Artificial Intelligence Radio - Transceiver (AIR-T)

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Jul 12, 2018

$4,995 Reduced Pricing!

Hello Everyone,

The Deepwave Team has received many emails and comments regarding the AIR-T. From questions and explanations, to motivating words of encouragement, we have received a plethora of people and industry interested in the AIR-T and what Deepwave is up to. More importantly, we are taking actions to meet your needs. Out of all of the feedback, one of the recurring themes is, I love the AIR-T, but it’s just too expensive.

Fair point. While the eventual price of the AIR-T needs to cover our expenses, including ongoing support, we realize you, as our first customers, are taking a chance on us and are giving us valuable feedback, and should therefore receive a significant discount. As such, we’ve decided to reduce the price to $4,995. This price will only be available during the crowdfunding campaign.

Thanks for your support!
The Deepwave Team

$56,517 raised

of $20,000 goal

Funded! Order Now

Aug 14

funded on





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Thanks for helping make the AIR-T a reality! You will be rewarded with good karma and regular backer updates.



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. Save 10% off of MSRP.


MCX-to-SMA Cables (6 Pack)

A set of six MCX-to-SMA cables allows for easy access to all the AIR-T MCX connections simultaneously. Each cable is 6 inches (15.24 cm) long with a male MCX right-angle connector and a female SMA (bulkhead style) connector.

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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

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