollers.
Monitor vibration and thermal anomalies on legacy pumps and motors. Local neural networks detect structural failure risks without transmitting operational telemetry to the cloud.
Calculate optimal pathing and collision avoidance locally. Fleet navigation models execute on low-power vehicle hardware to guarantee continuous uptime in dynamic warehouses.
SPEC: ARM Cortex-M7 LATENCY: < 0.8ms
SPEC: STM32 MCU LATENCY: < 1.2ms
SPEC: NXP i.MX RT LATENCY: < 1.5ms
Legacy PLC integration
We compile optimized models directly into lean C code, interfacing with standard industrial protocols. Connect to existing Siemens, Rockwell, or Beckhoff controllers via Modbus or OPC UA with zero hardware modifications.
Request evaluation kit
Get the Synaptivon compiler and test model compression on your local hardware.