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Starcloud

Starcloud develops and deploys hyperscale data centers in space to support large-scale AI training clusters. This orbital infrastructure leverages continuous solar energy and radiative cooling to achieve gigawatt-scale compute capacity. The company enables the next generation of AI by overcoming terrestrial permitting and scaling constraints.

Traction 10/10
Redmond, United States · HQ
Founded 20241710K+ followers
  • Artificial Intelligence
  • Hardware
Updated 2 days ago

Funding

Raised to date

$200MRaised 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.

across 3 rounds

+19

$170M · Series A

Announced Mar 2026

Disclosed cumulative: $191M

3/3

Founders

3 founders

Philip Johnston

Redmond, United States

Co-founder & CEO

Profile summary: Opontia (acquired by Perfection) • Co-Founder, Co-CEO, & Board Chair · MBA at The Wharton School

Adi Oltean

Redmond, United States

Co-founder & Chief Engineer

Profile summary: SpaceX • Principal Software Engineer

Ezra Feilden

Redmond, United States

Co-founder

Profile summary: Oxford Space Systems • Senior Mechanical Engineer · PhD at Imperial College London

Product

Problem

Terrestrial data centers face significant limitations regarding permitting processes and energy availability, which constrain the scalability required for hyperscale AI training clusters. These constraints hinder the deployment of the massive computational resources needed for advanced artificial intelligence workloads.

Solution

Starcloud is developing hyperscale data centers in orbit to address the scalability and resource limitations of terrestrial infrastructure. These orbital facilities will leverage continuous solar energy and radiative cooling for efficient, high-density computation. By relocating data processing to space, Starcloud bypasses Earth-based permitting hurdles and provides access to virtually unlimited energy resources. This enables the deployment of the next generation of AI training clusters, unburdened by the physical constraints of our planet.

Target Audience

The primary customers are organizations requiring massive computational power for AI model training, particularly those facing scalability challenges with existing terrestrial data center solutions.

Features

  • Orbital data center infrastructure designed for hyperscale AI workloads.
  • Utilization of 24/7 solar energy for consistent power supply.
  • Application of radiative cooling techniques for thermal management.
  • Architecture optimized for high-density computational deployments.
  • Mitigation of terrestrial permitting and energy availability constraints.
This profile is AI-generated and may contain inaccuracies.