Aspinity develops near-zero power analog machine-learning technology, centered on its RAMP™ (Reconfigurable Analog Module Processor) platform and the AML100 analog machine learning core. RAMP merges ultra-low-power analog processing with machine learning and software programmability to perform inference on raw analog sensor data. The AML100 runs in the analog domain, consumes tens of microamps, and keeps MCUs and digital processors asleep until meaningful events are detected. Aspinity provides a python-based SDK for development, testing, and verification of analog ML models across multiple inferencing applications. The company targets smart home, IoT, consumer, industrial, medical and automotive use cases, and is working with customers worldwide to integrate its technology into home security systems, automobiles, and condition monitoring equipment. Financially, Aspinity has closed a $5 million Series B and its total funding now exceeds $19 million. Aspinity designs ultra-low-power analog machine-learning processors that run on proprietary analog circuit technologies to extend battery life in always-on sensing devices. Its technology targets acoustic, vibrational and other ambient triggers to enable low-power wake-up and sensing. The company focuses on applications including voice/sound wake-up, industrial machine health monitoring, wearable health monitoring, and other IoT, consumer, industrial and biomedical uses. Aspinity plans to deploy its first neuromorphic analog-processing chip and to scale volume production. The company also intends to expand technical and partner support teams to accelerate deployments. Aspinity was founded in 2015 and is based in Pittsburgh, PA; it recently completed a Series A financing.

Total raised

$10M

Funding rounds

2

Latest round

Series B

Latest activity

Sep 2023