Deepwave provides intelligent RF data and infrastructure, enabling the extraction of insights from RF signals to inform automated systems and workflows. Their patented ARTIFICIAL INTELLIGENCE RADIO TRANSCEIVER (AIR-T) facilitates easier access to RF intelligence for various applications.
Funding
Funding not disclosed
Founders
Product
Problem
Extracting actionable insights from radio frequency (RF) signals is challenging due to the complexity of modern RF environments, which involve a multitude of intertwined signals. Legacy spectrum analyzers and manual monitoring methods struggle to keep pace with rapidly changing signals, leading to inefficient spectrum usage and potential interference issues.
Solution
Deepwave provides an intelligent RF data and infrastructure platform that simplifies the extraction of insights from RF signals, enabling automated systems and workflows. The platform combines the AIR-T, a GPU-based software-defined radio (SDR), with AirStack software to facilitate AI-driven signal processing at the edge. AirStack Core, the centerpiece of the platform, allows for RF signal analysis at the edge, reducing data output and delivering low-latency intelligence. The platform supports a range of applications, including spectrum monitoring, dynamic spectrum sharing, aircraft security, and RF DataOps, by integrating AI and machine learning models directly on GPU-based SDR platforms.
Target Audience
The primary target audience includes RF engineers, AI scientists, telecommunications providers, aviation safety teams, and manufacturing companies seeking to improve spectrum monitoring, enable dynamic spectrum sharing, enhance aircraft security, and streamline RF DataOps.
Features
- AIR-T, a software-defined radio (SDR) with integrated AMD FPGA, multi-core CPU, and NVIDIA GPU
- AirStack Core software for AI-driven signal processing applications
- AirStack BitStream development kit for fine-tuning AIR-T for ultra-low latency RF use cases
- AirStack AirPack, a solution for integrating deep learning into software-defined radio systems
- Real-time spectrum analysis for environmental sensing
- Integration of machine learning models directly on GPU-based SDR platforms
- Support for containerized workflows for fast deployment
- Compatibility with NVIDIA's TensorRT inference accelerator software
- SigMF format support for storing labeled recordings in a structured database
- Remote management and over-the-air updates for scalable edge field deployments