Artificial Intelligence Radio - Transceiver (AIR-T)

by Deepwave Digital

A high-performance SDR seamlessly integrated with state-of-the-art deep learning hardware

View all updates Apr 02, 2019

Shipping Has Begun!

AIR-T has officially started shipping! We expect all units to be shipped to Crowd Supply’s warehouse within the next 10 days. From there, it will take another few business days to get them out to backers. When your order ships, you will receive a shipping confirmation email with a tracking number from Crowd Supply. If you need to confirm or update your shipping address, please log in to your Crowd Supply account.

While you wait for your AIR-T, check out our tutorial on getting started with the AIR-T.

The team at Deepwave Digital would like to thank everyone for their patience and we will be reaching out to hear your feedback on the product in the near future.

The Deepwave Digital team

$199,313 raised

of $20,000 goal

996% Funded! Order Below

Product Choices


Air-T With Enclosure

The AIR-T is the first platform that enables out-of-the-box machine learning wireless systems. Simply port current GNURadio or code directly in Python to access the radio frequency spectrum. Includes, AIR-T board, four MCX-to-SMA cables, getting started tutorial, and power supply. The Air-T enclosure is expertly constructed from aluminum to produce a polished, elegant, and sleek metallic silver finish. It measures 192 x 182 x 79 mm (7.5 x 7.2 3.1 inches) and the power button illuminates blue when they system is on. All RF ports are brought to the front of the enclosure for ease of use and all computer peripherals connections are brought to the rear.


Deepwave Digital

We are a dedicated team of radio frequency and wireless industry experts with over fifty years of combined experience providing digital signal processing solutions to the commercial and defense industries. We understand both the technical capabilities as well as the limitations of these technologies, leading us to develop novel hardware and software solutions to combine the fields of artificial intelligence and signal processing.

John Ferguson

Steven Kline

Peter Witkowski

Steve Lisi

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