Enterprises will connect to and manage orbital workloads “the same way they manage cloud workloads today,” using optical links, the spokesperson added. The company’s approach is to “continuously launch new hardware and quickly integrate the latest architectures,” with older systems running lower-priority tasks to serve out the full useful lifetime of their high-end GPUs. The company declined to disclose pricing.
Aetherflux plans to launch about 30 satellites at a time on SpaceX Falcon 9 rockets. Before the data center launch, the company will launch a power-beaming demonstration satellite in 2026 to test transmission of one kilowatt of energy from orbit to ground stations, using infrared lasers.
Competition in the sector has intensified in recent months. In November, Starcloud launched its Starcloud-1 satellite carrying an Nvidia H100 GPU, which is 100 times more powerful than any previous GPU flown in space, according to the company, and demonstrated running Google’s Gemma AI model in orbit. In the same month, Google announced Project Suncatcher, with a 2027 demonstration mission planned.
Analysts see limited near-term applications
Despite the competitive activity, orbital data centers won’t replace terrestrial cloud regions for general hosting through 2030, said Ashish Banerjee, senior principal analyst at Gartner. Instead, they suit specific workloads, including meeting data sovereignty requirements for jurisdictionally complex scenarios, offering disaster recovery immune to terrestrial risks, and providing asynchronous high-performance computing, he said.
“Orbital centers are ideal for high-compute, low-I/O batch jobs,” Banerjee said. “Think molecular folding simulations for pharma, massive Monte Carlo financial simulations, or training specific AI model weights. If the job takes 48 hours, the 500ms latency penalty of LEO is irrelevant.”
One immediate application involves processing satellite-generated data in orbit, he said. Earth observation satellites using synthetic aperture radar generate roughly 10 gigabytes per second, but limited downlink bandwidth creates bottlenecks. Processing data in orbit and transmitting only results could reduce latency and communication costs, he said.
