Space
Galileo builds AI-powered orbital intelligence satellites that combine electro-optical imagery and radio frequency signal collection on a single spacecraft. Onboard edge computing classifies signals in orbit and autonomously cues the camera, delivering a fused answer to warfighters instead of raw data streams. The company completed a live fusion demonstration at Space Systems Command and plans its first launch in Q4 2027 or Q1 2028.
- Space Technology
- Defense Tech
- Data & Analytics
- Artificial Intelligence
- Hardware
Funding
Funding not disclosed
Founders
Founder details are not available yet.
Product
Problem
The current orbital intelligence paradigm forces warfighters to wait for raw satellite data to be downlinked and processed on the ground, creating delays between collection and actionable insight. Separate electro-optical and radio frequency collection systems require ground teams to manually reconcile disparate data sources, slowing the path from tasking to intelligence.
Solution
Galileo builds AI-powered orbital intelligence satellites that integrate electro-optical imagery and radio frequency signal collection on a single spacecraft. Onboard edge compute classifies signals in orbit, cues the camera to relevant activity, and reads the scene in the band that resolves it—all without waiting for ground station processing. The satellite fuses EO and RF data before downlink, delivering one consolidated answer to warfighters instead of raw data streams. A completed government demonstration with Space Systems Command validated the RF classification and EO fusion approach, and the company has received endorsement from two Space Force System Deltas and AFRL.
Target Audience
Primary customers are U.S. Department of Defense organizations, particularly the U.S. Space Force and its System Deltas, along with intelligence agencies that require timely, fused orbital intelligence for operational decision-making.
Features
- Combined electro-optical and radio frequency collection on a single spacecraft bus, eliminating cross-sensor reconciliation
- Onboard edge computing that classifies RF signals in orbit and autonomously cues the EO camera to detected activity
- Fused multi-intelligence output delivered as a single answer, reducing the tasking-to-intelligence timeline
- Live fusion demonstration completed at Space Systems Command, LA AFB
- Classifier trained and benchmarked on live RF captures, with first contract under evaluation
- First launch planned for Q4 2027 / Q1 2028 with payload build and test in progress