Real-Time

On-Device Inference

Ultra-Low

SWaP-C

24/7

All-Weather Coverage

Zero

Cloud Dependency

From Detection to Understanding

The Challenge

Standard Radar Can’t Tell You What It Sees

  • Standard radar tells you where an object is and how fast it’s moving, but it cannot distinguish a bird from a drone or a fan from a person in real-world scenarios.
  • The result: massive false alarms, wasted resources, and operators who can’t trust their own systems.

The Solution

BrainChip Radar Adds Deep Learning to Traditional Radar

  • The Radar Reference Platform analyzes the unique frequency signatures created by moving parts — propeller rotation, wing beats, mechanical vibration.
  • The result: it doesn’t just detect objects; it classifies them with high accuracy, in real time, on device.

Built for Classification

Designed for the Field

Deep Learning Classification

Classifies, identifies, and characterizes aerial objects in real time, distinguishing drones from birds and friend from foe while eliminating false alarm fatigue.

Fast Prototyping

Record custom datasets, configure the radar pipeline, and test new AI models — all from an interactive dashboard.

Ultra-Low Swap-C

Ultra-low SWaP-C in a compact, small, fanless form factor — fully man-portable and easily deployable wherever the threat is.

Fully Customizable

Train on your own data, swap in your algorithms, and adapt the deep learning pipeline to your use case.

Radar Intelligence

Across Critical Sectors

Defense & Tactical Systems
Lightweight, deployable AI designed for accurate, real-time threat classification

Drone Countermeasures
Detect propeller micro-Doppler signatures to trigger precision countermeasures

Health & Biosignal Detection
Immediate gesture recognition, activity monitoring, and fall detection

Marine & Autonomous Platforms
Low-SWaP AI for navigation and obstacle detection on unmanned surface and aerial vehicles

See it in Action!

Join the Akida Radar Platform Webinar

Explore BrainChip’s Akida Radar Reference Platform, including architecture,
Micro-Doppler classification, and drone detection demos.

Join us on 20 April at 8:00 AM PT.