Polyn provides neuromorphic analog front‑end chips (NASP) that perform always‑on AI inference directly on raw sensor data, eliminating the need for ADC conversion. By processing in the analog domain, its chips deliver microsecond‑scale latency with microwatt power consumption, enabling continuous edge AI for voice extraction, speaker recognition, vibration analysis, and automotive sensing. The offering includes ready‑made product families—NeuroVoice, NeuroSense, VibroSense—and customizable neural‑network chips for integration into wearables, automotive sensors, audio devices, smart‑home products, and Industry 4.0 equipment.
Funding
$26.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Edge devices such as wearables, automotive sensors, and smart home appliances require continuous AI inference on raw sensor data, but conventional digital processors consume significant power and introduce latency, limiting battery life and real‑time responsiveness.
Solution
Polyn offers neuromorphic analog front‑end chips (NASP) that perform always‑on processing of raw sensor streams directly in the analog domain. By integrating neural network inference into silicon without digitizing the signal first, the chips achieve microsecond‑scale latency while drawing only microwatts of power. This eliminates the traditional power‑latency trade‑off, enabling ultra‑low‑power, always‑ready AI capabilities for voice extraction, speaker recognition, vibration analysis, and tire‑road grip estimation. The solution is delivered as a family of ready‑made products—NeuroVoice, NeuroSense, VibroSense—or as a customizable neural‑network chip for specific applications. Devices can be integrated with minimal hardware changes, providing on‑device edge AI that operates continuously without draining batteries.
Target Audience
Primary customers are manufacturers of wearables, automotive sensor systems, audio devices, smart‑home products, and Industry 4.0 equipment that require continuous, low‑power AI processing at the edge.
Features
- Analog‑domain neural network inference that processes raw sensor data without ADC conversion
- Microsecond inference latency for real‑time response in voice, vibration, and automotive sensing
- Microwatt power consumption enabling always‑on operation on battery‑powered devices
- Dedicated product families (NeuroVoice, NeuroSense, VibroSense) targeting voice processing, physical AI, and vibration analysis
- Simple integration with existing sensor stacks and standard I/O interfaces
- Customizable NN chip design service for bespoke edge AI workloads