Galamad Aerospace designs and manufactures mass‑produced spacecraft platforms, such as the PROSat, that serve telecommunications and power‑beaming applications.
Funding
Funding not disclosed
Founders
Product
Problem
Space satellite production is constrained by high manufacturing costs, limited scalability, and a lack of reusability, making it difficult for operators to deploy large constellations for communications and power‑beaming applications.
Solution
Galamad Aerospace separates spacecraft engineering from assembly, allowing a lean design team to create satellite platforms in Singapore while mass‑producing and testing them in a low‑cost African facility. The company applies artificial‑intelligence‑driven design optimisation, autonomous navigation, and on‑orbit decision‑making to produce reusable, programmable satellites. After completing a mission, a satellite can be recovered, refurbished, and relaunched, extending its service life and reducing per‑mission expense. Standardised, modular hardware combined with software‑defined subsystems enables rapid reconfiguration for diverse telecom and power‑beaming tasks. This approach lowers entry costs for customers and supports the rapid scaling of satellite constellations.
Target Audience
Primary customers are satellite operators and service providers seeking cost‑effective, reusable platforms for telecommunications constellations and space‑based power‑beaming solutions.
Features
- AI‑assisted design optimisation that reduces mass and improves performance across the spacecraft lifecycle
- Modular, software‑defined architecture allowing hardware reconfiguration and in‑orbit software updates
- Built‑in reusability with refurbishment‑ready structures and propulsion for multiple launch‑recover‑relaunch cycles
- Autonomous navigation and on‑orbit decision‑making algorithms to manage traffic and optimise manoeuvres without ground intervention
- Low‑cost, high‑volume assembly and testing operations located in Africa, leveraging a large workforce for economies of scale
- Standardised testing and quality‑control processes derived from “old‑space” practices combined with modern AI tools