Hawkeye 360 provides global, satellite‑based geospatial intelligence on radio‑frequency emissions. Its platform continuously collects RF data from a low‑Earth‑orbit constellation, uses machine‑learning to classify emitters and triangulate sub‑kilometer locations, and delivers the processed information via a secure web portal and API for defense, security, and commercial users.
Funding
$40M 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
Organizations that rely on radio frequency (RF) spectrum lack a comprehensive, real‑time view of terrestrial and space‑based emitters, making it difficult to detect, classify, and locate signals that could affect security, operations, or commercial services. Existing monitoring solutions are often ground‑based, regionally limited, or require costly custom sensor deployments.
Solution
Hawkeye 360 delivers geospatial intelligence by fusing commercial satellite imagery with proprietary signal‑processing algorithms to detect, characterize, and geolocate RF activity worldwide. The platform continuously ingests raw RF measurements from a constellation of low‑Earth‑orbit satellites, applies machine‑learning classifiers to identify emitter types, and triangulates precise coordinates for each source. Processed data are made available through a secure web portal and API, enabling customers to query historical and near‑real‑time signal events. By abstracting the underlying sensor network, Hawkeye 360 provides actionable insight without the need for on‑site hardware, supporting rapid decision‑making for defense, security, and commercial use cases.
Target Audience
Primary customers include national security and defense agencies, intelligence analysts, and commercial enterprises such as telecom operators, infrastructure owners, and satellite service providers that require precise RF situational awareness.
Features
- Satellite‑based RF detection covering the entire globe with revisit times under 30 minutes
- Automated emitter classification (e.g., radar, communications, navigation) using deep‑learning models
- Sub‑kilometer geolocation accuracy achieved through multi‑satellite triangulation
- Real‑time data pipeline that normalizes, timestamps, and stores signal metadata in a cloud data lake
- RESTful and WebSocket APIs for seamless integration with GIS, SIEM, and mission‑planning tools
- Role‑based access control and end‑to‑end encryption to meet classified and commercial data‑security requirements
- Customizable alert engine that triggers notifications based on frequency bands, geographic zones, or emitter signatures
- Historical archive spanning multiple years for trend analysis and post‑event forensics